From 666d5b64cb0b070f85aca390f4d806e3bfef789e Mon Sep 17 00:00:00 2001
From: pratikunterwegs <pratikgupte16@gmail.com>
Date: Tue, 23 Apr 2024 13:09:42 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20epiverse?=
 =?UTF-8?q?-trace/epidemics@ac85fa8fa4dcdeca18181b797bf81b1cd969a2d9=20?=
 =?UTF-8?q?=F0=9F=9A=80?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 404.html                                      |  21 +-
 LICENSE-text.html                             |  19 +-
 LICENSE.html                                  |  19 +-
 apple-touch-icon-120x120.png                  | Bin 16452 -> 16452 bytes
 apple-touch-icon-152x152.png                  | Bin 22185 -> 22185 bytes
 apple-touch-icon-180x180.png                  | Bin 27090 -> 27090 bytes
 apple-touch-icon-60x60.png                    | Bin 5705 -> 5705 bytes
 apple-touch-icon-76x76.png                    | Bin 8334 -> 8334 bytes
 apple-touch-icon.png                          | Bin 27090 -> 27090 bytes
 articles/design-principles.html               |  63 +-
 articles/epidemics.html                       |  42 +-
 articles/finalsize_comparison.html            |  31 +-
 articles/index.html                           |  29 +-
 articles/model_diphtheria.html                |  21 +-
 articles/model_ebola.html                     | 612 ++++++------------
 .../figure-html/fig-initial-1.png             | Bin 0 -> 333764 bytes
 .../figure-html/unnamed-chunk-11-1.png        | Bin 0 -> 418137 bytes
 .../figure-html/unnamed-chunk-16-1.png        | Bin 0 -> 410648 bytes
 .../figure-html/unnamed-chunk-8-1.png         | Bin 0 -> 419357 bytes
 articles/model_vacamole.html                  |  23 +-
 articles/modelling_interventions.html         |  38 +-
 .../modelling_multiple_interventions.html     |  21 +-
 articles/modelling_rate_interventions.html    |  21 +-
 articles/modelling_scenarios.html             |  21 +-
 articles/modelling_time_dependence.html       |  25 +-
 articles/modelling_vaccination.html           |  22 +-
 authors.html                                  |  33 +-
 deps/bootstrap-5.3.1/bootstrap.min.css        |   4 +-
 favicon-16x16.png                             | Bin 1280 -> 1280 bytes
 favicon-32x32.png                             | Bin 2526 -> 2526 bytes
 index.html                                    |  68 +-
 news/index.html                               |  70 +-
 pkgdown.js                                    |   8 +-
 pkgdown.yml                                   |   6 +-
 reference/as.intervention.html                |  17 +-
 reference/as.vaccination.html                 |  17 +-
 reference/assert_intervention.html            |  17 +-
 reference/assert_population.html              |  17 +-
 reference/assert_vaccination.html             |  17 +-
 reference/cross_checking_inputs.html          |  17 +-
 .../cumulative_contacts_intervention.html     |  17 +-
 reference/cumulative_rate_intervention.html   |  21 +-
 reference/dot-intervention_on_rates.html      | 140 ++++
 reference/dot-model_default_cpp.html          |  17 +-
 reference/dot-model_diphtheria_cpp.html       |  17 +-
 reference/dot-model_ebola_internal.html       | 219 +++++++
 reference/dot-model_vacamole_cpp.html         |  17 +-
 reference/dot-ode_model_default.html          |  19 +-
 reference/dot-ode_model_vacamole.html         |  19 +-
 reference/dot-prepare_population.html         |  17 +-
 reference/epidemic_size.html                  |  92 ++-
 reference/epidemics-package.html              |  23 +-
 reference/index.html                          |  27 +-
 reference/intervention.html                   |  21 +-
 reference/intervention_constructor.html       |  17 +-
 reference/model_default.html                  |  17 +-
 reference/model_diphtheria.html               |  17 +-
 reference/model_ebola.html                    | 164 +++--
 reference/model_vacamole.html                 |  17 +-
 reference/new_infections.html                 |  17 +-
 reference/output_to_df.html                   | 148 +++++
 reference/population.html                     |  17 +-
 reference/prepare_default_args.html           |  17 +-
 reference/prepare_diphtheria_args.html        |  17 +-
 reference/prepare_ebola_args.html             | 150 +++++
 reference/prepare_vacamole_args.html          |  17 +-
 reference/print.population.html               |  19 +-
 reference/print.vaccination.html              |  19 +-
 reference/print_intervention.html             |  23 +-
 reference/vaccination.html                    |  19 +-
 reference/validate_intervention.html          |  17 +-
 reference/vector_recycling.html               |  17 +-
 search.json                                   |   2 +-
 sitemap.xml                                   |  18 +-
 74 files changed, 1658 insertions(+), 1076 deletions(-)
 create mode 100644 articles/model_ebola_files/figure-html/fig-initial-1.png
 create mode 100644 articles/model_ebola_files/figure-html/unnamed-chunk-11-1.png
 create mode 100644 articles/model_ebola_files/figure-html/unnamed-chunk-16-1.png
 create mode 100644 articles/model_ebola_files/figure-html/unnamed-chunk-8-1.png
 create mode 100644 reference/dot-intervention_on_rates.html
 create mode 100644 reference/dot-model_ebola_internal.html
 create mode 100644 reference/output_to_df.html
 create mode 100644 reference/prepare_ebola_args.html

diff --git a/404.html b/404.html
index cb873c32..9f2159cc 100644
--- a/404.html
+++ b/404.html
@@ -16,7 +16,7 @@
 <link href="https://epiverse-trace.github.io/epidemics/deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="https://epiverse-trace.github.io/epidemics/deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
 <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous">
-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="https://epiverse-trace.github.io/epidemics/pkgdown.js"></script><meta property="og:title" content="Page not found (404)">
+<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="https://epiverse-trace.github.io/epidemics/pkgdown.js"></script><meta property="og:title" content="Page not found (404)">
 <meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg">
 <!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -33,12 +33,12 @@
     <a href="https://epiverse-trace.github.io/epidemics/#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="https://epiverse-trace.github.io/epidemics/logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="https://epiverse-trace.github.io/epidemics/index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -84,11 +84,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="https://epiverse-trace.github.io/epidemics/news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
 <li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
@@ -114,13 +113,11 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer>
diff --git a/LICENSE-text.html b/LICENSE-text.html
index b3df2498..26051416 100644
--- a/LICENSE-text.html
+++ b/LICENSE-text.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>License • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="License"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>License • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="License"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -81,7 +80,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
       
     </div>
 
-<pre>YEAR: 2023
+<pre>YEAR: 2024
 COPYRIGHT HOLDER: epidemics authors
 </pre>
 
@@ -89,11 +88,11 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/LICENSE.html b/LICENSE.html
index d91b44c6..2062a671 100644
--- a/LICENSE.html
+++ b/LICENSE.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>MIT License • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="MIT License"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>MIT License • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="MIT License"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -83,7 +82,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
 <div id="mit-license" class="section level1">
 
-<p>Copyright (c) 2023 epidemics authors</p>
+<p>Copyright (c) 2024 epidemics authors</p>
 <p>Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:</p>
 <p>The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.</p>
 <p>THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</p>
@@ -93,11 +92,11 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/apple-touch-icon-120x120.png b/apple-touch-icon-120x120.png
index d5c7fa4730fd650b13ea6525d6f451d2dce2adfc..48aa59157c9a8bba727400dd8542c3102f76abcf 100644
GIT binary patch
delta 99
zcmX@oz<8vAaY7|0i#RX4PW73|_ck_h+k2Sk8X1Qe8e18dTbY<>8yHv_7<}8Cz{|kE
npjzS@QIe8al4_NkpOTqY$zWt)WTI<;MML|88yhEIwa*6t<~<&k

delta 99
zcmX@oz<8vAaY7|0vzP#%=<7`FlN+13?LCZjjf_GJ&8!Sftc(n`4GgRd3^r<Yt1~b#
msFt`!l%yn<q*~?Xr(~v8G8h>cndll|(Qu&Lc=qJ0_W1ynUL1`8

diff --git a/apple-touch-icon-152x152.png b/apple-touch-icon-152x152.png
index 5fb9b4a212ba52d3b0f1c43d974ccc194043ccf7..3256f57dd9a049b504253f2ed4497cf800e7095a 100644
GIT binary patch
delta 99
zcmZ3vmT~1;#tD_2EaJTEx;&>Bdu(hf2=y@0H8Kt{G`2D@w=yx+HZZU<FbFu6y_11~
nLAAs+q9i4;B-JW6KP5A*lEKKp$VArwiw4E%msuxUh2;YP#7!K0

delta 99
zcmZ3vmT~1;#tD_2%wht3Vnqp6#T%OnLOqOijf_GJ&8!Sftc;Ab4GgRd3>pqi+{M7a
mpjzS@QIe8al4_NkpOTqY$zWt)WTI<;MZ?GWnrxG;!tw#osT|w@

diff --git a/apple-touch-icon-180x180.png b/apple-touch-icon-180x180.png
index 892e55cda6e78b1e07ea93aaaaf8c7b3614fbe05..b327925058526052317d12d0a2684363ceacc3f0 100644
GIT binary patch
delta 99
zcmca~neozP#tD_2EaJTEdQ%U5`n0iWW`>7}u90zwp|O>Lxs{2Twt<0_fkC2Dp$Y>7
ngKCLuL`h0wNvc(DeoAIqC4-THk%_JW77YURCudAf&ddh@Q05*;

delta 99
zcmca~neozP#tD_2%wht3;;iXjPd7Hr%<wSQH8Kh@G_x`^u`)8&HZZU<Fi_h%i;sbU
nLAAs+q9i4;B-JW6KP5A*lEKKp$VArwi-zzQN}DDpXXXO{+IAfq

diff --git a/apple-touch-icon-60x60.png b/apple-touch-icon-60x60.png
index ce7a95b987bf60e60e2835a29e47520c086011b5..52c287d46f7c84e10970ce9c5c49fce3d250bb9a 100644
GIT binary patch
delta 97
zcmX@9b5dtQB`1qGFT2*H^=7X(HVKG&nCKcAhZq`L8JJs{7-<_ASQ!{h%?&kYU|>)!
kag8WRNi0dV%FR#7OsixtGB7gHHNc|biNV|M$+txF0b8gXS^xk5

delta 97
zcmX@9b5dtQB`33(0H07P@4l>!O#-4G#=1sEA%<pFh9*{q7TN{|Rt5&EY)^_aFfgc=
kxJHzuB$lLF<>sekrd2W+85o)98eq|IJE3s(<XfWo043}jng9R*

diff --git a/apple-touch-icon-76x76.png b/apple-touch-icon-76x76.png
index 373d042c21ce6dee11b4affe8534965fa2cf97fa..e70d190b16490631d0f7058bb8aade576d1dc886 100644
GIT binary patch
delta 76
zcmeBk>~ow@$;l$l%dY)&1zYXLrcilt6I~<Y5JO`t19K}AV{HQiD+2>#skr9J@8qSh
O$vL?{v!5)lkPiSZkra^t

delta 76
zcmeBk>~ow@$;m7xz$eVa)%Ry(Q>eVSv96I(h@qL4p^25DrM7{Am4N||*P+Fe-^oj1
OldBc4lAkQEkPiSFQWO^e

diff --git a/apple-touch-icon.png b/apple-touch-icon.png
index c6cea7a1bdf8c5a17d943b9a276cd012631e5519..7ea10b4483b60aaeda8bcd62eb46b94f4b50b94e 100644
GIT binary patch
delta 99
zcmca~neozP#tD_2EaJTE`j3ttO4-;nGsD9~*T^`;(Adhr+{(mU+rYrez~Fdj)dU6x
n2GtVRh?11Vl2ohQ{FKbJN(LhXBNJT%EE=|P9MYMboS6>*X-Xca

delta 99
zcmca~neozP#tD_2%wht35>s!4muzgBnc-oqYh)B+Xl7+-Vr68aZD3$!VDMOINdp4|
ngKCLuL`h0wNvc(DeoAIqC4-THk%_JW77dg9Wo#xVXXXO{E9o6~

diff --git a/articles/design-principles.html b/articles/design-principles.html
index 7aa18c67..0443af37 100644
--- a/articles/design-principles.html
+++ b/articles/design-principles.html
@@ -17,7 +17,7 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Design Principles for epidemics">
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-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
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-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
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@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
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-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
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     <span class="fab fa fab fa-github fa-lg"></span>
@@ -169,7 +168,7 @@ <h3 id="epidemic-modelling">Epidemic modelling<a class="anchor" aria-label="anch
 <h3 id="ode-systems-and-models">ODE systems and models<a class="anchor" aria-label="anchor" href="#ode-systems-and-models"></a>
 </h3>
 <ul>
-<li><p>A common method for defining and solving ODEs in R is to write the ODE system in R and pass it to solvers such as <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code> from the <a href="https://cran.r-project.org/package=deSolve" class="external-link"><em>deSolve</em> package</a>. We have opted against this approach (referred to as ‘R-deSolve’).</p></li>
+<li><p>A common method for defining and solving ODEs in R is to write the ODE system in R and pass it to solvers such as <code>deSolve::lsoda()</code> from the <a href="https://cran.r-project.org/package=deSolve" class="external-link"><em>deSolve</em> package</a>. We have opted against this approach (referred to as ‘R-deSolve’).</p></li>
 <li><p>It is possible to write ODE compartmental transitions in C++, and expose the C++ code to R, eventually passing this ODE system to deSolve solvers (referred to as ‘Rcpp-deSolve’). We have also opted against this approach, as it involves substantial interconversion of more complex objects such as structured lists (the model composable elements) from R to C++ in each solver timestep, reducing performance.</p></li>
 <li><p>ODE systems are written in C++, and solved using the <a href="https://www.boost.org/doc/libs/1_84_0/libs/numeric/odeint/doc/html/index.html" class="external-link">Boost <em>odeint</em> solvers</a> with <em>fixed step sizes</em>. This means that within each call to <code>model_*()</code>, R objects are converted for use by C++ only once (in the scalar arguments case), and are not passed back and forth multiple times.</p></li>
 <li><p><em>odeint</em> is provided by the package <a href="https://cran.r-project.org/package=BH" class="external-link">BH (Boost Headers)</a>, making it convenient to use in Rcpp packages. The <a href="https://cran.r-project.org/package=r2sundials" class="external-link"><em>r2sundials</em> package</a> provides an Rcpp-friendly interface to the <a href="https://computing.llnl.gov/projects/sundials" class="external-link">SUNDIALS ODE solvers</a>, but the documentation is less clear overall, and seems to recommend the use of <a href="https://cran.r-project.org/package=RcppArmadillo" class="external-link"><em>RcppArmadillo</em></a> and <a href="https://cran.r-project.org/package=RcppXPtrUtils" class="external-link"><em>RcppXPtrUtils</em></a>; these have not been evaluated for use.</p></li>
@@ -183,7 +182,39 @@ <h3 id="ode-systems-and-models">ODE systems and models<a class="anchor" aria-lab
 <div class="section level3">
 <h3 id="stochastic-models">Stochastic models<a class="anchor" aria-label="anchor" href="#stochastic-models"></a>
 </h3>
-<p><em>epidemics</em> only includes a single stochastic model adapted from earlier implementations, and hence common design decisions for stochastic models are likely to be worked out only as more models are added. The input and output types correspond to the ODE model types. This model is written in R <a href="https://github.com/epiverse-trace/epidemics/issues/179" class="external-link">although this may change in future</a>.</p>
+<p><em>epidemics</em> currently includes a single discrete-time stochastic model that implements a sub-compartment system taken from <span class="citation">@getz2018</span>, and initially adapted in <em>Epirecipes</em>.
+Some modelling decisions are explained here, while recognising that adding more models with different implementations could see them being revisited.</p>
+<ul>
+<li><p>Stochastic models currently target, and are expected to target, diseases for which outbreak sizes are initially small and thus where stochasticity matters more; the typical example is Ebola virus disease (simply, Ebola), and this is reflected in the model name.</p></li>
+<li><p>The Ebola model is also expected to be suitable for diseases with a high fatality risk that are detected when outbreak sizes are small, and with an isolation and treatment response comparable to Ebola, e.g. Marburg virus disease.</p></li>
+<li><p><strong>Note that</strong> very different alternative implementations of stochastic models exist.</p></li>
+<li><p>The current implementation was chosen due to the use of Erlang sub-compartments that were felt to better represent the long-tailed distributions of infection times seen in haemorrhagic fevers like Ebola.</p></li>
+<li><p>The model implements a two-level structure similar to the ODE models, with <code><a href="../reference/dot-model_ebola_internal.html">.model_ebola_internal()</a></code> the function implementing the simulation, while <code><a href="../reference/model_ebola.html">model_ebola()</a></code> is the user-facing wrapper with input checks and parameter and scenario combination handling.</p></li>
+<li><p>The model allows vectors for the infection parameters and the duration (called <code>time_end</code>); however the number of replicates for each parameter-scenario combination is not allowed to vary. A default of 100 was chosen as a reasonable middle ground between efficiency and realism.</p></li>
+<li>
+<p>The model allows lists of intervention sets and time-dependence functions to be passed.</p>
+<ul>
+<li><p>Only interventions on model parameters are allowed, and interventions on social contacts are not allowed, as the model does not include age-stratification in transmission (or otherwise).</p></li>
+<li><p>The parameters <code>infectiousness_rate</code> (often denoted <span class="math inline">\(\sigma\)</span>) and <code>removal_rate</code> (recovery or death with safe burial, <span class="math inline">\(\gamma\)</span>) <em>cannot</em> be targeted by rate interventions or time-dependence as these values determine the number of sub-compartments in the exposed and infectious (and hospitalised) compartments, respectively. These are fixed at the start of the simulation, and changing them partway is challenging to support as it would involve redistributing individuals currently in any sub-compartment into more or fewer sub-compartments.</p></li>
+</ul>
+</li>
+<li>
+<p>The model supports and defaults to multiple replicates or runs for each parameter-scenario combination.</p>
+<ul>
+<li><p>For any <span class="math inline">\(N\)</span> runs with a single parameter set and a single intervention set, runs will differ due to stochasticity (essentially, as different random numbers are drawn for each run).</p></li>
+<li><p>For any <span class="math inline">\(N\)</span> runs with multiple parameter sets and a single intervention set, runs will differ due to stochasticity <em>within</em> parameter sets, but any differences between runs <em>across</em> parameter sets (e.g. two different transmission rates) will be due to differences in parameter values alone.</p></li>
+<li><p>For multiple runs of multiple parameter-scenario combinations, differences among runs will be due to differences in parameters and composable elements (such as interventions) alone.</p></li>
+<li><p>The <a href="https://CRAN.R-project.org/package=withr" class="external-link"><em>withr</em> package</a> is used to ensure that seeds are preserved across parameter sets and interventions.</p></li>
+</ul>
+</li>
+<li><p>The input and output types correspond to the ODE model types.</p></li>
+<li>
+<p>The model is written in R <a href="https://github.com/epiverse-trace/epidemics/issues/179" class="external-link">although this may change in future</a>. The main reason for keeping the implementation in R is that the <code><a href="https://rdrr.io/r/stats/Multinom.html" class="external-link">stats::rmultinom()</a></code> function is a very efficient way of drawing from a categorical distribution (often called a discrete distribution) with heterogeneous probabilities. This <a href="https://stackoverflow.com/questions/23097269/efficient-multinomial-sampling-when-sample-size-and-probability-vary" class="external-link">StackOverflow question from 2014</a> has more details including benchmarks against other implementations using <em>Rcpp</em>; though old, we have benchmarked a minimal example using <em>Boost</em> and found that this information is still valid.</p>
+<ul>
+<li>One possible reason to switch at least part of the Ebola model implementation to C++ is to make use of more efficient random number generation from the GNU Scientific Library via <a href="https://CRAN.R-project.org/package=RcppGSL" class="external-link"><em>RcppGSL</em></a>, although there may be <a href="https://stackoverflow.com/questions/55976547/linking-gsl-libraries-to-rcppgsl-in-windows-10" class="external-link">issues for users trying to compile from source on Windows</a>.</li>
+</ul>
+</li>
+</ul>
 </div>
 <div class="section level3">
 <h3 id="classes">Classes<a class="anchor" aria-label="anchor" href="#classes"></a>
@@ -242,6 +273,8 @@ <h2 id="dependencies">Dependencies<a class="anchor" aria-label="anchor" href="#d
 <li>
 <a href="https://CRAN.R-project.org/package=BH" class="external-link"><em>BH</em></a>: provides the Boost <em>odeint</em> ODE solvers;</li>
 <li>
+<a href="https://CRAN.R-project.org/package=withr" class="external-link"><em>withr</em></a>: for seed management;</li>
+<li>
 <em>stats</em> and <em>utils</em>: already installed with R, and used only in the Ebola model, and hence liable to be removed in the future.</li>
 </ul>
 <p>A wider range of packages are taken on as soft dependencies to make the vignettes more user-friendly.</p>
@@ -263,9 +296,7 @@ <h2 id="dependencies">Dependencies<a class="anchor" aria-label="anchor" href="#d
 <li>
 <a href="https://CRAN.R-project.org/package=spelling" class="external-link"><em>spelling</em></a>: for spell-checking;</li>
 <li>
-<a href="https://CRAN.R-project.org/package=testthat" class="external-link"><em>testthat</em></a> (&gt;= 3.0.0): for unit tests;</li>
-<li>
-<a href="https://CRAN.R-project.org/package=withr" class="external-link"><em>withr</em></a>: for seed management.</li>
+<a href="https://CRAN.R-project.org/package=testthat" class="external-link"><em>testthat</em></a> (&gt;= 3.0.0): for unit tests.</li>
 </ul>
 </div>
 <div class="section level2">
@@ -281,13 +312,11 @@ <h2 id="contribute">Contribute<a class="anchor" aria-label="anchor" href="#contr
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/articles/epidemics.html b/articles/epidemics.html
index 6ea2173f..674248ac 100644
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-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
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-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
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     <span class="fab fa fab fa-github fa-lg"></span>
@@ -117,7 +116,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
     
     
 <p>This initial vignette shows to get started with using the <em>epidemics</em> package.</p>
-<p>Further vignettes include guidance on <a href="modelling_vaccination.html">“Modelling the implementation of vaccination regimes”</a>, as well as on<a href="modelling_interventions.html">“Modelling non-pharmaceutical interventions (NPIs) to reduce social contacts”</a> and <a href="multiple_interventions.html">“Modelling multiple overlapping NPIs”</a>.</p>
+<p>Further vignettes include guidance on <a href="modelling_vaccination.html">“Modelling the implementation of vaccination regimes”</a>, as well as on<a href="modelling_interventions.html">“Modelling non-pharmaceutical interventions (NPIs) to reduce social contacts”</a> and <a href="modelling_multiple_interventions.html">“Modelling multiple overlapping NPIs”</a>.</p>
 <p>There is also guidance available on specific models in the model library, such as the <a href="model_vacamole.html">Vacamole model developed by RIVM, the Dutch Institute for Public Health</a>.</p>
 <details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/epiverse-trace/epidemics" class="external-link">epidemics</a></span><span class="op">)</span></span>
@@ -135,6 +134,15 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <h2 id="prepare-population-and-initial-conditions">Prepare population and initial conditions<a class="anchor" aria-label="anchor" href="#prepare-population-and-initial-conditions"></a>
 </h2>
 <p>Prepare population and contact data.</p>
+<div class="section level3 unnumbered alert alert-info">
+<h3 id="note-on-social-contacts-data">Note on social contacts data<a class="anchor" aria-label="anchor" href="#note-on-social-contacts-data"></a>
+</h3>
+<p><strong>Note that</strong> the social contacts matrices provided by the <em>socialmixr</em>[<a href="https://CRAN.R-project.org/package=socialmixr" class="external-link uri">https://CRAN.R-project.org/package=socialmixr</a>] package follow a format wherein the matrix <span class="math inline">\(M_{ij}\)</span> represents <a href="https://epiforecasts.io/socialmixr/articles/socialmixr.html#usage" class="external-link">contacts from group <span class="math inline">\(i\)</span> to group <span class="math inline">\(j\)</span></a>.</p>
+<p>However, epidemic models traditionally adopt the notation that <span class="math inline">\(M_{ij}\)</span> defines contacts to <span class="math inline">\(i\)</span> from <span class="math inline">\(j\)</span> <span class="citation">(<a href="#ref-wallinga2006">Wallinga, Teunis, and Kretzschmar 2006</a>)</span>.</p>
+<p><span class="math inline">\(q M_{ij} / n_i\)</span> then defines the probability of infection, where <span class="math inline">\(q\)</span> is a scaling factor dependent on <span class="math inline">\(R_0\)</span> (or another measure of infection transmissibility), and <span class="math inline">\(n_i\)</span> is the population proportion of group <span class="math inline">\(i\)</span>.
+The ODEs in <em>epidemics</em> also follow this convention.</p>
+<p>For consistency with this notation, social contact matrices from <em>socialmixr</em> need to be transposed (using <code><a href="https://rdrr.io/r/base/t.html" class="external-link">t()</a></code>) before they are used with <em>epidemics</em>.</p>
+</div>
 <details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># load contact and population data from socialmixr::polymod</span></span>
 <span><span class="va">polymod</span> <span class="op">&lt;-</span> <span class="fu">socialmixr</span><span class="fu">::</span><span class="va"><a href="https://epiforecasts.io/socialmixr/reference/polymod.html" class="external-link">polymod</a></span></span>
@@ -144,7 +152,6 @@ <h2 id="prepare-population-and-initial-conditions">Prepare population and initia
 <span>  age.limits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">20</span>, <span class="fl">40</span><span class="op">)</span>,</span>
 <span>  symmetric <span class="op">=</span> <span class="cn">TRUE</span></span>
 <span><span class="op">)</span></span>
-<span><span class="co">#&gt; Using POLYMOD social contact data. To cite this in a publication, use the 'get_citation()' function</span></span>
 <span><span class="co">#&gt; Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option</span></span>
 <span></span>
 <span><span class="co"># prepare contact matrix</span></span>
@@ -267,6 +274,15 @@ <h2 id="prepare-data-and-visualise-infections">Prepare data and visualise infect
 <span>    y <span class="op">=</span> <span class="st">"Individuals"</span></span>
 <span>  <span class="op">)</span></span></code></pre></div>
 </details><p><img src="epidemics_files/figure-html/unnamed-chunk-6-1.png"><!-- --></p>
+</div>
+<div class="section level2 unnumbered">
+<h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a>
+</h2>
+<div id="refs" class="references csl-bib-body hanging-indent" entry-spacing="0">
+<div id="ref-wallinga2006" class="csl-entry">
+Wallinga, Jacco, Peter Teunis, and Mirjam Kretzschmar. 2006. <span>“Using Data on Social Contacts to Estimate Age-Specific Transmission Parameters for Respiratory-Spread Infectious Agents.”</span> <em>American Journal of Epidemiology</em> 164 (10): 936–44. <a href="https://doi.org/10.1093/aje/kwj317" class="external-link">https://doi.org/10.1093/aje/kwj317</a>.
+</div>
+</div>
 </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
     </nav></aside>
@@ -275,13 +291,11 @@ <h2 id="prepare-data-and-visualise-infections">Prepare data and visualise infect
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
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 </div>
 
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-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
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diff --git a/articles/finalsize_comparison.html b/articles/finalsize_comparison.html
index 71ff33f1..66d9fa09 100644
--- a/articles/finalsize_comparison.html
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@@ -17,7 +17,7 @@
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 <!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -35,12 +35,12 @@
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-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
 <li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
@@ -368,13 +367,11 @@ <h3 id="implementing-vaccination-in-finalsize">Implementing vaccination in <em>f
 <code class="sourceCode R"><span><span class="co"># note that epidemic_size() returns the absolute values</span></span>
 <span><span class="co"># epidemic size after 10% of the epidemic model run</span></span>
 <span><span class="fu"><a href="../reference/epidemic_size.html">epidemic_size</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">output</span>, stage <span class="op">=</span> <span class="fl">0.1</span><span class="op">)</span></span>
-<span><span class="co">#&gt;   [0,20)  [20,40)      40+ </span></span>
-<span><span class="co">#&gt; 574.4348 488.3563 585.5760</span></span>
+<span><span class="co">#&gt; [1] 574.4348 488.3563 585.5760</span></span>
 <span></span>
 <span><span class="co"># epidemic size at 50%</span></span>
 <span><span class="fu"><a href="../reference/epidemic_size.html">epidemic_size</a></span><span class="op">(</span>data <span class="op">=</span> <span class="va">output</span>, stage <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span></span>
-<span><span class="co">#&gt;  [0,20) [20,40)     40+ </span></span>
-<span><span class="co">#&gt; 5565772 4890178 5254726</span></span></code></pre></div>
+<span><span class="co">#&gt; [1] 5565772 4890178 5254726</span></span></code></pre></div>
 </details>
 </div>
 </div>
@@ -414,8 +411,8 @@ <h2 id="consideration-of-computational-speed">Consideration of computational spe
 <span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2 × 2</span></span></span>
 <span><span class="co">#&gt;   expression        total_time</span></span>
 <span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;bch:expr&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> analytical_method      0.456</span></span>
-<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> ode_model             10.1</span></span></code></pre></div>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> analytical_method      0.467</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> ode_model             10.9</span></span></code></pre></div>
 </details><p><strong>Note</strong> that some model runs using <em>epidemics</em> that implement more complex compartmental structure, or multiple interventions and vaccination regimes are likely to be slower than the example shown here.</p>
 <p>However, users should choose <em>finalsize</em> only when the assumptions underlying a final size calculation are met.
 For example, in cases where vaccinations are concurrent with a large number of infections, or when interventions are applied to reduce transmission, the final size assumptions are not met.
@@ -437,13 +434,11 @@ <h2 id="references">References<a class="anchor" aria-label="anchor" href="#refer
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/articles/index.html b/articles/index.html
index ffd7f69c..a2e5c230 100644
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+++ b/articles/index.html
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 <!DOCTYPE html>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Articles • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Articles"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -82,7 +81,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="section ">
       <h3>Modelling interventions</h3>
-      <p class="section-desc"></p>
+      <div class="section-desc"></div>
 
       <dl><dt><a href="modelling_interventions.html">Getting started with modelling interventions targeting social contacts</a></dt>
         <dd>
@@ -93,21 +92,21 @@ <h3>Modelling interventions</h3>
       </dd></dl></div>
     <div class="section ">
       <h3>Modelling vaccination</h3>
-      <p class="section-desc"></p>
+      <div class="section-desc"></div>
 
       <dl><dt><a href="modelling_vaccination.html">Modelling the effect of a vaccination campaign</a></dt>
         <dd>
       </dd></dl></div>
     <div class="section ">
       <h3>Modelling seasonality</h3>
-      <p class="section-desc"></p>
+      <div class="section-desc"></div>
 
       <dl><dt><a href="modelling_time_dependence.html">Modelling time-dependence and seasonality in transmission dynamics</a></dt>
         <dd>
       </dd></dl></div>
     <div class="section ">
       <h3>Other modelling vignettes</h3>
-      <p class="section-desc"></p>
+      <div class="section-desc"></div>
 
       <dl><dt><a href="modelling_scenarios.html">Modelling parameter uncertainty and epidemic scenarios</a></dt>
         <dd>
@@ -116,7 +115,7 @@ <h3>Other modelling vignettes</h3>
       </dd></dl></div>
     <div class="section ">
       <h3>Guides to library models</h3>
-      <p class="section-desc"></p>
+      <div class="section-desc"></div>
 
       <dl><dt><a href="model_vacamole.html">Modelling leaky vaccination and hospitalisation outcomes with Vacamole</a></dt>
         <dd>
@@ -127,7 +126,7 @@ <h3>Guides to library models</h3>
       </dd></dl></div>
     <div class="section ">
       <h3>Package design</h3>
-      <p class="section-desc"></p>
+      <div class="section-desc"></div>
 
       <dl><dt><a href="design-principles.html">Design Principles for epidemics</a></dt>
         <dd>
@@ -137,11 +136,11 @@ <h3>Package design</h3>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/articles/model_diphtheria.html b/articles/model_diphtheria.html
index 5a0e640c..1ea9079f 100644
--- a/articles/model_diphtheria.html
+++ b/articles/model_diphtheria.html
@@ -17,7 +17,7 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Modelling a diphtheria outbreak in a humanitarian camp setting">
+<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Modelling a diphtheria outbreak in a humanitarian camp setting">
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@@ -35,12 +35,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
 <li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
@@ -320,13 +319,11 @@ <h2 id="references">References<a class="anchor" aria-label="anchor" href="#refer
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer>
diff --git a/articles/model_ebola.html b/articles/model_ebola.html
index 22e549ea..7213a938 100644
--- a/articles/model_ebola.html
+++ b/articles/model_ebola.html
@@ -17,7 +17,7 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
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@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
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@@ -123,12 +122,14 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 This is often the case with outbreaks of infections such as Ebola virus disease (EVD, or simply, ebola).</p>
 <p><em>epidemics</em> includes a discrete time, stochastic compartmental model of ebola based on a consensus model presented in <span class="citation">Li et al. (<a href="#ref-li2019">2019</a>)</span>, with six compartments — susceptible, exposed, infectious, hospitalised, funeral, and removed.
 The transitions between compartments are based on an Erlang model developed by <span class="citation">Getz and Dougherty (<a href="#ref-getz2018">2018</a>)</span> for the 2014 West African EVD outbreak, with the code adapted from <a href="http://epirecip.es/epicookbook/chapters/erlang/r" class="external-link">Epirecipes</a>.</p>
-<p>The model does not include demographic variation in contacts, as ebola spreads primarily among contacts caring for infected individuals, making age or demographic structure less important.</p>
-<p>This model can currently accommodate interventions on model rates only (as there are no demographic groups for contacts interventions).</p>
+<p>The model allows easily running multiple replicates, accepts infection parameter vectors to help model parameter uncertainty, and can accept lists of intervention sets to model response scenarios.</p>
 <details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># some initial setup to load necessary packages</span></span>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/epiverse-trace/epidemics" class="external-link">epidemics</a></span><span class="op">)</span></span>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://purrr.tidyverse.org/" class="external-link">purrr</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidyr.tidyverse.org" class="external-link">tidyr</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://withr.r-lib.org" class="external-link">withr</a></span><span class="op">)</span></span>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></code></pre></div>
 </details><div class="section level2">
 <h2 id="prepare-population-and-initial-conditions">Prepare population and initial conditions<a class="anchor" aria-label="anchor" href="#prepare-population-and-initial-conditions"></a>
@@ -189,231 +190,159 @@ <h2 id="prepare-model-parameters">Prepare model parameters<a class="anchor" aria
 <div class="section level2">
 <h2 id="run-epidemic-model">Run epidemic model<a class="anchor" aria-label="anchor" href="#run-epidemic-model"></a>
 </h2>
-<p>We run the model using the function <code><a href="../reference/model_ebola.html">model_ebola()</a></code>.
-While there is a C++ equivalent of this model, it was not found to be much faster than the R-only version, and is not made available to users.</p>
-<p>The model is run for 100 days, with data reported on each day.
+<p>We run the model using the function <code><a href="../reference/model_ebola.html">model_ebola()</a></code>.</p>
+<p>The model is run for 100 days (the default), with data reported on each day.
 This is an appropriate period over which to obtain initial predictions for the outbreak, and after which response efforts such as non-pharmaceutical interventions and vaccination campaigns are likely to be launched to bring the outbreak under control.</p>
+<p>The function automatically runs 100 replicates (stochastic realisations) as a default, and this can be changed using the <code>replicates</code> argument.</p>
 <details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set seed to get consistent results</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span></span>
+<code class="sourceCode R"><span><span class="co"># run with a pre-set seed for consisten results</span></span>
 <span><span class="co"># run the epidemic model using `epidemic`</span></span>
 <span><span class="co"># we call the model "ebola" from the library</span></span>
-<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
+<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu">withr</span><span class="fu">::</span><span class="fu"><a href="https://withr.r-lib.org/reference/with_seed.html" class="external-link">with_seed</a></span><span class="op">(</span></span>
+<span>  <span class="fl">1</span>,</span>
+<span>  <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
+<span>    population <span class="op">=</span> <span class="va">guinea_population</span></span>
+<span>  <span class="op">)</span></span>
 <span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># view the head of the output</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span>
-<span><span class="co">#&gt;   time demography_group  compartment    value</span></span>
-<span><span class="co">#&gt; 1    1     demo_group_1  susceptible 13999989</span></span>
-<span><span class="co">#&gt; 2    1     demo_group_1      exposed       10</span></span>
-<span><span class="co">#&gt; 3    1     demo_group_1   infectious        1</span></span>
-<span><span class="co">#&gt; 4    1     demo_group_1 hospitalised        0</span></span>
-<span><span class="co">#&gt; 5    1     demo_group_1      funeral        0</span></span>
-<span><span class="co">#&gt; 6    1     demo_group_1      removed        0</span></span></code></pre></div>
+<span><span class="co">#&gt;     time demography_group  compartment    value replicate</span></span>
+<span><span class="co">#&gt;    &lt;int&gt;           &lt;char&gt;       &lt;char&gt;    &lt;num&gt;     &lt;int&gt;</span></span>
+<span><span class="co">#&gt; 1:     0     demo_group_1  susceptible 13999989         1</span></span>
+<span><span class="co">#&gt; 2:     0     demo_group_1      exposed       10         1</span></span>
+<span><span class="co">#&gt; 3:     0     demo_group_1   infectious        1         1</span></span>
+<span><span class="co">#&gt; 4:     0     demo_group_1 hospitalised        0         1</span></span>
+<span><span class="co">#&gt; 5:     0     demo_group_1      funeral        0         1</span></span>
+<span><span class="co">#&gt; 6:     0     demo_group_1      removed        0         1</span></span></code></pre></div>
 </details>
 </div>
 <div class="section level2">
 <h2 id="prepare-data-and-visualise-infections">Prepare data and visualise infections<a class="anchor" aria-label="anchor" href="#prepare-data-and-visualise-infections"></a>
 </h2>
-<p>We plot the ebola epidemic over time, showing the number of individuals exposed and infectious.</p>
+<p>We plot the size of the ebola epidemic over time; the epidemic size is taken to be the number of individuals considered ‘removed’.</p>
 <details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># plot figure of epidemic curve</span></span>
-<span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data</span>, <span class="va">compartment</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"exposed"</span>, <span class="st">"infectious"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"removed"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span></span>
 <span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span></span>
-<span>      x <span class="op">=</span> <span class="va">time</span>,</span>
-<span>      y <span class="op">=</span> <span class="va">value</span>,</span>
-<span>      colour <span class="op">=</span> <span class="va">compartment</span></span>
+<span>      x <span class="op">=</span> <span class="va">time</span>, y <span class="op">=</span> <span class="va">value</span></span>
 <span>    <span class="op">)</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_continuous.html" class="external-link">scale_y_continuous</a></span><span class="op">(</span></span>
-<span>    labels <span class="op">=</span> <span class="fu">scales</span><span class="fu">::</span><span class="va"><a href="https://scales.r-lib.org/reference/comma.html" class="external-link">comma</a></span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer</a></span><span class="op">(</span></span>
-<span>    palette <span class="op">=</span> <span class="st">"Dark2"</span>,</span>
-<span>    name <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Exposed"</span>, <span class="st">"Infectious"</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/expand_limits.html" class="external-link">expand_limits</a></span><span class="op">(</span></span>
-<span>    x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">101</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span></span>
-<span>    legend.position <span class="op">=</span> <span class="st">"top"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span></span>
-<span>    x <span class="op">=</span> <span class="st">"Simulation time (days)"</span>,</span>
-<span>    linetype <span class="op">=</span> <span class="st">"Compartment"</span>,</span>
-<span>    y <span class="op">=</span> <span class="st">"Individuals"</span></span>
-<span>  <span class="op">)</span></span></code></pre></div>
-</details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-5"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-5-1.png" alt="Model results from a single run showing the number of individuals in the exposed and infectious compartments over 100 days of the outbreak. The model assumes that 1 initially infectious person has exposed 10 others."><p class="caption">
-Figure 1: Model results from a single run showing the number of individuals in the exposed and infectious compartments over 100 days of the outbreak. The model assumes that 1 initially infectious person has exposed 10 others.
-</p>
-</div>
-</div>
-<div class="section level2">
-<h2 id="consensus-estimates-from-multiple-model-iterations">Consensus estimates from multiple model iterations<a class="anchor" aria-label="anchor" href="#consensus-estimates-from-multiple-model-iterations"></a>
-</h2>
-<p>Since the ebola model is a stochastic one, model results will vary in each run.
-We can run the model multiple times — here, 100 times — and plot the number of infectious people, to get a consensus idea of what an ebola outbreak might look like.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set seed for consistent output</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">1</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># run the simulation 100 times</span></span>
-<span><span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span></span>
-<span>  X <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">100</span><span class="op">)</span>,</span>
-<span>  FUN <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="op">{</span></span>
-<span>    <span class="va">data</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>      population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>      time_end <span class="op">=</span> <span class="fl">100</span></span>
-<span>    <span class="op">)</span></span>
-<span></span>
-<span>    <span class="co"># add replicate number and return data</span></span>
-<span>    <span class="va">data</span><span class="op">$</span><span class="va">replicate</span> <span class="op">&lt;-</span> <span class="va">x</span></span>
-<span>    <span class="va">data</span></span>
-<span>  <span class="op">}</span></span>
-<span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># use data.table to collect the data</span></span>
-<span><span class="va">data_timeseries</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
-</details><p>We plot the data.</p>
-<details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data_timeseries</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"infectious"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, group <span class="op">=</span> <span class="va">replicate</span><span class="op">)</span>,</span>
-<span>    alpha <span class="op">=</span> <span class="fl">0.3</span>, colour <span class="op">=</span> <span class="st">"grey50"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>group <span class="op">=</span> <span class="va">replicate</span><span class="op">)</span>, linewidth <span class="op">=</span> <span class="fl">0.2</span>, colour <span class="op">=</span> <span class="st">"grey"</span><span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span><span class="op">)</span>,</span>
-<span>    geom <span class="op">=</span> <span class="st">"ribbon"</span>,</span>
-<span>    fill <span class="op">=</span> <span class="st">"red"</span>, alpha <span class="op">=</span> <span class="fl">0.5</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span><span class="op">)</span>,</span>
-<span>    geom <span class="op">=</span> <span class="st">"line"</span></span>
+<span>    fun.min <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.025</span><span class="op">)</span>,</span>
+<span>    fun.max <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.975</span><span class="op">)</span>,</span>
+<span>    geom <span class="op">=</span> <span class="st">"ribbon"</span>, fill <span class="op">=</span> <span class="st">"red"</span>, alpha <span class="op">=</span> <span class="fl">0.2</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span>geom <span class="op">=</span> <span class="st">"line"</span><span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_continuous.html" class="external-link">scale_y_continuous</a></span><span class="op">(</span></span>
 <span>    labels <span class="op">=</span> <span class="fu">scales</span><span class="fu">::</span><span class="va"><a href="https://scales.r-lib.org/reference/comma.html" class="external-link">comma</a></span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/expand_limits.html" class="external-link">expand_limits</a></span><span class="op">(</span></span>
-<span>    x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">101</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/coord_cartesian.html" class="external-link">coord_cartesian</a></span><span class="op">(</span></span>
-<span>    expand <span class="op">=</span> <span class="cn">FALSE</span></span>
+<span>    x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">101</span><span class="op">)</span>,</span>
+<span>    y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="op">-</span><span class="fl">10</span>, <span class="cn">NA</span><span class="op">)</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/coord_cartesian.html" class="external-link">coord_cartesian</a></span><span class="op">(</span>expand <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span></span>
 <span>    legend.position <span class="op">=</span> <span class="st">"top"</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span></span>
 <span>    x <span class="op">=</span> <span class="st">"Simulation time (days)"</span>,</span>
-<span>    y <span class="op">=</span> <span class="st">"Individuals infectious with ebola"</span></span>
+<span>    y <span class="op">=</span> <span class="st">"Outbreak size"</span></span>
 <span>  <span class="op">)</span></span></code></pre></div>
 </details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-7"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-7-1.png" alt="Model results from 100 runs showing the number of individuals in the infectious compartments over 100 days of each outbreak. All models assume that 1 initially infectious person has exposed 10 others. A simple summary using the mean (black line with standard error as shaded red regions), plotted over the individual model runs (grey) show that there can be wide variation in individual outbreak trajectories."><p class="caption">
-Figure 2: Model results from 100 runs showing the number of individuals in the infectious compartments over 100 days of each outbreak. All models assume that 1 initially infectious person has exposed 10 others. A simple summary using the mean (black line with standard error as shaded red regions), plotted over the individual model runs (grey) show that there can be wide variation in individual outbreak trajectories.
+<span style="display:block;" id="fig:fig-initial"></span>
+<img src="model_ebola_files/figure-html/fig-initial-1.png" alt="Model results from a single run showing the epidemic size over 100 days of the outbreak. The model assumes that 1 initially infectious person has exposed 10 others. Grey lines show 100 stochastic realisations or model replicates."><p class="caption">
+Figure 1: Model results from a single run showing the epidemic size over 100 days of the outbreak. The model assumes that 1 initially infectious person has exposed 10 others. Grey lines show 100 stochastic realisations or model replicates.
 </p>
 </div>
-<p>We observe that model stochasticity leads to wide variation in model outcomes, and not all simulation replicates lead to exponential growth of the outbreak within the first 100 days.
-However, in a number of replicates, the outbreak has only a low daily incidence within the simulation time, although these replicates might show exponential growth later.</p>
-<p>We can find the ‘final size’ of each replicate using the <code><a href="../reference/epidemic_size.html">epidemic_size()</a></code> function on the original simulation data.
-Note that the final size here refers to the final size after 365 days, which is the duration of our simulation.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<p>We observe that model stochasticity leads to wide variation in model outcomes within the first 100 days: some outbreaks may be much more severe than the mean outbreak.
+Note how in nearly all replicates, the epidemic size is increasing at near exponential rates.</p>
+<p>We can find the size of each replicate using the <code><a href="../reference/epidemic_size.html">epidemic_size()</a></code> function on the original simulation data.
+Note that the final size here refers to the final size after 100 days, which is the duration of our simulation.</p>
+<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># apply the function over each replicate</span></span>
-<span><span class="va">data_final_size</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span></span>
-<span>  X <span class="op">=</span> <span class="va">data</span>,</span>
-<span>  FUN <span class="op">=</span> <span class="va">epidemic_size</span>, include_deaths <span class="op">=</span> <span class="cn">FALSE</span>, by_group <span class="op">=</span> <span class="cn">FALSE</span></span>
-<span><span class="op">)</span></span>
-<span><span class="va">data_final_size</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/unlist.html" class="external-link">unlist</a></span><span class="op">(</span><span class="va">data_final_size</span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># plot a histogram of the replicates</span></span>
-<span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_histogram.html" class="external-link">geom_histogram</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">data_final_size</span><span class="op">)</span>,</span>
-<span>    fill <span class="op">=</span> <span class="st">"steelblue"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_continuous.html" class="external-link">scale_x_continuous</a></span><span class="op">(</span></span>
-<span>    labels <span class="op">=</span> <span class="fu">scales</span><span class="fu">::</span><span class="va"><a href="https://scales.r-lib.org/reference/comma.html" class="external-link">comma</a></span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/coord_cartesian.html" class="external-link">coord_cartesian</a></span><span class="op">(</span></span>
-<span>    expand <span class="op">=</span> <span class="cn">FALSE</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span></span>
-<span>    legend.position <span class="op">=</span> <span class="st">"top"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span></span>
-<span>    x <span class="op">=</span> <span class="st">"Epidemic size at 100 days"</span>,</span>
-<span>    y <span class="op">=</span> <span class="st">"Number of replicates"</span></span>
-<span>  <span class="op">)</span></span></code></pre></div>
-</details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-9"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-9-1.png" alt="Histogram of the final outbreak sizes of 100 ebola outbreaks. These are taken from the 100 model runs presented in the earlier figure, and show that most outbreaks may affect fewer than 500 individuals within their first 100 days."><p class="caption">
-Figure 3: Histogram of the final outbreak sizes of 100 ebola outbreaks. These are taken from the 100 model runs presented in the earlier figure, and show that most outbreaks may affect fewer than 500 individuals within their first 100 days.
-</p>
+<span><span class="va">data_final_size</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/nest.html" class="external-link">nest</a></span><span class="op">(</span><span class="va">data</span>, .by <span class="op">=</span> <span class="st">"replicate"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span></span>
+<span>    final_size <span class="op">=</span> <span class="fu"><a href="https://purrr.tidyverse.org/reference/map.html" class="external-link">map_dbl</a></span><span class="op">(</span><span class="va">data</span>, <span class="va">epidemic_size</span><span class="op">)</span></span>
+<span>  <span class="op">)</span></span>
+<span></span>
+<span><span class="co"># get range of final sizes</span></span>
+<span><span class="fu"><a href="https://rdrr.io/r/base/range.html" class="external-link">range</a></span><span class="op">(</span><span class="va">data_final_size</span><span class="op">$</span><span class="va">final_size</span><span class="op">)</span></span>
+<span><span class="co">#&gt; [1]  97 686</span></span></code></pre></div>
+</details><div class="alert alert-info">
+<p><strong>Looking to model parameter uncertainty?</strong> The <a href="modelling_scenarios.html">vignette on modelling parameter uncertainty</a> has helpful information that is also applicable to the Ebola model.</p>
 </div>
-<p>We see that while some replicates affect over 600 individuals within the first 100 days, most replicates have fewer than 500 cases, suggesting that responses to halt the spread of ebola could be quite effective in most real outbreaks.</p>
 </div>
 <div class="section level2">
 <h2 id="applying-interventions-that-reduce-transmission">Applying interventions that reduce transmission<a class="anchor" aria-label="anchor" href="#applying-interventions-that-reduce-transmission"></a>
 </h2>
-<p>An intervention that reduces transmission can be applied by passing a <code>&lt;rate_intervention&gt;</code> on the transmission rate parameter, <code>beta</code>.</p>
-<p>We begin with an initial simple example that models an intervention that begins 15 days into the outbreak, and reduces transmission by 20%.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
+<p>Interventions that affect model parameters (called rate interventions) can be simulated for an Ebola outbreak in the same way as for other models; creating and passing rate interventions is covered in the <a href="modelling_rate_interventions.html">vignette on modelling rate interventions.</a></p>
+<div class="alert alert-warning">
+<p><strong>Note that</strong> the model does not include demographic variation in contacts, as EVD spreads primarily among contacts caring for infected individuals, making age or demographic structure less important. Thus this model allows interventions on model rates only (as there are no demographic groups for contacts interventions).</p>
+</div>
+<p>Here, we compare the effect of an intervention that begins 15 days into the outbreak, and reduces transmission by 20%, against the counterfactual, baseline scenario of no specific outbreak response.
+We simulate 100 days as in the previous examples.</p>
+<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># create an intervention on the transmission rate</span></span>
 <span><span class="va">reduce_transmission</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/intervention.html">intervention</a></span><span class="op">(</span></span>
 <span>  type <span class="op">=</span> <span class="st">"rate"</span>,</span>
 <span>  time_begin <span class="op">=</span> <span class="fl">15</span>, time_end <span class="op">=</span> <span class="fl">100</span>, reduction <span class="op">=</span> <span class="fl">0.2</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-</details><p>We can pass the intervention to the model function’s <code>intervention</code> argument.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set a seed for comparison with the baseline model</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># run the epidemic model and save data as the baseline</span></span>
-<span><span class="va">data_baseline</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span><span class="co"># note that the intervention is passed within a list,</span></span>
-<span><span class="co"># where it is named for the rate it is targeting</span></span>
-<span><span class="va">data_intervention</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  intervention <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span><span class="co"># create a list of intervention scenarios</span></span>
+<span><span class="va">intervention_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>  baseline <span class="op">=</span> <span class="cn">NULL</span>,</span>
+<span>  response <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
 <span>    transmission_rate <span class="op">=</span> <span class="va">reduce_transmission</span></span>
-<span>  <span class="op">)</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
+<span>  <span class="op">)</span></span>
+<span><span class="op">)</span></span></code></pre></div>
+</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># run the epidemic model and save data as the baseline, using a fixed seed</span></span>
+<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu">withr</span><span class="fu">::</span><span class="fu"><a href="https://withr.r-lib.org/reference/with_seed.html" class="external-link">with_seed</a></span><span class="op">(</span></span>
+<span>  <span class="fl">1</span>,</span>
+<span>  <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
+<span>    population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
+<span>    intervention <span class="op">=</span> <span class="va">intervention_scenarios</span></span>
+<span>  <span class="op">)</span></span>
 <span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># assign scenario names</span></span>
-<span><span class="va">data_baseline</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"baseline"</span></span>
-<span><span class="va">data_intervention</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"intervention"</span></span>
+<span><span class="va">data_scenarios</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"baseline"</span>, <span class="st">"response"</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># bind the data together</span></span>
-<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data_baseline</span>, <span class="va">data_intervention</span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
+<span><span class="co"># unnest the data, preserving scenario identifiers</span></span>
+<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">data</span>, <span class="va">scenario</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/unnest.html" class="external-link">unnest</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
+</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"removed"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span></span>
 <span>    xintercept <span class="op">=</span> <span class="fl">15</span>,</span>
 <span>    linetype <span class="op">=</span> <span class="st">"dotted"</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
+<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>group <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interaction.html" class="external-link">interaction</a></span><span class="op">(</span><span class="va">scenario</span>, <span class="va">replicate</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>    linewidth <span class="op">=</span> <span class="fl">0.2</span>, alpha <span class="op">=</span> <span class="fl">0.5</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
+<span>    geom <span class="op">=</span> <span class="st">"ribbon"</span>,</span>
+<span>    fun.min <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.025</span><span class="op">)</span>,</span>
+<span>    fun.max <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.975</span><span class="op">)</span>,</span>
+<span>    alpha <span class="op">=</span> <span class="fl">0.3</span>, colour <span class="op">=</span> <span class="cn">NA</span>,</span>
+<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>fill <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
+<span>    geom <span class="op">=</span> <span class="st">"line"</span>, linewidth <span class="op">=</span> <span class="fl">1</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer</a></span><span class="op">(</span></span>
-<span>    palette <span class="op">=</span> <span class="st">"Set1"</span>,</span>
+<span>    palette <span class="op">=</span> <span class="st">"Dark2"</span>,</span>
+<span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
+<span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Intervention"</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_fill_brewer</a></span><span class="op">(</span></span>
+<span>    palette <span class="op">=</span> <span class="st">"Dark2"</span>,</span>
 <span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
 <span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Intervention"</span><span class="op">)</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
@@ -426,12 +355,12 @@ <h2 id="applying-interventions-that-reduce-transmission">Applying interventions
 <span>    y <span class="op">=</span> <span class="st">"Outbreak size"</span></span>
 <span>  <span class="op">)</span></span></code></pre></div>
 </details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-12"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-12-1.png" alt="Effect of implementing an intervention that reduces transmission by 30% during an ebola outbreak. The intervention begins on the 15th day (dotted vertical line), and is active for the remainder of the model duration. Applying this intervention leads to many fewer individuals infectious with ebola over the outbreak."><p class="caption">
-Figure 4: Effect of implementing an intervention that reduces transmission by 30% during an ebola outbreak. The intervention begins on the 15th day (dotted vertical line), and is active for the remainder of the model duration. Applying this intervention leads to many fewer individuals infectious with ebola over the outbreak.
+<span style="display:block;" id="fig:unnamed-chunk-8"></span>
+<img src="model_ebola_files/figure-html/unnamed-chunk-8-1.png" alt="Effect of implementing an intervention that reduces transmission by 20% during an ebola outbreak. The intervention begins on the 15th day (dotted vertical line), and is active for the remainder of the model duration. Applying this intervention leads to many fewer individuals infectious with ebola over the outbreak."><p class="caption">
+Figure 2: Effect of implementing an intervention that reduces transmission by 20% during an ebola outbreak. The intervention begins on the 15th day (dotted vertical line), and is active for the remainder of the model duration. Applying this intervention leads to many fewer individuals infectious with ebola over the outbreak.
 </p>
 </div>
-<p>We see that applying an intervention that reduces transmission can be effective in reducing the number of individuals infected over the outbreak.</p>
+<p>We see that applying an intervention that reduces transmission may be effective in reducing outbreak sizes.</p>
 </div>
 <div class="section level2">
 <h2 id="modelling-the-roll-out-of-vaccination">Modelling the roll-out of vaccination<a class="anchor" aria-label="anchor" href="#modelling-the-roll-out-of-vaccination"></a>
@@ -440,52 +369,72 @@ <h2 id="modelling-the-roll-out-of-vaccination">Modelling the roll-out of vaccina
 <p><code><a href="../reference/model_ebola.html">model_ebola()</a></code> does not accept a vaccination regime as a <code>&lt;vaccination&gt;</code> object, but we can still model the effect of vaccination as a gradual decrease in the transmission rate <span class="math inline">\(\beta\)</span> over time.</p>
 <p>This is done by using the <em>time dependence</em> functionality of <em>epidemics</em>.</p>
 <div class="alert alert-warning">
-<p><strong>New to implementing parameter time dependence in <em>epidemics</em>?</strong> It may help to read the <a href="time_dependence.html">vignette on time dependence functionality</a> first!</p>
+<p><strong>New to implementing parameter time dependence in <em>epidemics</em>?</strong> It may help to read the <a href="modelling_time_dependence.html">vignette on time dependence functionality</a> first!</p>
+<p><strong>Note that</strong> the time-dependence composable element cannot be passed as a set of scenarios.</p>
 </div>
 <p>We first define a function suitable for the <code>time_dependence</code> argument.
-This function assumes that the baseline transmission rate of ebola decreases over time, with a 5% reduction each day due to vaccination.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># we assume a maximum time of 100 days, and a 5% daily reduction</span></span>
+This function assumes that the baseline transmission rate of ebola decreases over time, with a 0.5% reduction each day due to vaccination.</p>
+<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># we assume a 0.5% daily reduction</span></span>
 <span><span class="co"># we assume that this vaccination begins on the 15th day</span></span>
 <span><span class="va">time_dep_vax</span> <span class="op">&lt;-</span> <span class="kw">function</span><span class="op">(</span></span>
-<span>    <span class="va">time</span>, <span class="va">x</span>, <span class="va">max_time</span> <span class="op">=</span> <span class="fl">100</span>, <span class="va">time_start</span> <span class="op">=</span> <span class="fl">15</span>,</span>
-<span>    <span class="va">reduction</span> <span class="op">=</span> <span class="fl">0.05</span><span class="op">)</span> <span class="op">{</span></span>
+<span>    <span class="va">time</span>, <span class="va">x</span>, <span class="va">time_start</span> <span class="op">=</span> <span class="fl">15</span>, <span class="va">reduction</span> <span class="op">=</span> <span class="fl">0.005</span><span class="op">)</span> <span class="op">{</span></span>
 <span>  <span class="kw">if</span> <span class="op">(</span><span class="va">time</span> <span class="op">&lt;</span> <span class="va">time_start</span><span class="op">)</span> <span class="op">{</span></span>
 <span>    <span class="va">x</span></span>
 <span>  <span class="op">}</span> <span class="kw">else</span> <span class="op">{</span></span>
-<span>    <span class="va">x</span> <span class="op">*</span> <span class="op">(</span><span class="op">(</span><span class="fl">1.0</span> <span class="op">-</span> <span class="va">reduction</span><span class="op">)</span><span class="op">^</span><span class="op">(</span><span class="va">time</span> <span class="op">/</span> <span class="va">max_time</span><span class="op">)</span><span class="op">)</span></span>
+<span>    <span class="va">x</span> <span class="op">*</span> <span class="op">(</span><span class="fl">1.0</span> <span class="op">-</span> <span class="va">reduction</span><span class="op">)</span><span class="op">^</span><span class="va">time</span></span>
 <span>  <span class="op">}</span></span>
 <span><span class="op">}</span></span></code></pre></div>
-</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set a seed for comparison with the baseline model</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span><span class="co"># note that the intervention is passed within a list,</span></span>
-<span><span class="co"># where it is named for the rate it is targeting</span></span>
-<span><span class="va">data_apply_vax</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  time_dependence <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
-<span>    transmission_rate <span class="op">=</span> <span class="va">time_dep_vax</span></span>
-<span>  <span class="op">)</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
+</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">data_baseline</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://withr.r-lib.org/reference/with_seed.html" class="external-link">with_seed</a></span><span class="op">(</span></span>
+<span>  <span class="fl">1</span>,</span>
+<span>  <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
+<span>    population <span class="op">=</span> <span class="va">guinea_population</span></span>
+<span>  <span class="op">)</span></span>
+<span><span class="op">)</span></span>
+<span><span class="va">data_vax_scenario</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://withr.r-lib.org/reference/with_seed.html" class="external-link">with_seed</a></span><span class="op">(</span></span>
+<span>  <span class="fl">1</span>,</span>
+<span>  <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
+<span>    population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
+<span>    time_dependence <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>      transmission_rate <span class="op">=</span> <span class="va">time_dep_vax</span></span>
+<span>    <span class="op">)</span></span>
+<span>  <span class="op">)</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># assign scenario name</span></span>
-<span><span class="va">data_apply_vax</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"apply_vaccination"</span></span>
+<span><span class="va">data_baseline</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"baseline"</span></span>
+<span><span class="va">data_vax_scenario</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"scenario"</span></span>
 <span></span>
 <span><span class="co"># bind the data together</span></span>
-<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data_baseline</span>, <span class="va">data_apply_vax</span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
+<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data_baseline</span>, <span class="va">data_vax_scenario</span><span class="op">)</span></span></code></pre></div>
+</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"removed"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span></span>
 <span>    xintercept <span class="op">=</span> <span class="fl">15</span>,</span>
 <span>    linetype <span class="op">=</span> <span class="st">"dotted"</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
+<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>group <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interaction.html" class="external-link">interaction</a></span><span class="op">(</span><span class="va">scenario</span>, <span class="va">replicate</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>    linewidth <span class="op">=</span> <span class="fl">0.2</span>, alpha <span class="op">=</span> <span class="fl">0.5</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
+<span>    geom <span class="op">=</span> <span class="st">"ribbon"</span>,</span>
+<span>    fun.min <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.025</span><span class="op">)</span>,</span>
+<span>    fun.max <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.975</span><span class="op">)</span>,</span>
+<span>    alpha <span class="op">=</span> <span class="fl">0.3</span>, colour <span class="op">=</span> <span class="cn">NA</span>,</span>
+<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>fill <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
+<span>    geom <span class="op">=</span> <span class="st">"line"</span>, linewidth <span class="op">=</span> <span class="fl">1</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer</a></span><span class="op">(</span></span>
-<span>    palette <span class="op">=</span> <span class="st">"Set1"</span>,</span>
+<span>    palette <span class="op">=</span> <span class="st">"Dark2"</span>,</span>
+<span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
+<span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Vaccination campaign"</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_fill_brewer</a></span><span class="op">(</span></span>
+<span>    palette <span class="op">=</span> <span class="st">"Dark2"</span>,</span>
 <span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
 <span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Vaccination campaign"</span><span class="op">)</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
@@ -498,9 +447,9 @@ <h2 id="modelling-the-roll-out-of-vaccination">Modelling the roll-out of vaccina
 <span>    y <span class="op">=</span> <span class="st">"Outbreak size"</span></span>
 <span>  <span class="op">)</span></span></code></pre></div>
 </details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-15"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-15-1.png" alt="Effect of implementing a vaccination regime that gradually reduces ebola transmission over time, using the time dependence functionality."><p class="caption">
-Figure 5: Effect of implementing a vaccination regime that gradually reduces ebola transmission over time, using the time dependence functionality.
+<span style="display:block;" id="fig:unnamed-chunk-11"></span>
+<img src="model_ebola_files/figure-html/unnamed-chunk-11-1.png" alt="Effect of implementing a vaccination regime that gradually reduces ebola transmission over time, using the time dependence functionality."><p class="caption">
+Figure 3: Effect of implementing a vaccination regime that gradually reduces ebola transmission over time, using the time dependence functionality.
 </p>
 </div>
 <p>Similar functionality can be used to model other parameters more flexibly than allowed by the <code>&lt;rate_intervention&gt;</code> class.</p>
@@ -515,221 +464,83 @@ <h2 id="modelling-a-multi-pronged-ebola-response">Modelling a multi-pronged ebol
 <li><p>safety of hospitals and the risk of community transmission, and</p></li>
 <li><p>safety of funeral practices to reduce the risk of transmission from dead bodies.</p></li>
 </ul>
-<p>Here, we show the effects of these interventions separately, before showing their combined effect.</p>
-<div class="section level3">
-<h3 id="improving-hospitalisation">Improving hospitalisation<a class="anchor" aria-label="anchor" href="#improving-hospitalisation"></a>
-</h3>
-<p>We first model an intervention that begins 15 days into the outbreak, and reduces the proportion of individuals who are infectious in the community by 30%, thus improving the proportion that are hospitalised.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
+<p>Here, we show the combined effects of these interventions separately.
+We can pass the interventions to the model function’s <code>intervention</code> argument as a named list, with the names indicating the model parameters to target.</p>
+<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># create an intervention on the transmission rate</span></span>
 <span><span class="va">improve_hospitalisation</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/intervention.html">intervention</a></span><span class="op">(</span></span>
 <span>  type <span class="op">=</span> <span class="st">"rate"</span>,</span>
 <span>  time_begin <span class="op">=</span> <span class="fl">15</span>, time_end <span class="op">=</span> <span class="fl">100</span>, reduction <span class="op">=</span> <span class="fl">0.3</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-</details><p>We can pass the interventions to the model function’s <code>intervention</code> argument as a named list, with the names indicating the model parameters to target.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set a seed for comparison with the baseline model</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span><span class="co"># note that the intervention is passed within a list,</span></span>
-<span><span class="co"># where it is named for the rate it is targeting</span></span>
-<span><span class="va">data_improve_hosp</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  intervention <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
-<span>    prop_community <span class="op">=</span> <span class="va">improve_hospitalisation</span></span>
-<span>  <span class="op">)</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># assign scenario name</span></span>
-<span><span class="va">data_improve_hosp</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"improve_hosp"</span></span>
-<span></span>
-<span><span class="co"># bind the data together</span></span>
-<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data_baseline</span>, <span class="va">data_improve_hosp</span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"removed"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span></span>
-<span>    xintercept <span class="op">=</span> <span class="fl">15</span>,</span>
-<span>    linetype <span class="op">=</span> <span class="st">"dotted"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer</a></span><span class="op">(</span></span>
-<span>    palette <span class="op">=</span> <span class="st">"Set1"</span>,</span>
-<span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
-<span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Improved hospitalisation"</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span></span>
-<span>    legend.position <span class="op">=</span> <span class="st">"top"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span></span>
-<span>    x <span class="op">=</span> <span class="st">"Days"</span>,</span>
-<span>    y <span class="op">=</span> <span class="st">"Outbreak size"</span></span>
-<span>  <span class="op">)</span></span></code></pre></div>
-</details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-18"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-18-1.png" alt="Effect of implementing an intervention that reduces the proportion of infectious cases in the community by transferring them to a hospitalisation setting."><p class="caption">
-Figure 6: Effect of implementing an intervention that reduces the proportion of infectious cases in the community by transferring them to a hospitalisation setting.
-</p>
-</div>
-</div>
-<div class="section level3">
-<h3 id="improve-etu-safety">Improve ETU safety<a class="anchor" aria-label="anchor" href="#improve-etu-safety"></a>
-</h3>
-<p>We next model an intervention to improve the safety of ETUs by reducing transmission risk by 70%, alongside the earlier improvement in hospitalisation.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># create an intervention on the transmission rate</span></span>
+<span><span class="co"># create an intervention on ETU risk</span></span>
 <span><span class="va">improve_etu_safety</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/intervention.html">intervention</a></span><span class="op">(</span></span>
 <span>  type <span class="op">=</span> <span class="st">"rate"</span>,</span>
 <span>  time_begin <span class="op">=</span> <span class="fl">15</span>, time_end <span class="op">=</span> <span class="fl">100</span>, reduction <span class="op">=</span> <span class="fl">0.7</span></span>
-<span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set a seed for comparison with the baseline model</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span><span class="co"># note that the intervention is passed within a list,</span></span>
-<span><span class="co"># where it is named for the rate it is targeting</span></span>
-<span><span class="va">data_improve_etu</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  intervention <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
-<span>    etu_risk <span class="op">=</span> <span class="va">improve_etu_safety</span></span>
-<span>  <span class="op">)</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># assign scenario name</span></span>
-<span><span class="va">data_improve_etu</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"improve_etu"</span></span>
-<span></span>
-<span><span class="co"># bind the data together</span></span>
-<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data_baseline</span>, <span class="va">data_improve_etu</span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"removed"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span></span>
-<span>    xintercept <span class="op">=</span> <span class="fl">15</span>,</span>
-<span>    linetype <span class="op">=</span> <span class="st">"dotted"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer</a></span><span class="op">(</span></span>
-<span>    palette <span class="op">=</span> <span class="st">"Set1"</span>,</span>
-<span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
-<span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Improve ETU safety"</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span></span>
-<span>    legend.position <span class="op">=</span> <span class="st">"top"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span></span>
-<span>    x <span class="op">=</span> <span class="st">"Days"</span>,</span>
-<span>    y <span class="op">=</span> <span class="st">"Outbreak size"</span></span>
-<span>  <span class="op">)</span></span></code></pre></div>
-</details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-21"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-21-1.png" alt="Effect of implementing an intervention that reduces the risk of ebola transmission in a hospitalisation context."><p class="caption">
-Figure 7: Effect of implementing an intervention that reduces the risk of ebola transmission in a hospitalisation context.
-</p>
-</div>
-<p>Note that the reason that this intervention has little to no effect is that it is only likely to be effective when the proportion of cases hospitalised is high.
-In this model, the large majority of cases remain in the community, and improving the safety of ETUs is not an effective intervention.</p>
-</div>
-<div class="section level3">
-<h3 id="improve-funeral-safety">Improve funeral safety<a class="anchor" aria-label="anchor" href="#improve-funeral-safety"></a>
-</h3>
-<p>We next model an intervention to improve the safety of funeral practices, by reducing transmission risk associated with funerals by 50%.</p>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># create an intervention on the transmission rate</span></span>
+<span><span class="co"># create an intervention on the transmission rate</span></span>
 <span><span class="va">reduce_funeral_risk</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/intervention.html">intervention</a></span><span class="op">(</span></span>
 <span>  type <span class="op">=</span> <span class="st">"rate"</span>,</span>
 <span>  time_begin <span class="op">=</span> <span class="fl">15</span>, time_end <span class="op">=</span> <span class="fl">100</span>, reduction <span class="op">=</span> <span class="fl">0.5</span></span>
 <span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set a seed for comparison with the baseline model</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span><span class="co"># note that the intervention is passed within a list,</span></span>
-<span><span class="co"># where it is named for the rate it is targeting</span></span>
-<span><span class="va">data_improve_funeral</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  intervention <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
-<span>    funeral_risk <span class="op">=</span> <span class="va">reduce_funeral_risk</span></span>
-<span>  <span class="op">)</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
-<span><span class="op">)</span></span>
-<span></span>
-<span><span class="co"># assign scenario name</span></span>
-<span><span class="va">data_improve_funeral</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"improve_funeral"</span></span>
-<span></span>
-<span><span class="co"># bind the data together</span></span>
-<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data_baseline</span>, <span class="va">data_improve_funeral</span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"removed"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span></span>
-<span>    xintercept <span class="op">=</span> <span class="fl">15</span>,</span>
-<span>    linetype <span class="op">=</span> <span class="st">"dotted"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer</a></span><span class="op">(</span></span>
-<span>    palette <span class="op">=</span> <span class="st">"Set1"</span>,</span>
-<span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
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-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_continuous.html" class="external-link">scale_y_sqrt</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggtheme.html" class="external-link">theme_bw</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span></span>
-<span>    legend.position <span class="op">=</span> <span class="st">"top"</span></span>
-<span>  <span class="op">)</span> <span class="op">+</span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span></span>
-<span>    x <span class="op">=</span> <span class="st">"Days"</span>,</span>
-<span>    y <span class="op">=</span> <span class="st">"Outbreak size"</span></span>
-<span>  <span class="op">)</span></span></code></pre></div>
-</details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-24"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-24-1.png" alt="Effect of implementing an intervention that reduces the risk of ebola transmission in a funeral context."><p class="caption">
-Figure 8: Effect of implementing an intervention that reduces the risk of ebola transmission in a funeral context.
-</p>
-</div>
-</div>
-<div class="section level3">
-<h3 id="combined-interventions">Combined interventions<a class="anchor" aria-label="anchor" href="#combined-interventions"></a>
-</h3>
-<details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
-<code class="sourceCode R"><span><span class="co"># set a seed for comparison with the baseline model</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">0</span><span class="op">)</span></span>
-<span><span class="co"># note that the intervention is passed within a list,</span></span>
-<span><span class="co"># where it is named for the rate it is targeting</span></span>
-<span><span class="va">data_combined_interventions</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
-<span>  population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
-<span>  intervention <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># create a list of single and combined interventions</span></span>
+<span><span class="va">intervention_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>  baseline <span class="op">=</span> <span class="cn">NULL</span>,</span>
+<span>  combined <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
 <span>    transmission_rate <span class="op">=</span> <span class="va">reduce_transmission</span>,</span>
 <span>    prop_community <span class="op">=</span> <span class="va">improve_hospitalisation</span>,</span>
 <span>    etu_risk <span class="op">=</span> <span class="va">improve_etu_safety</span>,</span>
 <span>    funeral_risk <span class="op">=</span> <span class="va">reduce_funeral_risk</span></span>
-<span>  <span class="op">)</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
+<span>  <span class="op">)</span></span>
+<span><span class="op">)</span></span></code></pre></div>
+</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># run the epidemic model and save data as the baseline, using a fixed seed</span></span>
+<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu">withr</span><span class="fu">::</span><span class="fu"><a href="https://withr.r-lib.org/reference/with_seed.html" class="external-link">with_seed</a></span><span class="op">(</span></span>
+<span>  <span class="fl">1</span>,</span>
+<span>  <span class="fu"><a href="../reference/model_ebola.html">model_ebola</a></span><span class="op">(</span></span>
+<span>    population <span class="op">=</span> <span class="va">guinea_population</span>,</span>
+<span>    intervention <span class="op">=</span> <span class="va">intervention_scenarios</span></span>
+<span>  <span class="op">)</span></span>
+<span><span class="op">)</span></span></code></pre></div>
+</details><details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># name the scenarios and unnest the data</span></span>
+<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span></span>
+<span>  <span class="va">data_scenarios</span>,</span>
+<span>  scenario <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">intervention_scenarios</span><span class="op">)</span></span>
 <span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># assign scenario name</span></span>
-<span><span class="va">data_combined_interventions</span><span class="op">$</span><span class="va">scenario</span> <span class="op">&lt;-</span> <span class="st">"combined_interventions"</span></span>
-<span></span>
-<span><span class="co"># bind the data together</span></span>
-<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows</a></span><span class="op">(</span><span class="va">data_baseline</span>, <span class="va">data_combined_interventions</span><span class="op">)</span></span></code></pre></div>
-</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
+<span><span class="va">data_scenarios</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">scenario</span>, <span class="va">data</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
+<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/unnest.html" class="external-link">unnest</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></code></pre></div>
+</details><details class="chunk-details"><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">data_scenarios</span>, <span class="va">compartment</span> <span class="op">==</span> <span class="st">"removed"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
-<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_abline.html" class="external-link">geom_vline</a></span><span class="op">(</span></span>
 <span>    xintercept <span class="op">=</span> <span class="fl">15</span>,</span>
 <span>    linetype <span class="op">=</span> <span class="st">"dotted"</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_path.html" class="external-link">geom_line</a></span><span class="op">(</span></span>
-<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span><span class="va">time</span>, <span class="va">value</span>, colour <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
+<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>group <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interaction.html" class="external-link">interaction</a></span><span class="op">(</span><span class="va">scenario</span>, <span class="va">replicate</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>    linewidth <span class="op">=</span> <span class="fl">0.2</span>, alpha <span class="op">=</span> <span class="fl">0.5</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
+<span>    geom <span class="op">=</span> <span class="st">"ribbon"</span>,</span>
+<span>    fun.min <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.025</span><span class="op">)</span>,</span>
+<span>    fun.max <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/stats/quantile.html" class="external-link">quantile</a></span><span class="op">(</span><span class="va">x</span>, <span class="fl">0.975</span><span class="op">)</span>,</span>
+<span>    alpha <span class="op">=</span> <span class="fl">0.3</span>, colour <span class="op">=</span> <span class="cn">NA</span>,</span>
+<span>    <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>fill <span class="op">=</span> <span class="va">scenario</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/stat_summary.html" class="external-link">stat_summary</a></span><span class="op">(</span></span>
+<span>    geom <span class="op">=</span> <span class="st">"line"</span>, linewidth <span class="op">=</span> <span class="fl">1</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
 <span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer</a></span><span class="op">(</span></span>
-<span>    palette <span class="op">=</span> <span class="st">"Set1"</span>,</span>
+<span>    palette <span class="op">=</span> <span class="st">"Dark2"</span>,</span>
+<span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
+<span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Combined interventions"</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_fill_brewer</a></span><span class="op">(</span></span>
+<span>    palette <span class="op">=</span> <span class="st">"Dark2"</span>,</span>
 <span>    name <span class="op">=</span> <span class="st">"Scenario"</span>,</span>
 <span>    labels <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Baseline"</span>, <span class="st">"Combined interventions"</span><span class="op">)</span></span>
 <span>  <span class="op">)</span> <span class="op">+</span></span>
@@ -742,18 +553,17 @@ <h3 id="combined-interventions">Combined interventions<a class="anchor" aria-lab
 <span>    y <span class="op">=</span> <span class="st">"Outbreak size"</span></span>
 <span>  <span class="op">)</span></span></code></pre></div>
 </details><div class="figure">
-<span style="display:block;" id="fig:unnamed-chunk-26"></span>
-<img src="model_ebola_files/figure-html/unnamed-chunk-26-1.png" alt="Effect of implementing multiple simultaneous interventions to reduce transmission during an ebola outbreak, all beginning on the 15th day (dotted vertical line), and remaining active for the remainder of the model duration. Applying these interventions substantially reduces the final size of the outbreak, with a potential plateau in the outbreak size reached at 100 days."><p class="caption">
-Figure 9: Effect of implementing multiple simultaneous interventions to reduce transmission during an ebola outbreak, all beginning on the 15th day (dotted vertical line), and remaining active for the remainder of the model duration. Applying these interventions substantially reduces the final size of the outbreak, with a potential plateau in the outbreak size reached at 100 days.
+<span style="display:block;" id="fig:unnamed-chunk-16"></span>
+<img src="model_ebola_files/figure-html/unnamed-chunk-16-1.png" alt="Effect of implementing multiple simultaneous interventions to reduce transmission during an ebola outbreak, all beginning on the 15th day (dotted vertical line), and remaining active for the remainder of the model duration. Applying these interventions substantially reduces the final size of the outbreak, with a potential plateau in the outbreak size reached at 100 days. Individual scenario replicates are shown in the background, while the shaded region shows the 95% interval, and the heavy central line shows the mean for each scenario."><p class="caption">
+Figure 4: Effect of implementing multiple simultaneous interventions to reduce transmission during an ebola outbreak, all beginning on the 15th day (dotted vertical line), and remaining active for the remainder of the model duration. Applying these interventions substantially reduces the final size of the outbreak, with a potential plateau in the outbreak size reached at 100 days. Individual scenario replicates are shown in the background, while the shaded region shows the 95% interval, and the heavy central line shows the mean for each scenario.
 </p>
 </div>
 </div>
-</div>
 <div class="section level2">
 <h2 id="details-discrete-time-ebola-virus-disease-model">Details: Discrete-time Ebola virus disease model<a class="anchor" aria-label="anchor" href="#details-discrete-time-ebola-virus-disease-model"></a>
 </h2>
-<p>This model has compartments adopted from the consensus model for Ebola virus disease presented in Li et al. (2019), and with transitions between epidemiological compartments modelled using Erlang sub-compartments adapted from Getz and Dougherty (2018); see <strong>References</strong>.</p>
-<p>The R code for this model is adapted from code by Ha Minh Lam and initially made available on <em>Epirecipes</em> (<a href="https://github.com/epirecipes/epicookbook" class="external-link uri">https://github.com/epirecipes/epicookbook</a>) under the MIT license.</p>
+<p>This model has compartments adopted from the consensus model for Ebola virus disease presented in <span class="citation">Li et al. (<a href="#ref-li2019">2019</a>)</span>, and with transitions between epidemiological compartments modelled using Erlang sub-compartments adapted from <span class="citation">Getz and Dougherty (<a href="#ref-getz2018">2018</a>)</span>; see <strong>References</strong>.</p>
+<p>The R code for this model is adapted from code by <a href="https://github.com/epirecipes/epicookbook" class="external-link">Ha Minh Lam and initially made available on <em>Epirecipes</em></a> under the MIT license.</p>
 <p>The transition rates between the exposed and infectious, and infectious and funeral compartments (and also hospitalised to removed), <span class="math inline">\(\gamma^E\)</span> and <span class="math inline">\(\gamma^I\)</span> in Getz and Dougherty’s notation, are passed by the user as the <code>infectiousness_rate</code> and <code>removal_rate</code> respectively.</p>
 <p>The shape of the Erlang distributions of passage times through the exposed and infectious compartments (<span class="math inline">\(k^E\)</span> and <span class="math inline">\(k^I\)</span>) are recommended to be set to 2 as a sensible choice, which is the default value for the <code>erlang_sbubcompartments</code> argument, but can be allowed to vary (but not independently).</p>
 <p>Getz and Dougherty’s equation (6) gives the relationship between these parameters and the mean pre-infectious <span class="math inline">\(\rho^E\)</span> and infectious <span class="math inline">\(\rho^I\)</span> periods.</p>
@@ -802,13 +612,11 @@ <h2 id="references">References<a class="anchor" aria-label="anchor" href="#refer
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer>
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diff --git a/articles/model_vacamole.html b/articles/model_vacamole.html
index 89e9929a..595bb1a0 100644
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+<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Modelling leaky vaccination and hospitalisation outcomes with Vacamole">
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@@ -121,7 +120,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 </div>
 <p>Vacamole is a deterministic, compartmental epidemic model built by Kylie Ainslie and others at <a href="https://www.rivm.nl/" class="external-link">RIVM, the Dutch Public Health Institute</a> for the Covid-19 pandemic, with a focus on scenario modelling for hospitalisation and vaccination <span class="citation">(<a href="#ref-ainslie2022">Ainslie et al. 2022</a>)</span>.</p>
 <p>Vacamole was implemented as an R package, and the <a href="https://github.com/kylieainslie/vacamole" class="external-link">source code can be found on GitHub</a>. Some versions have been used to generate scenarios for the ECDC Covid-19 Scenario Hub.</p>
-<p>The original model has 8 conceptual compartments - four epidemiological compartments: susceptible, exposed, infectious, and recovered (S, E, I, R respectively), three hospitalisation compartments: hospitalised, in intensive care, and returning from intensive care to regular hospital care (H, ICU, ICU2H), and death - see the <a href="doi.org/10.2807/1560-7917.ES.2022.27.44.2101090">manuscript describing them here</a>. Only infected individuals can enter the hospitalisation or death compartments.</p>
+<p>The original model has 8 conceptual compartments - four epidemiological compartments: susceptible, exposed, infectious, and recovered (S, E, I, R respectively), three hospitalisation compartments: hospitalised, in intensive care, and returning from intensive care to regular hospital care (H, ICU, ICU2H), and death. Only infected individuals can enter the hospitalisation or death compartments.</p>
 <p>Individuals from the susceptible compartment may be vaccinated partially (<span class="math inline">\(V_1\)</span>) or fully (<span class="math inline">\(V_2\)</span>; assuming a two dose regimen), with each dose reducing their probability of being infected, and of being hospitalised or dying.</p>
 <div class="section level2">
 <h2 id="modifications-for-epidemics">Modifications for <em>epidemics</em><a class="anchor" aria-label="anchor" href="#modifications-for-epidemics"></a>
@@ -452,13 +451,11 @@ <h2 id="references">References<a class="anchor" aria-label="anchor" href="#refer
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
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 </div>
 
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-  <p></p>
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diff --git a/articles/modelling_interventions.html b/articles/modelling_interventions.html
index b79cd7d8..0b86398c 100644
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@@ -17,7 +17,7 @@
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-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
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@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
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-</form>
-
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+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
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@@ -132,6 +131,13 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <h2 id="prepare-population-and-initial-conditions">Prepare population and initial conditions<a class="anchor" aria-label="anchor" href="#prepare-population-and-initial-conditions"></a>
 </h2>
 <p>Prepare population and contact data.</p>
+<div class="section level3 unnumbered alert alert-info">
+<h3 id="note-on-social-contacts-data">Note on social contacts data<a class="anchor" aria-label="anchor" href="#note-on-social-contacts-data"></a>
+</h3>
+<p><em>epidemics</em> expects social contacts matrices <span class="math inline">\(M_{ij}\)</span> to represent contacts to <span class="math inline">\(i\)</span> from <span class="math inline">\(j\)</span> <span class="citation">(<a href="#ref-wallinga2006">Wallinga, Teunis, and Kretzschmar 2006</a>)</span>, such that <span class="math inline">\(q M_{ij} / n_i\)</span> is the probability of infection, where <span class="math inline">\(q\)</span> is a scaling factor dependent on infection transmissibility, and <span class="math inline">\(n_i\)</span> is the population proportion of group <span class="math inline">\(i\)</span>.</p>
+<p>Social contacts matrices provided by the <em>socialmixr</em>[<a href="https://CRAN.R-project.org/package=socialmixr" class="external-link uri">https://CRAN.R-project.org/package=socialmixr</a>] package follow the opposite convention, where <span class="math inline">\(M_{ij}\)</span> represents <a href="https://epiforecasts.io/socialmixr/articles/socialmixr.html#usage" class="external-link">contacts from group <span class="math inline">\(i\)</span> to group <span class="math inline">\(j\)</span></a>.</p>
+<p>Thus social contact matrices from <em>socialmixr</em> need to be transposed (using <code><a href="https://rdrr.io/r/base/t.html" class="external-link">t()</a></code>) before they are used with <em>epidemics</em>.</p>
+</div>
 <details class="chunk-details" open><summary class="chunk-summary"><span class="chunk-summary-text">Code</span></summary><div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># load contact and population data from socialmixr::polymod</span></span>
 <span><span class="va">polymod</span> <span class="op">&lt;-</span> <span class="fu">socialmixr</span><span class="fu">::</span><span class="va"><a href="https://epiforecasts.io/socialmixr/reference/polymod.html" class="external-link">polymod</a></span></span>
@@ -141,7 +147,6 @@ <h2 id="prepare-population-and-initial-conditions">Prepare population and initia
 <span>  age.limits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">20</span>, <span class="fl">40</span><span class="op">)</span>,</span>
 <span>  symmetric <span class="op">=</span> <span class="cn">TRUE</span></span>
 <span><span class="op">)</span></span>
-<span><span class="co">#&gt; Using POLYMOD social contact data. To cite this in a publication, use the 'get_citation()' function</span></span>
 <span><span class="co">#&gt; Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option</span></span>
 <span></span>
 <span><span class="co"># prepare contact matrix</span></span>
@@ -277,6 +282,15 @@ <h2 id="prepare-data-and-visualise-infections">Prepare data and visualise infect
 <span>    y <span class="op">=</span> <span class="st">"Individuals"</span></span>
 <span>  <span class="op">)</span></span></code></pre></div>
 </details><p><img src="modelling_interventions_files/figure-html/unnamed-chunk-7-1.png"><!-- --></p>
+</div>
+<div class="section level2 unnumbered">
+<h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a>
+</h2>
+<div id="refs" class="references csl-bib-body hanging-indent" entry-spacing="0">
+<div id="ref-wallinga2006" class="csl-entry">
+Wallinga, Jacco, Peter Teunis, and Mirjam Kretzschmar. 2006. <span>“Using Data on Social Contacts to Estimate Age-Specific Transmission Parameters for Respiratory-Spread Infectious Agents.”</span> <em>American Journal of Epidemiology</em> 164 (10): 936–44. <a href="https://doi.org/10.1093/aje/kwj317" class="external-link">https://doi.org/10.1093/aje/kwj317</a>.
+</div>
+</div>
 </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
     </nav></aside>
@@ -285,13 +299,11 @@ <h2 id="prepare-data-and-visualise-infections">Prepare data and visualise infect
 
 
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index dbd8844c..9ca5fffd 100644
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 </div>
 
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-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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index c24f244b..0a1a469e 100644
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-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
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-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
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+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
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     <footer><div class="pkgdown-footer-left">
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 </div>
 
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index 1b017b1f..d434aa12 100644
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-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
 <li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
@@ -837,13 +836,11 @@ <h2 id="counter-intuitive-effects-of-time-limited-interventions">Counter-intuiti
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer>
diff --git a/articles/modelling_time_dependence.html b/articles/modelling_time_dependence.html
index ee91a221..a1707ea6 100644
--- a/articles/modelling_time_dependence.html
+++ b/articles/modelling_time_dependence.html
@@ -17,7 +17,7 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Modelling time-dependence and seasonality in transmission dynamics">
+<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Modelling time-dependence and seasonality in transmission dynamics">
 <meta property="og:description" content="epidemics">
 <meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg">
 <!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -35,12 +35,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
 <li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
@@ -121,11 +120,11 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
 <span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span></code></pre></div>
 </details><div class="alert alert-warning">
-<p><strong>New to <em>epidemics</em>?</strong> It may help to read the <a href="epidemics.html">“Get started”</a> vignette first, and to browse through some of the other vignettes such as <a href="modelling_interventions.html">“Modelling a non-pharmaceutical intervention”</a>, or <a href="rate_interventions.html">“Modelling interventions on epidemic parameters”</a>.</p>
+<p><strong>New to <em>epidemics</em>?</strong> It may help to read the <a href="epidemics.html">“Get started”</a> vignette first, and to browse through some of the other vignettes such as <a href="modelling_interventions.html">“Modelling a non-pharmaceutical intervention”</a>, or <a href="modelling_rate_interventions.html">“Modelling interventions on epidemic parameters”</a>.</p>
 </div>
 <p>This vignette shows how to compose a model in which one or more epidemic parameters vary gradually over time.</p>
 <p>This functionality can be used to compose models that include a seasonal component, i.e., where the epidemic parameters vary due to variation in ambient conditions over the modelled time-period.</p>
-<p>This is intended to be different from <a href="rate_interventions.html">modelling interventions on epidemic parameters</a> by allowing small, continuous changes to the epidemic parameters, while rate interventions are intended to be large step-changes as would be expected from policies such as mask mandates or the roll-out of therapeutics.</p>
+<p>This is intended to be different from <a href="modelling_rate_interventions.html">modelling interventions on epidemic parameters</a> by allowing small, continuous changes to the epidemic parameters, while rate interventions are intended to be large step-changes as would be expected from policies such as mask mandates or the roll-out of therapeutics.</p>
 <p>The time-dependence functionality shown in this vignette is also expected to be a starting point for data-driven modelling in which epidemic parameters vary as a function of externally provided data, such as climate data.</p>
 <div class="section level2">
 <h2 id="setup-and-initial-conditions">Setup and initial conditions<a class="anchor" aria-label="anchor" href="#setup-and-initial-conditions"></a>
@@ -469,13 +468,11 @@ <h2 id="timing-vaccination-to-prevent-epidemic-peaks">Timing vaccination to prev
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer>
diff --git a/articles/modelling_vaccination.html b/articles/modelling_vaccination.html
index 81b0d18b..113ee273 100644
--- a/articles/modelling_vaccination.html
+++ b/articles/modelling_vaccination.html
@@ -17,7 +17,7 @@
 <link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
 <script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous">
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-<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Modelling the effect of a vaccination campaign">
+<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Modelling the effect of a vaccination campaign">
 <meta property="og:description" content="epidemics">
 <meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg">
 <!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -35,12 +35,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -86,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
-
-      <ul class="navbar-nav">
+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
 <li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
@@ -141,7 +140,6 @@ <h2 id="prepare-population-and-initial-conditions">Prepare population and initia
 <span>  age.limits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">20</span>, <span class="fl">65</span><span class="op">)</span>,</span>
 <span>  symmetric <span class="op">=</span> <span class="cn">TRUE</span></span>
 <span><span class="op">)</span></span>
-<span><span class="co">#&gt; Using POLYMOD social contact data. To cite this in a publication, use the 'get_citation()' function</span></span>
 <span><span class="co">#&gt; Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option</span></span>
 <span></span>
 <span><span class="co"># prepare contact matrix</span></span>
@@ -275,13 +273,11 @@ <h2 id="prepare-data-and-visualise-infections">Prepare data and visualise infect
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer>
diff --git a/authors.html b/authors.html
index 8b4ad300..0a1f0d8a 100644
--- a/authors.html
+++ b/authors.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Authors and Citation • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="apple-touch-icon-60x60.png"><script src="deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Authors and Citation"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
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@@ -103,6 +102,10 @@ <h2>Authors</h2>
           <p><strong>Tim Taylor</strong>. Contributor, reviewer. <a href="https://orcid.org/0000-0002-8587-7113" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
+        <li>
+          <p><strong>Banky Ahadzie</strong>. Contributor. 
+          </p>
+        </li>
         <li>
           <p><strong>Hugo Gruson</strong>. Reviewer. <a href="https://orcid.org/0000-0002-4094-1476" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
@@ -111,6 +114,10 @@ <h2>Authors</h2>
           <p><strong>Joshua W. Lambert</strong>. Reviewer. <a href="https://orcid.org/0000-0001-5218-3046" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
+        <li>
+          <p><strong>James M. Azam</strong>. Reviewer. <a href="https://orcid.org/0000-0001-5782-7330" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          </p>
+        </li>
       </ul></div>
 
     <div class="section level2 citation">
@@ -118,15 +125,15 @@ <h2 id="citation">Citation</h2>
       <p><small class="dont-index">Source: <a href="https://github.com/epiverse-trace/epidemics/blob/HEAD/DESCRIPTION" class="external-link"><code>DESCRIPTION</code></a></small></p>
 
       <p>Gupte P, Eggo R, Van Leeuwen E (2024).
-<em>epidemics: A Library of Compartmental Epidemic Scenario Models</em>.
-R package version 0.2.0.9000, 
+<em>epidemics: Composable Epidemic Scenario Modelling</em>.
+R package version 0.3.0, 
 https://epiverse-trace.github.io/epidemics/, <a href="https://github.com/epiverse-trace/epidemics" class="external-link">https://github.com/epiverse-trace/epidemics</a>. 
 </p>
       <pre>@Manual{,
-  title = {epidemics: A Library of Compartmental Epidemic Scenario Models},
+  title = {epidemics: Composable Epidemic Scenario Modelling},
   author = {Pratik Gupte and Rosalind Eggo and Edwin {Van Leeuwen}},
   year = {2024},
-  note = {R package version 0.2.0.9000, 
+  note = {R package version 0.3.0, 
 https://epiverse-trace.github.io/epidemics/},
   url = {https://github.com/epiverse-trace/epidemics},
 }</pre>
@@ -136,11 +143,11 @@ <h2 id="citation">Citation</h2>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
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index 418054fa..6d88bfbf 100644
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3),.btn-group>:not(.btn-check)+.btn,.btn-group>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-bottom-left-radius:0}.dropdown-toggle-split{padding-right:1.5em;padding-left:1.5em}.dropdown-toggle-split::after,.dropup .dropdown-toggle-split::after,.dropend .dropdown-toggle-split::after{margin-left:0}.dropstart .dropdown-toggle-split::before{margin-right:0}.btn-sm+.dropdown-toggle-split,.btn-group-sm>.btn+.dropdown-toggle-split{padding-right:.375rem;padding-left:.375rem}.btn-lg+.dropdown-toggle-split,.btn-group-lg>.btn+.dropdown-toggle-split{padding-right:.75rem;padding-left:.75rem}.btn-group-vertical{flex-direction:column;-webkit-flex-direction:column;align-items:flex-start;-webkit-align-items:flex-start;justify-content:center;-webkit-justify-content:center}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group{width:100%}.btn-group-vertical>.btn:not(:first-child),.btn-group-vertical>.btn-group:not(:first-child){margin-top:calc(var(--bs-border-width) * 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var(--bs-navbar-hover-color);--bs-nav-link-disabled-color: var(--bs-navbar-disabled-color);display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;list-style:none}.navbar-nav .nav-link.active,.navbar-nav .nav-link.show{color:var(--bs-navbar-active-color)}.navbar-nav .dropdown-menu{position:static}.navbar-text{padding-top:.5rem;padding-bottom:.5rem;color:var(--bs-navbar-color)}.navbar-text a,.navbar-text a:hover,.navbar-text a:focus{color:var(--bs-navbar-active-color)}.navbar-collapse{flex-basis:100%;-webkit-flex-basis:100%;flex-grow:1;-webkit-flex-grow:1;align-items:center;-webkit-align-items:center}.navbar-toggler{padding:var(--bs-navbar-toggler-padding-y) var(--bs-navbar-toggler-padding-x);font-size:var(--bs-navbar-toggler-font-size);line-height:1;color:var(--bs-navbar-color);background-color:transparent;border:var(--bs-border-width) solid 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992px){.navbar-expand-lg{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-lg .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-lg .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-lg .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-lg .navbar-nav-scroll{overflow:visible}.navbar-expand-lg .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-lg .navbar-toggler{display:none}.navbar-expand-lg .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-lg .offcanvas .offcanvas-header{display:none}.navbar-expand-lg .offcanvas 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!important;transform:none !important;transition:none}.navbar-expand-xl .offcanvas .offcanvas-header{display:none}.navbar-expand-xl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}@media (min-width: 1400px){.navbar-expand-xxl{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-xxl .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-xxl .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-xxl .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-xxl .navbar-nav-scroll{overflow:visible}.navbar-expand-xxl .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-xxl .navbar-toggler{display:none}.navbar-expand-xxl .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-xxl .offcanvas .offcanvas-header{display:none}.navbar-expand-xxl .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}}.navbar-expand{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand .navbar-nav .dropdown-menu{position:absolute}.navbar-expand .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand .navbar-nav-scroll{overflow:visible}.navbar-expand .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme="dark"]{--bs-navbar-color: rgba(var(--bs-emphasis-color-rgb), 0.55);--bs-navbar-hover-color: rgba(var(--bs-emphasis-color-rgb), 0.75);--bs-navbar-disabled-color: rgba(var(--bs-emphasis-color-rgb), 0.25);--bs-navbar-active-color: rgba(var(--bs-emphasis-color-rgb), 1);--bs-navbar-brand-color: rgba(var(--bs-emphasis-color-rgb), 1);--bs-navbar-brand-hover-color: rgba(var(--bs-emphasis-color-rgb), 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.accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme="dark"] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%2366b0da'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%2366b0da'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: var(--bs-secondary-color);--bs-breadcrumb-item-padding-x: .5rem;--bs-breadcrumb-item-active-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, "/") /* rtl: var(--bs-breadcrumb-divider, "/") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: .75rem;--bs-pagination-padding-y: .375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: var(--bs-link-color);--bs-pagination-bg: var(--bs-body-bg);--bs-pagination-border-width: var(--bs-border-width);--bs-pagination-border-color: var(--bs-border-color);--bs-pagination-border-radius: var(--bs-border-radius);--bs-pagination-hover-color: var(--bs-link-hover-color);--bs-pagination-hover-bg: var(--bs-tertiary-bg);--bs-pagination-hover-border-color: var(--bs-border-color);--bs-pagination-focus-color: var(--bs-link-hover-color);--bs-pagination-focus-bg: var(--bs-secondary-bg);--bs-pagination-focus-box-shadow: 0 0 0 .25rem rgba(0,123,194,0.25);--bs-pagination-active-color: #fff;--bs-pagination-active-bg: #007bc2;--bs-pagination-active-border-color: #007bc2;--bs-pagination-disabled-color: var(--bs-secondary-color);--bs-pagination-disabled-bg: var(--bs-secondary-bg);--bs-pagination-disabled-border-color: var(--bs-border-color);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(var(--bs-border-width) * -1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: .75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x: .5rem;--bs-pagination-padding-y: .25rem;--bs-pagination-font-size:.875rem;--bs-pagination-border-radius: var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x: .65em;--bs-badge-padding-y: .35em;--bs-badge-font-size:.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: var(--bs-border-radius);display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: var(--bs-border-width) solid var(--bs-alert-border-color);--bs-alert-border-radius: var(--bs-border-radius);--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:.75rem;--bs-progress-bg: var(--bs-secondary-bg);--bs-progress-border-radius: var(--bs-border-radius);--bs-progress-box-shadow: var(--bs-box-shadow-inset);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #007bc2;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media (prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media (prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: var(--bs-body-color);--bs-list-group-bg: var(--bs-body-bg);--bs-list-group-border-color: var(--bs-border-color);--bs-list-group-border-width: var(--bs-border-width);--bs-list-group-border-radius: var(--bs-border-radius);--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: .5rem;--bs-list-group-action-color: var(--bs-secondary-color);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-tertiary-bg);--bs-list-group-action-active-color: var(--bs-body-color);--bs-list-group-action-active-bg: var(--bs-secondary-bg);--bs-list-group-disabled-color: var(--bs-secondary-color);--bs-list-group-disabled-bg: var(--bs-body-bg);--bs-list-group-active-color: #fff;--bs-list-group-active-bg: #007bc2;--bs-list-group-active-border-color: #007bc2;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") ". ";counter-increment:section}.list-group-item-action{width:100%;color:var(--bs-list-group-action-color);text-align:inherit}.list-group-item-action:hover,.list-group-item-action:focus{z-index:1;color:var(--bs-list-group-action-hover-color);text-decoration:none;background-color:var(--bs-list-group-action-hover-bg)}.list-group-item-action:active{color:var(--bs-list-group-action-active-color);background-color:var(--bs-list-group-action-active-bg)}.list-group-item{position:relative;display:block;padding:var(--bs-list-group-item-padding-y) var(--bs-list-group-item-padding-x);color:var(--bs-list-group-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-list-group-bg);border:var(--bs-list-group-border-width) solid var(--bs-list-group-border-color)}.list-group-item:first-child{border-top-left-radius:inherit;border-top-right-radius:inherit}.list-group-item:last-child{border-bottom-right-radius:inherit;border-bottom-left-radius:inherit}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1 * var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media (min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 1400px){.list-group-horizontal-xxl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xxl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xxl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xxl>.list-group-item.active{margin-top:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xxl>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}.list-group-flush{border-radius:0}.list-group-flush>.list-group-item{border-width:0 0 var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' 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var(--bs-toast-padding-x));margin-left:var(--bs-toast-padding-x)}.toast-body{padding:var(--bs-toast-padding-x);word-wrap:break-word}.modal{--bs-modal-zindex: 1055;--bs-modal-width: 500px;--bs-modal-padding: 1rem;--bs-modal-margin: .5rem;--bs-modal-color: ;--bs-modal-bg: var(--bs-body-bg);--bs-modal-border-color: var(--bs-border-color-translucent);--bs-modal-border-width: var(--bs-border-width);--bs-modal-border-radius: var(--bs-border-radius-lg);--bs-modal-box-shadow: 0px 1px 2px RGBA(var(--bslib-box-shadow-color-rgb), 0.1),0px 2px 3px RGBA(var(--bslib-box-shadow-color-rgb), 0.1),0px 3px 8px RGBA(var(--bslib-box-shadow-color-rgb), 0.1);--bs-modal-inner-border-radius: calc(var(--bs-border-radius-lg) - (var(--bs-border-width)));--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1.5rem;--bs-modal-header-border-color: var(--bs-border-color);--bs-modal-header-border-width: none;--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: 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.nav-underline{--bs-nav-underline-border-width: 0;--bs-nav-underline-gap: 0}.navbar .nav-underline .nav-link{padding-bottom:calc(var(--bs-navbar-padding-y, .5rem) * 2);margin-bottom:calc(var(--bs-navbar-padding-y, .5rem) * -1)}.bslib-value-box.default .value-box-showcase>i.bi{background:linear-gradient(140deg, #007bc2 36%, #74149c 180%) #007bc2;-webkit-background-clip:text;-webkit-text-fill-color:transparent}.bslib-value-box.default .value-box-showcase>i.fa{background:linear-gradient(140deg, #007bc2 36%, #74149c 180%) #007bc2;-webkit-background-clip:text;-webkit-text-fill-color:transparent}.bslib-value-box.default .value-box-showcase>i.fas{background:linear-gradient(140deg, #007bc2 36%, #74149c 180%) #007bc2;-webkit-background-clip:text;-webkit-text-fill-color:transparent}.bslib-value-box.default .value-box-showcase>i.far{background:linear-gradient(140deg, #007bc2 36%, #74149c 180%) #007bc2;-webkit-background-clip:text;-webkit-text-fill-color:transparent}.bslib-value-box.default .value-box-showcase>i.fab{background:linear-gradient(140deg, #007bc2 36%, #74149c 180%) #007bc2;-webkit-background-clip:text;-webkit-text-fill-color:transparent}.bslib-value-box.default .value-box-showcase>i.material-icons{background:linear-gradient(140deg, #007bc2 36%, #74149c 180%) #007bc2;-webkit-background-clip:text;-webkit-text-fill-color:transparent}.bslib-value-box.default .value-box-showcase>svg.bi{fill:url("#bslib---icon-gradient") #007bc2 !important}.bslib-value-box.default .value-box-showcase>svg.fa{fill:url("#bslib---icon-gradient") #007bc2 !important}.bslib-value-box.default .value-box-showcase>svg.fas{fill:url("#bslib---icon-gradient") #007bc2 !important}.bslib-value-box.default .value-box-showcase>svg.far{fill:url("#bslib---icon-gradient") #007bc2 !important}.bslib-value-box.default .value-box-showcase>svg.fab{fill:url("#bslib---icon-gradient") #007bc2 !important}.bslib-value-box.default .value-box-showcase>svg.material-icons{fill:url("#bslib---icon-gradient") #007bc2 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#198754;--bs-btn-border-color: #198754;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #198754;--bs-btn-hover-border-color: #198754;--bs-btn-focus-shadow-rgb: 25,135,84;--bs-btn-active-color: #fff;--bs-btn-active-bg: #198754;--bs-btn-active-border-color: #198754;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #198754;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #198754;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-info{--bs-btn-color: #0dcaf0;--bs-btn-border-color: #0dcaf0;--bs-btn-hover-color: #000;--bs-btn-hover-bg: #0dcaf0;--bs-btn-hover-border-color: #0dcaf0;--bs-btn-focus-shadow-rgb: 13,202,240;--bs-btn-active-color: #000;--bs-btn-active-bg: #0dcaf0;--bs-btn-active-border-color: #0dcaf0;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #0dcaf0;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #0dcaf0;--bs-btn-bg: transparent;--bs-gradient: 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transparent;--bs-gradient: none}.btn-outline-light{--bs-btn-color: #f8f9fa;--bs-btn-border-color: #f8f9fa;--bs-btn-hover-color: #000;--bs-btn-hover-bg: #f8f9fa;--bs-btn-hover-border-color: #f8f9fa;--bs-btn-focus-shadow-rgb: 248,249,250;--bs-btn-active-color: #000;--bs-btn-active-bg: #f8f9fa;--bs-btn-active-border-color: #f8f9fa;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #f8f9fa;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: #f8f9fa;--bs-btn-bg: transparent;--bs-gradient: none}.btn-outline-dark{--bs-btn-color: #212529;--bs-btn-border-color: #212529;--bs-btn-hover-color: #fff;--bs-btn-hover-bg: #212529;--bs-btn-hover-border-color: #212529;--bs-btn-focus-shadow-rgb: 33,37,41;--bs-btn-active-color: #fff;--bs-btn-active-bg: #212529;--bs-btn-active-border-color: #212529;--bs-btn-active-shadow: inset 0 3px 5px rgba(0,0,0,0.125);--bs-btn-disabled-color: #212529;--bs-btn-disabled-bg: transparent;--bs-btn-disabled-border-color: 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.5rem;--bs-btn-font-size:.875rem;--bs-btn-border-radius: var(--bs-border-radius-sm)}.fade{transition:opacity 0.15s linear}@media (prefers-reduced-motion: reduce){.fade{transition:none}}.fade:not(.show){opacity:0}.collapse:not(.show){display:none}.collapsing{height:0;overflow:hidden;transition:height 0.35s ease}@media (prefers-reduced-motion: reduce){.collapsing{transition:none}}.collapsing.collapse-horizontal{width:0;height:auto;transition:width 0.35s ease}@media (prefers-reduced-motion: reduce){.collapsing.collapse-horizontal{transition:none}}.dropup,.dropend,.dropdown,.dropstart,.dropup-center,.dropdown-center{position:relative}.dropdown-toggle{white-space:nowrap}.dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:.3em solid;border-right:.3em solid transparent;border-bottom:0;border-left:.3em solid transparent}.dropdown-toggle:empty::after{margin-left:0}.dropdown-menu{--bs-dropdown-zindex: 1000;--bs-dropdown-min-width: 10rem;--bs-dropdown-padding-x: 0;--bs-dropdown-padding-y: .5rem;--bs-dropdown-spacer: .125rem;--bs-dropdown-font-size:1rem;--bs-dropdown-color: var(--bs-body-color);--bs-dropdown-bg: var(--bs-body-bg);--bs-dropdown-border-color: var(--bs-border-color-translucent);--bs-dropdown-border-radius: var(--bs-border-radius);--bs-dropdown-border-width: var(--bs-border-width);--bs-dropdown-inner-border-radius: calc(var(--bs-border-radius) - var(--bs-border-width));--bs-dropdown-divider-bg: var(--bs-border-color-translucent);--bs-dropdown-divider-margin-y: .5rem;--bs-dropdown-box-shadow: 0 0.5rem 1rem rgba(0,0,0,0.15);--bs-dropdown-link-color: var(--bs-body-color);--bs-dropdown-link-hover-color: var(--bs-body-color);--bs-dropdown-link-hover-bg: var(--bs-tertiary-bg);--bs-dropdown-link-active-color: #fff;--bs-dropdown-link-active-bg: #0d6efd;--bs-dropdown-link-disabled-color: var(--bs-tertiary-color);--bs-dropdown-item-padding-x: 1rem;--bs-dropdown-item-padding-y: .25rem;--bs-dropdown-header-color: #6c757d;--bs-dropdown-header-padding-x: 1rem;--bs-dropdown-header-padding-y: .5rem;position:absolute;z-index:var(--bs-dropdown-zindex);display:none;min-width:var(--bs-dropdown-min-width);padding:var(--bs-dropdown-padding-y) var(--bs-dropdown-padding-x);margin:0;font-size:var(--bs-dropdown-font-size);color:var(--bs-dropdown-color);text-align:left;list-style:none;background-color:var(--bs-dropdown-bg);background-clip:padding-box;border:var(--bs-dropdown-border-width) solid var(--bs-dropdown-border-color);border-radius:var(--bs-dropdown-border-radius)}.dropdown-menu[data-bs-popper]{top:100%;left:0;margin-top:var(--bs-dropdown-spacer)}.dropdown-menu-start{--bs-position: start}.dropdown-menu-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-end{--bs-position: end}.dropdown-menu-end[data-bs-popper]{right:0;left:auto}@media (min-width: 576px){.dropdown-menu-sm-start{--bs-position: start}.dropdown-menu-sm-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-sm-end{--bs-position: end}.dropdown-menu-sm-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 768px){.dropdown-menu-md-start{--bs-position: start}.dropdown-menu-md-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-md-end{--bs-position: end}.dropdown-menu-md-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 992px){.dropdown-menu-lg-start{--bs-position: start}.dropdown-menu-lg-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-lg-end{--bs-position: end}.dropdown-menu-lg-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 1200px){.dropdown-menu-xl-start{--bs-position: start}.dropdown-menu-xl-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-xl-end{--bs-position: end}.dropdown-menu-xl-end[data-bs-popper]{right:0;left:auto}}@media (min-width: 1400px){.dropdown-menu-xxl-start{--bs-position: start}.dropdown-menu-xxl-start[data-bs-popper]{right:auto;left:0}.dropdown-menu-xxl-end{--bs-position: end}.dropdown-menu-xxl-end[data-bs-popper]{right:0;left:auto}}.dropup .dropdown-menu[data-bs-popper]{top:auto;bottom:100%;margin-top:0;margin-bottom:var(--bs-dropdown-spacer)}.dropup .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:0;border-right:.3em solid transparent;border-bottom:.3em solid;border-left:.3em solid transparent}.dropup .dropdown-toggle:empty::after{margin-left:0}.dropend .dropdown-menu[data-bs-popper]{top:0;right:auto;left:100%;margin-top:0;margin-left:var(--bs-dropdown-spacer)}.dropend .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:"";border-top:.3em solid transparent;border-right:0;border-bottom:.3em solid transparent;border-left:.3em solid}.dropend .dropdown-toggle:empty::after{margin-left:0}.dropend .dropdown-toggle::after{vertical-align:0}.dropstart .dropdown-menu[data-bs-popper]{top:0;right:100%;left:auto;margin-top:0;margin-right:var(--bs-dropdown-spacer)}.dropstart .dropdown-toggle::after{display:inline-block;margin-left:.255em;vertical-align:.255em;content:""}.dropstart .dropdown-toggle::after{display:none}.dropstart .dropdown-toggle::before{display:inline-block;margin-right:.255em;vertical-align:.255em;content:"";border-top:.3em solid transparent;border-right:.3em solid;border-bottom:.3em solid transparent}.dropstart .dropdown-toggle:empty::after{margin-left:0}.dropstart .dropdown-toggle::before{vertical-align:0}.dropdown-divider{height:0;margin:var(--bs-dropdown-divider-margin-y) 0;overflow:hidden;border-top:1px solid var(--bs-dropdown-divider-bg);opacity:1}.dropdown-item{display:block;width:100%;padding:var(--bs-dropdown-item-padding-y) 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auto}.btn-group>.btn-check:checked+.btn,.btn-group>.btn-check:focus+.btn,.btn-group>.btn:hover,.btn-group>.btn:focus,.btn-group>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn-check:checked+.btn,.btn-group-vertical>.btn-check:focus+.btn,.btn-group-vertical>.btn:hover,.btn-group-vertical>.btn:focus,.btn-group-vertical>.btn:active,.btn-group-vertical>.btn.active{z-index:1}.btn-toolbar{display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;justify-content:flex-start;-webkit-justify-content:flex-start}.btn-toolbar .input-group{width:auto}.btn-group{border-radius:var(--bs-border-radius)}.btn-group>:not(.btn-check:first-child)+.btn,.btn-group>.btn-group:not(:first-child){margin-left:calc(var(--bs-border-width) * -1)}.btn-group>.btn:not(:last-child):not(.dropdown-toggle),.btn-group>.btn.dropdown-toggle-split:first-child,.btn-group>.btn-group:not(:last-child)>.btn{border-top-right-radius:0;border-bottom-right-radius:0}.btn-group>.btn:nth-child(n + 3),.btn-group>:not(.btn-check)+.btn,.btn-group>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-bottom-left-radius:0}.dropdown-toggle-split{padding-right:.5625rem;padding-left:.5625rem}.dropdown-toggle-split::after,.dropup .dropdown-toggle-split::after,.dropend .dropdown-toggle-split::after{margin-left:0}.dropstart .dropdown-toggle-split::before{margin-right:0}.btn-sm+.dropdown-toggle-split,.btn-group-sm>.btn+.dropdown-toggle-split{padding-right:.375rem;padding-left:.375rem}.btn-lg+.dropdown-toggle-split,.btn-group-lg>.btn+.dropdown-toggle-split{padding-right:.75rem;padding-left:.75rem}.btn-group-vertical{flex-direction:column;-webkit-flex-direction:column;align-items:flex-start;-webkit-align-items:flex-start;justify-content:center;-webkit-justify-content:center}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group{width:100%}.btn-group-vertical>.btn:not(:first-child),.btn-group-vertical>.btn-group:not(:first-child){margin-top:calc(var(--bs-border-width) * -1)}.btn-group-vertical>.btn:not(:last-child):not(.dropdown-toggle),.btn-group-vertical>.btn-group:not(:last-child)>.btn{border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn~.btn,.btn-group-vertical>.btn-group:not(:first-child)>.btn{border-top-left-radius:0;border-top-right-radius:0}.nav{--bs-nav-link-padding-x: 1rem;--bs-nav-link-padding-y: .5rem;--bs-nav-link-font-weight: ;--bs-nav-link-color: var(--bs-link-color);--bs-nav-link-hover-color: var(--bs-link-hover-color);--bs-nav-link-disabled-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:var(--bs-nav-link-padding-y) 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992px){.navbar-expand-lg{flex-wrap:nowrap;-webkit-flex-wrap:nowrap;justify-content:flex-start;-webkit-justify-content:flex-start}.navbar-expand-lg .navbar-nav{flex-direction:row;-webkit-flex-direction:row}.navbar-expand-lg .navbar-nav .dropdown-menu{position:absolute}.navbar-expand-lg .navbar-nav .nav-link{padding-right:var(--bs-navbar-nav-link-padding-x);padding-left:var(--bs-navbar-nav-link-padding-x)}.navbar-expand-lg .navbar-nav-scroll{overflow:visible}.navbar-expand-lg .navbar-collapse{display:flex !important;display:-webkit-flex !important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand-lg .navbar-toggler{display:none}.navbar-expand-lg .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand-lg .offcanvas .offcanvas-header{display:none}.navbar-expand-lg .offcanvas 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!important;flex-basis:auto;-webkit-flex-basis:auto}.navbar-expand .navbar-toggler{display:none}.navbar-expand .offcanvas{position:static;z-index:auto;flex-grow:1;-webkit-flex-grow:1;width:auto !important;height:auto !important;visibility:visible !important;background-color:transparent !important;border:0 !important;transform:none !important;transition:none}.navbar-expand .offcanvas .offcanvas-header{display:none}.navbar-expand .offcanvas .offcanvas-body{display:flex;display:-webkit-flex;flex-grow:0;-webkit-flex-grow:0;padding:0;overflow-y:visible}.navbar-dark,.navbar[data-bs-theme="dark"]{--bs-navbar-color: rgba(var(--bs-emphasis-color-rgb), 0.55);--bs-navbar-hover-color: rgba(var(--bs-emphasis-color-rgb), 0.75);--bs-navbar-disabled-color: rgba(var(--bs-emphasis-color-rgb), 0.25);--bs-navbar-active-color: rgba(var(--bs-emphasis-color-rgb), 1);--bs-navbar-brand-color: rgba(var(--bs-emphasis-color-rgb), 1);--bs-navbar-brand-hover-color: rgba(var(--bs-emphasis-color-rgb), 1);--bs-navbar-toggler-border-color: rgba(var(--bs-emphasis-color-rgb), 0.1);--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255,255,255,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}[data-bs-theme="dark"] .navbar-toggler-icon{--bs-navbar-toggler-icon-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255,255,255,0.75%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e")}.card{--bs-card-spacer-y: 1rem;--bs-card-spacer-x: 1rem;--bs-card-title-spacer-y: .5rem;--bs-card-title-color: ;--bs-card-subtitle-color: ;--bs-card-border-width: var(--bs-border-width);--bs-card-border-color: var(--bs-border-color-translucent);--bs-card-border-radius: var(--bs-border-radius);--bs-card-box-shadow: ;--bs-card-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-card-cap-padding-y: .5rem;--bs-card-cap-padding-x: 1rem;--bs-card-cap-bg: rgba(var(--bs-body-color-rgb), 0.03);--bs-card-cap-color: ;--bs-card-height: ;--bs-card-color: ;--bs-card-bg: var(--bs-body-bg);--bs-card-img-overlay-padding: 1rem;--bs-card-group-margin: .75rem;position:relative;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;min-width:0;height:var(--bs-card-height);color:var(--bs-body-color);word-wrap:break-word;background-color:var(--bs-card-bg);background-clip:border-box;border:var(--bs-card-border-width) solid var(--bs-card-border-color);border-radius:var(--bs-card-border-radius)}.card>hr{margin-right:0;margin-left:0}.card>.list-group{border-top:inherit;border-bottom:inherit}.card>.list-group:first-child{border-top-width:0;border-top-left-radius:var(--bs-card-inner-border-radius);border-top-right-radius:var(--bs-card-inner-border-radius)}.card>.list-group:last-child{border-bottom-width:0;border-bottom-right-radius:var(--bs-card-inner-border-radius);border-bottom-left-radius:var(--bs-card-inner-border-radius)}.card>.card-header+.list-group,.card>.list-group+.card-footer{border-top:0}.card-body{flex:1 1 auto;-webkit-flex:1 1 auto;padding:var(--bs-card-spacer-y) var(--bs-card-spacer-x);color:var(--bs-card-color)}.card-title{margin-bottom:var(--bs-card-title-spacer-y);color:var(--bs-card-title-color)}.card-subtitle{margin-top:calc(-.5 * var(--bs-card-title-spacer-y));margin-bottom:0;color:var(--bs-card-subtitle-color)}.card-text:last-child{margin-bottom:0}.card-link+.card-link{margin-left:var(--bs-card-spacer-x)}.card-header{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);margin-bottom:0;color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-bottom:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-header:first-child{border-radius:var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius) 0 0}.card-footer{padding:var(--bs-card-cap-padding-y) var(--bs-card-cap-padding-x);color:var(--bs-card-cap-color);background-color:var(--bs-card-cap-bg);border-top:var(--bs-card-border-width) solid var(--bs-card-border-color)}.card-footer:last-child{border-radius:0 0 var(--bs-card-inner-border-radius) var(--bs-card-inner-border-radius)}.card-header-tabs{margin-right:calc(-.5 * var(--bs-card-cap-padding-x));margin-bottom:calc(-1 * 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wrap;-webkit-flex-flow:row wrap}.card-group>.card{flex:1 0 0%;-webkit-flex:1 0 0%;margin-bottom:0}.card-group>.card+.card{margin-left:0;border-left:0}.card-group>.card:not(:last-child){border-top-right-radius:0;border-bottom-right-radius:0}.card-group>.card:not(:last-child) .card-img-top,.card-group>.card:not(:last-child) .card-header{border-top-right-radius:0}.card-group>.card:not(:last-child) .card-img-bottom,.card-group>.card:not(:last-child) .card-footer{border-bottom-right-radius:0}.card-group>.card:not(:first-child){border-top-left-radius:0;border-bottom-left-radius:0}.card-group>.card:not(:first-child) .card-img-top,.card-group>.card:not(:first-child) .card-header{border-top-left-radius:0}.card-group>.card:not(:first-child) .card-img-bottom,.card-group>.card:not(:first-child) .card-footer{border-bottom-left-radius:0}}.accordion{--bs-accordion-color: var(--bs-body-color);--bs-accordion-bg: var(--bs-body-bg);--bs-accordion-transition: color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out,border-radius 0.15s ease;--bs-accordion-border-color: var(--bs-border-color);--bs-accordion-border-width: var(--bs-border-width);--bs-accordion-border-radius: var(--bs-border-radius);--bs-accordion-inner-border-radius: calc(var(--bs-border-radius) - (var(--bs-border-width)));--bs-accordion-btn-padding-x: 1.25rem;--bs-accordion-btn-padding-y: 1rem;--bs-accordion-btn-color: var(--bs-body-color);--bs-accordion-btn-bg: var(--bs-accordion-bg);--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23212529'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-icon-width: 1.25rem;--bs-accordion-btn-icon-transform: rotate(-180deg);--bs-accordion-btn-icon-transition: transform 0.2s ease-in-out;--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23052c65'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-focus-border-color: #86b7fe;--bs-accordion-btn-focus-box-shadow: 0 0 0 .25rem rgba(13,110,253,0.25);--bs-accordion-body-padding-x: 1.25rem;--bs-accordion-body-padding-y: 1rem;--bs-accordion-active-color: var(--bs-primary-text-emphasis);--bs-accordion-active-bg: var(--bs-primary-bg-subtle)}.accordion-button{position:relative;display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;width:100%;padding:var(--bs-accordion-btn-padding-y) var(--bs-accordion-btn-padding-x);font-size:1rem;color:var(--bs-accordion-btn-color);text-align:left;background-color:var(--bs-accordion-btn-bg);border:0;border-radius:0;overflow-anchor:none;transition:var(--bs-accordion-transition)}@media (prefers-reduced-motion: reduce){.accordion-button{transition:none}}.accordion-button:not(.collapsed){color:var(--bs-accordion-active-color);background-color:var(--bs-accordion-active-bg);box-shadow:inset 0 calc(-1 * var(--bs-accordion-border-width)) 0 var(--bs-accordion-border-color)}.accordion-button:not(.collapsed)::after{background-image:var(--bs-accordion-btn-active-icon);transform:var(--bs-accordion-btn-icon-transform)}.accordion-button::after{flex-shrink:0;-webkit-flex-shrink:0;width:var(--bs-accordion-btn-icon-width);height:var(--bs-accordion-btn-icon-width);margin-left:auto;content:"";background-image:var(--bs-accordion-btn-icon);background-repeat:no-repeat;background-size:var(--bs-accordion-btn-icon-width);transition:var(--bs-accordion-btn-icon-transition)}@media (prefers-reduced-motion: reduce){.accordion-button::after{transition:none}}.accordion-button:hover{z-index:2}.accordion-button:focus{z-index:3;border-color:var(--bs-accordion-btn-focus-border-color);outline:0;box-shadow:var(--bs-accordion-btn-focus-box-shadow)}.accordion-header{margin-bottom:0}.accordion-item{color:var(--bs-accordion-color);background-color:var(--bs-accordion-bg);border:var(--bs-accordion-border-width) solid var(--bs-accordion-border-color)}.accordion-item:first-of-type{border-top-left-radius:var(--bs-accordion-border-radius);border-top-right-radius:var(--bs-accordion-border-radius)}.accordion-item:first-of-type .accordion-button{border-top-left-radius:var(--bs-accordion-inner-border-radius);border-top-right-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:not(:first-of-type){border-top:0}.accordion-item:last-of-type{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-item:last-of-type .accordion-button.collapsed{border-bottom-right-radius:var(--bs-accordion-inner-border-radius);border-bottom-left-radius:var(--bs-accordion-inner-border-radius)}.accordion-item:last-of-type .accordion-collapse{border-bottom-right-radius:var(--bs-accordion-border-radius);border-bottom-left-radius:var(--bs-accordion-border-radius)}.accordion-body{padding:var(--bs-accordion-body-padding-y) var(--bs-accordion-body-padding-x)}.accordion-flush .accordion-collapse{border-width:0}.accordion-flush .accordion-item{border-right:0;border-left:0;border-radius:0}.accordion-flush .accordion-item:first-child{border-top:0}.accordion-flush .accordion-item:last-child{border-bottom:0}.accordion-flush .accordion-item .accordion-button,.accordion-flush .accordion-item .accordion-button.collapsed{border-radius:0}[data-bs-theme="dark"] .accordion-button::after{--bs-accordion-btn-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e");--bs-accordion-btn-active-icon: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%236ea8fe'%3e%3cpath fill-rule='evenodd' d='M1.646 4.646a.5.5 0 0 1 .708 0L8 10.293l5.646-5.647a.5.5 0 0 1 .708.708l-6 6a.5.5 0 0 1-.708 0l-6-6a.5.5 0 0 1 0-.708z'/%3e%3c/svg%3e")}.breadcrumb{--bs-breadcrumb-padding-x: 0;--bs-breadcrumb-padding-y: 0;--bs-breadcrumb-margin-bottom: 1rem;--bs-breadcrumb-bg: ;--bs-breadcrumb-border-radius: ;--bs-breadcrumb-divider-color: var(--bs-secondary-color);--bs-breadcrumb-item-padding-x: .5rem;--bs-breadcrumb-item-active-color: var(--bs-secondary-color);display:flex;display:-webkit-flex;flex-wrap:wrap;-webkit-flex-wrap:wrap;padding:var(--bs-breadcrumb-padding-y) var(--bs-breadcrumb-padding-x);margin-bottom:var(--bs-breadcrumb-margin-bottom);font-size:var(--bs-breadcrumb-font-size);list-style:none;background-color:var(--bs-breadcrumb-bg);border-radius:var(--bs-breadcrumb-border-radius)}.breadcrumb-item+.breadcrumb-item{padding-left:var(--bs-breadcrumb-item-padding-x)}.breadcrumb-item+.breadcrumb-item::before{float:left;padding-right:var(--bs-breadcrumb-item-padding-x);color:var(--bs-breadcrumb-divider-color);content:var(--bs-breadcrumb-divider, "/") /* rtl: var(--bs-breadcrumb-divider, "/") */}.breadcrumb-item.active{color:var(--bs-breadcrumb-item-active-color)}.pagination{--bs-pagination-padding-x: .75rem;--bs-pagination-padding-y: .375rem;--bs-pagination-font-size:1rem;--bs-pagination-color: var(--bs-link-color);--bs-pagination-bg: var(--bs-body-bg);--bs-pagination-border-width: var(--bs-border-width);--bs-pagination-border-color: var(--bs-border-color);--bs-pagination-border-radius: var(--bs-border-radius);--bs-pagination-hover-color: var(--bs-link-hover-color);--bs-pagination-hover-bg: var(--bs-tertiary-bg);--bs-pagination-hover-border-color: var(--bs-border-color);--bs-pagination-focus-color: var(--bs-link-hover-color);--bs-pagination-focus-bg: var(--bs-secondary-bg);--bs-pagination-focus-box-shadow: 0 0 0 .25rem rgba(13,110,253,0.25);--bs-pagination-active-color: #fff;--bs-pagination-active-bg: #0d6efd;--bs-pagination-active-border-color: #0d6efd;--bs-pagination-disabled-color: var(--bs-secondary-color);--bs-pagination-disabled-bg: var(--bs-secondary-bg);--bs-pagination-disabled-border-color: var(--bs-border-color);display:flex;display:-webkit-flex;padding-left:0;list-style:none}.page-link{position:relative;display:block;padding:var(--bs-pagination-padding-y) var(--bs-pagination-padding-x);font-size:var(--bs-pagination-font-size);color:var(--bs-pagination-color);text-decoration:none;-webkit-text-decoration:none;-moz-text-decoration:none;-ms-text-decoration:none;-o-text-decoration:none;background-color:var(--bs-pagination-bg);border:var(--bs-pagination-border-width) solid var(--bs-pagination-border-color);transition:color 0.15s ease-in-out,background-color 0.15s ease-in-out,border-color 0.15s ease-in-out,box-shadow 0.15s ease-in-out}@media (prefers-reduced-motion: reduce){.page-link{transition:none}}.page-link:hover{z-index:2;color:var(--bs-pagination-hover-color);background-color:var(--bs-pagination-hover-bg);border-color:var(--bs-pagination-hover-border-color)}.page-link:focus{z-index:3;color:var(--bs-pagination-focus-color);background-color:var(--bs-pagination-focus-bg);outline:0;box-shadow:var(--bs-pagination-focus-box-shadow)}.page-link.active,.active>.page-link{z-index:3;color:var(--bs-pagination-active-color);background-color:var(--bs-pagination-active-bg);border-color:var(--bs-pagination-active-border-color)}.page-link.disabled,.disabled>.page-link{color:var(--bs-pagination-disabled-color);pointer-events:none;background-color:var(--bs-pagination-disabled-bg);border-color:var(--bs-pagination-disabled-border-color)}.page-item:not(:first-child) .page-link{margin-left:calc(var(--bs-border-width) * -1)}.page-item:first-child .page-link{border-top-left-radius:var(--bs-pagination-border-radius);border-bottom-left-radius:var(--bs-pagination-border-radius)}.page-item:last-child .page-link{border-top-right-radius:var(--bs-pagination-border-radius);border-bottom-right-radius:var(--bs-pagination-border-radius)}.pagination-lg{--bs-pagination-padding-x: 1.5rem;--bs-pagination-padding-y: .75rem;--bs-pagination-font-size:1.25rem;--bs-pagination-border-radius: var(--bs-border-radius-lg)}.pagination-sm{--bs-pagination-padding-x: .5rem;--bs-pagination-padding-y: .25rem;--bs-pagination-font-size:.875rem;--bs-pagination-border-radius: var(--bs-border-radius-sm)}.badge{--bs-badge-padding-x: .65em;--bs-badge-padding-y: .35em;--bs-badge-font-size:.75em;--bs-badge-font-weight: 700;--bs-badge-color: #fff;--bs-badge-border-radius: var(--bs-border-radius);display:inline-block;padding:var(--bs-badge-padding-y) var(--bs-badge-padding-x);font-size:var(--bs-badge-font-size);font-weight:var(--bs-badge-font-weight);line-height:1;color:var(--bs-badge-color);text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:var(--bs-badge-border-radius)}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.alert{--bs-alert-bg: transparent;--bs-alert-padding-x: 1rem;--bs-alert-padding-y: 1rem;--bs-alert-margin-bottom: 1rem;--bs-alert-color: inherit;--bs-alert-border-color: transparent;--bs-alert-border: var(--bs-border-width) solid var(--bs-alert-border-color);--bs-alert-border-radius: var(--bs-border-radius);--bs-alert-link-color: inherit;position:relative;padding:var(--bs-alert-padding-y) var(--bs-alert-padding-x);margin-bottom:var(--bs-alert-margin-bottom);color:var(--bs-alert-color);background-color:var(--bs-alert-bg);border:var(--bs-alert-border);border-radius:var(--bs-alert-border-radius)}.alert-heading{color:inherit}.alert-link{font-weight:700;color:var(--bs-alert-link-color)}.alert-dismissible{padding-right:3rem}.alert-dismissible .btn-close{position:absolute;top:0;right:0;z-index:2;padding:1.25rem 1rem}.alert-default{--bs-alert-color: var(--bs-default-text-emphasis);--bs-alert-bg: var(--bs-default-bg-subtle);--bs-alert-border-color: var(--bs-default-border-subtle);--bs-alert-link-color: var(--bs-default-text-emphasis)}.alert-primary{--bs-alert-color: var(--bs-primary-text-emphasis);--bs-alert-bg: var(--bs-primary-bg-subtle);--bs-alert-border-color: var(--bs-primary-border-subtle);--bs-alert-link-color: var(--bs-primary-text-emphasis)}.alert-secondary{--bs-alert-color: var(--bs-secondary-text-emphasis);--bs-alert-bg: var(--bs-secondary-bg-subtle);--bs-alert-border-color: var(--bs-secondary-border-subtle);--bs-alert-link-color: var(--bs-secondary-text-emphasis)}.alert-success{--bs-alert-color: var(--bs-success-text-emphasis);--bs-alert-bg: var(--bs-success-bg-subtle);--bs-alert-border-color: var(--bs-success-border-subtle);--bs-alert-link-color: var(--bs-success-text-emphasis)}.alert-info{--bs-alert-color: var(--bs-info-text-emphasis);--bs-alert-bg: var(--bs-info-bg-subtle);--bs-alert-border-color: var(--bs-info-border-subtle);--bs-alert-link-color: var(--bs-info-text-emphasis)}.alert-warning{--bs-alert-color: var(--bs-warning-text-emphasis);--bs-alert-bg: var(--bs-warning-bg-subtle);--bs-alert-border-color: var(--bs-warning-border-subtle);--bs-alert-link-color: var(--bs-warning-text-emphasis)}.alert-danger{--bs-alert-color: var(--bs-danger-text-emphasis);--bs-alert-bg: var(--bs-danger-bg-subtle);--bs-alert-border-color: var(--bs-danger-border-subtle);--bs-alert-link-color: var(--bs-danger-text-emphasis)}.alert-light{--bs-alert-color: var(--bs-light-text-emphasis);--bs-alert-bg: var(--bs-light-bg-subtle);--bs-alert-border-color: var(--bs-light-border-subtle);--bs-alert-link-color: var(--bs-light-text-emphasis)}.alert-dark{--bs-alert-color: var(--bs-dark-text-emphasis);--bs-alert-bg: var(--bs-dark-bg-subtle);--bs-alert-border-color: var(--bs-dark-border-subtle);--bs-alert-link-color: var(--bs-dark-text-emphasis)}@keyframes progress-bar-stripes{0%{background-position-x:1rem}}.progress,.progress-stacked{--bs-progress-height: 1rem;--bs-progress-font-size:.75rem;--bs-progress-bg: var(--bs-secondary-bg);--bs-progress-border-radius: var(--bs-border-radius);--bs-progress-box-shadow: var(--bs-box-shadow-inset);--bs-progress-bar-color: #fff;--bs-progress-bar-bg: #0d6efd;--bs-progress-bar-transition: width 0.6s ease;display:flex;display:-webkit-flex;height:var(--bs-progress-height);overflow:hidden;font-size:var(--bs-progress-font-size);background-color:var(--bs-progress-bg);border-radius:var(--bs-progress-border-radius)}.progress-bar{display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;justify-content:center;-webkit-justify-content:center;overflow:hidden;color:var(--bs-progress-bar-color);text-align:center;white-space:nowrap;background-color:var(--bs-progress-bar-bg);transition:var(--bs-progress-bar-transition)}@media (prefers-reduced-motion: reduce){.progress-bar{transition:none}}.progress-bar-striped{background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-size:var(--bs-progress-height) var(--bs-progress-height)}.progress-stacked>.progress{overflow:visible}.progress-stacked>.progress>.progress-bar{width:100%}.progress-bar-animated{animation:1s linear infinite progress-bar-stripes}@media (prefers-reduced-motion: reduce){.progress-bar-animated{animation:none}}.list-group{--bs-list-group-color: var(--bs-body-color);--bs-list-group-bg: var(--bs-body-bg);--bs-list-group-border-color: var(--bs-border-color);--bs-list-group-border-width: var(--bs-border-width);--bs-list-group-border-radius: var(--bs-border-radius);--bs-list-group-item-padding-x: 1rem;--bs-list-group-item-padding-y: .5rem;--bs-list-group-action-color: var(--bs-secondary-color);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-tertiary-bg);--bs-list-group-action-active-color: var(--bs-body-color);--bs-list-group-action-active-bg: var(--bs-secondary-bg);--bs-list-group-disabled-color: var(--bs-secondary-color);--bs-list-group-disabled-bg: var(--bs-body-bg);--bs-list-group-active-color: #fff;--bs-list-group-active-bg: #0d6efd;--bs-list-group-active-border-color: #0d6efd;display:flex;display:-webkit-flex;flex-direction:column;-webkit-flex-direction:column;padding-left:0;margin-bottom:0;border-radius:var(--bs-list-group-border-radius)}.list-group-numbered{list-style-type:none;counter-reset:section}.list-group-numbered>.list-group-item::before{content:counters(section, ".") 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var(--bs-list-group-border-color)}.list-group-item:first-child{border-top-left-radius:inherit;border-top-right-radius:inherit}.list-group-item:last-child{border-bottom-right-radius:inherit;border-bottom-left-radius:inherit}.list-group-item.disabled,.list-group-item:disabled{color:var(--bs-list-group-disabled-color);pointer-events:none;background-color:var(--bs-list-group-disabled-bg)}.list-group-item.active{z-index:2;color:var(--bs-list-group-active-color);background-color:var(--bs-list-group-active-bg);border-color:var(--bs-list-group-active-border-color)}.list-group-item+.list-group-item{border-top-width:0}.list-group-item+.list-group-item.active{margin-top:calc(-1 * var(--bs-list-group-border-width));border-top-width:var(--bs-list-group-border-width)}.list-group-horizontal{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal>.list-group-item.active{margin-top:0}.list-group-horizontal>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}@media (min-width: 576px){.list-group-horizontal-sm{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-sm>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-sm>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-sm>.list-group-item.active{margin-top:0}.list-group-horizontal-sm>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-sm>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 768px){.list-group-horizontal-md{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-md>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-md>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-md>.list-group-item.active{margin-top:0}.list-group-horizontal-md>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-md>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 992px){.list-group-horizontal-lg{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-lg>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-lg>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-lg>.list-group-item.active{margin-top:0}.list-group-horizontal-lg>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-lg>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 1200px){.list-group-horizontal-xl{flex-direction:row;-webkit-flex-direction:row}.list-group-horizontal-xl>.list-group-item:first-child:not(:last-child){border-bottom-left-radius:var(--bs-list-group-border-radius);border-top-right-radius:0}.list-group-horizontal-xl>.list-group-item:last-child:not(:first-child){border-top-right-radius:var(--bs-list-group-border-radius);border-bottom-left-radius:0}.list-group-horizontal-xl>.list-group-item.active{margin-top:0}.list-group-horizontal-xl>.list-group-item+.list-group-item{border-top-width:var(--bs-list-group-border-width);border-left-width:0}.list-group-horizontal-xl>.list-group-item+.list-group-item.active{margin-left:calc(-1 * var(--bs-list-group-border-width));border-left-width:var(--bs-list-group-border-width)}}@media (min-width: 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var(--bs-list-group-border-width)}.list-group-flush>.list-group-item:last-child{border-bottom-width:0}.list-group-item-default{--bs-list-group-color: var(--bs-default-text-emphasis);--bs-list-group-bg: var(--bs-default-bg-subtle);--bs-list-group-border-color: var(--bs-default-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-default-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-default-border-subtle);--bs-list-group-active-color: var(--bs-default-bg-subtle);--bs-list-group-active-bg: var(--bs-default-text-emphasis);--bs-list-group-active-border-color: var(--bs-default-text-emphasis)}.list-group-item-primary{--bs-list-group-color: var(--bs-primary-text-emphasis);--bs-list-group-bg: var(--bs-primary-bg-subtle);--bs-list-group-border-color: var(--bs-primary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-primary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-primary-border-subtle);--bs-list-group-active-color: var(--bs-primary-bg-subtle);--bs-list-group-active-bg: var(--bs-primary-text-emphasis);--bs-list-group-active-border-color: var(--bs-primary-text-emphasis)}.list-group-item-secondary{--bs-list-group-color: var(--bs-secondary-text-emphasis);--bs-list-group-bg: var(--bs-secondary-bg-subtle);--bs-list-group-border-color: var(--bs-secondary-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-secondary-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-secondary-border-subtle);--bs-list-group-active-color: var(--bs-secondary-bg-subtle);--bs-list-group-active-bg: var(--bs-secondary-text-emphasis);--bs-list-group-active-border-color: var(--bs-secondary-text-emphasis)}.list-group-item-success{--bs-list-group-color: var(--bs-success-text-emphasis);--bs-list-group-bg: var(--bs-success-bg-subtle);--bs-list-group-border-color: var(--bs-success-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-success-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-success-border-subtle);--bs-list-group-active-color: var(--bs-success-bg-subtle);--bs-list-group-active-bg: var(--bs-success-text-emphasis);--bs-list-group-active-border-color: var(--bs-success-text-emphasis)}.list-group-item-info{--bs-list-group-color: var(--bs-info-text-emphasis);--bs-list-group-bg: var(--bs-info-bg-subtle);--bs-list-group-border-color: var(--bs-info-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-info-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-info-border-subtle);--bs-list-group-active-color: var(--bs-info-bg-subtle);--bs-list-group-active-bg: var(--bs-info-text-emphasis);--bs-list-group-active-border-color: var(--bs-info-text-emphasis)}.list-group-item-warning{--bs-list-group-color: var(--bs-warning-text-emphasis);--bs-list-group-bg: var(--bs-warning-bg-subtle);--bs-list-group-border-color: var(--bs-warning-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-warning-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-warning-border-subtle);--bs-list-group-active-color: var(--bs-warning-bg-subtle);--bs-list-group-active-bg: var(--bs-warning-text-emphasis);--bs-list-group-active-border-color: var(--bs-warning-text-emphasis)}.list-group-item-danger{--bs-list-group-color: var(--bs-danger-text-emphasis);--bs-list-group-bg: var(--bs-danger-bg-subtle);--bs-list-group-border-color: var(--bs-danger-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-danger-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-danger-border-subtle);--bs-list-group-active-color: var(--bs-danger-bg-subtle);--bs-list-group-active-bg: var(--bs-danger-text-emphasis);--bs-list-group-active-border-color: var(--bs-danger-text-emphasis)}.list-group-item-light{--bs-list-group-color: var(--bs-light-text-emphasis);--bs-list-group-bg: var(--bs-light-bg-subtle);--bs-list-group-border-color: var(--bs-light-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-light-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-light-border-subtle);--bs-list-group-active-color: var(--bs-light-bg-subtle);--bs-list-group-active-bg: var(--bs-light-text-emphasis);--bs-list-group-active-border-color: var(--bs-light-text-emphasis)}.list-group-item-dark{--bs-list-group-color: var(--bs-dark-text-emphasis);--bs-list-group-bg: var(--bs-dark-bg-subtle);--bs-list-group-border-color: var(--bs-dark-border-subtle);--bs-list-group-action-hover-color: var(--bs-emphasis-color);--bs-list-group-action-hover-bg: var(--bs-dark-border-subtle);--bs-list-group-action-active-color: var(--bs-emphasis-color);--bs-list-group-action-active-bg: var(--bs-dark-border-subtle);--bs-list-group-active-color: var(--bs-dark-bg-subtle);--bs-list-group-active-bg: var(--bs-dark-text-emphasis);--bs-list-group-active-border-color: var(--bs-dark-text-emphasis)}.btn-close{--bs-btn-close-color: #000;--bs-btn-close-bg: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16' fill='%23000'%3e%3cpath d='M.293.293a1 1 0 0 1 1.414 0L8 6.586 14.293.293a1 1 0 1 1 1.414 1.414L9.414 8l6.293 6.293a1 1 0 0 1-1.414 1.414L8 9.414l-6.293 6.293a1 1 0 0 1-1.414-1.414L6.586 8 .293 1.707a1 1 0 0 1 0-1.414z'/%3e%3c/svg%3e");--bs-btn-close-opacity: .5;--bs-btn-close-hover-opacity: .75;--bs-btn-close-focus-shadow: 0 0 0 .25rem rgba(13,110,253,0.25);--bs-btn-close-focus-opacity: 1;--bs-btn-close-disabled-opacity: .25;--bs-btn-close-white-filter: invert(1) grayscale(100%) brightness(200%);box-sizing:content-box;width:1em;height:1em;padding:.25em .25em;color:var(--bs-btn-close-color);background:transparent var(--bs-btn-close-bg) center/1em auto no-repeat;border:0;border-radius:.375rem;opacity:var(--bs-btn-close-opacity)}.btn-close:hover{color:var(--bs-btn-close-color);text-decoration:none;opacity:var(--bs-btn-close-hover-opacity)}.btn-close:focus{outline:0;box-shadow:var(--bs-btn-close-focus-shadow);opacity:var(--bs-btn-close-focus-opacity)}.btn-close:disabled,.btn-close.disabled{pointer-events:none;user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;-o-user-select:none;opacity:var(--bs-btn-close-disabled-opacity)}.btn-close-white{filter:var(--bs-btn-close-white-filter)}[data-bs-theme="dark"] .btn-close{filter:var(--bs-btn-close-white-filter)}.toast{--bs-toast-zindex: 1090;--bs-toast-padding-x: .75rem;--bs-toast-padding-y: .5rem;--bs-toast-spacing: 1.5rem;--bs-toast-max-width: 350px;--bs-toast-font-size:.875rem;--bs-toast-color: ;--bs-toast-bg: rgba(var(--bs-body-bg-rgb), 0.85);--bs-toast-border-width: var(--bs-border-width);--bs-toast-border-color: var(--bs-border-color-translucent);--bs-toast-border-radius: var(--bs-border-radius);--bs-toast-box-shadow: var(--bs-box-shadow);--bs-toast-header-color: var(--bs-secondary-color);--bs-toast-header-bg: rgba(var(--bs-body-bg-rgb), 0.85);--bs-toast-header-border-color: var(--bs-border-color-translucent);width:var(--bs-toast-max-width);max-width:100%;font-size:var(--bs-toast-font-size);color:var(--bs-toast-color);pointer-events:auto;background-color:var(--bs-toast-bg);background-clip:padding-box;border:var(--bs-toast-border-width) solid var(--bs-toast-border-color);box-shadow:var(--bs-toast-box-shadow);border-radius:var(--bs-toast-border-radius)}.toast.showing{opacity:0}.toast:not(.show){display:none}.toast-container{--bs-toast-zindex: 1090;position:absolute;z-index:var(--bs-toast-zindex);width:max-content;width:-webkit-max-content;width:-moz-max-content;width:-ms-max-content;width:-o-max-content;max-width:100%;pointer-events:none}.toast-container>:not(:last-child){margin-bottom:var(--bs-toast-spacing)}.toast-header{display:flex;display:-webkit-flex;align-items:center;-webkit-align-items:center;padding:var(--bs-toast-padding-y) var(--bs-toast-padding-x);color:var(--bs-toast-header-color);background-color:var(--bs-toast-header-bg);background-clip:padding-box;border-bottom:var(--bs-toast-border-width) solid var(--bs-toast-header-border-color);border-top-left-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width));border-top-right-radius:calc(var(--bs-toast-border-radius) - var(--bs-toast-border-width))}.toast-header .btn-close{margin-right:calc(-.5 * var(--bs-toast-padding-x));margin-left:var(--bs-toast-padding-x)}.toast-body{padding:var(--bs-toast-padding-x);word-wrap:break-word}.modal{--bs-modal-zindex: 1055;--bs-modal-width: 500px;--bs-modal-padding: 1rem;--bs-modal-margin: .5rem;--bs-modal-color: ;--bs-modal-bg: var(--bs-body-bg);--bs-modal-border-color: var(--bs-border-color-translucent);--bs-modal-border-width: var(--bs-border-width);--bs-modal-border-radius: var(--bs-border-radius-lg);--bs-modal-box-shadow: 0 0.125rem 0.25rem rgba(0,0,0,0.075);--bs-modal-inner-border-radius: calc(var(--bs-border-radius-lg) - (var(--bs-border-width)));--bs-modal-header-padding-x: 1rem;--bs-modal-header-padding-y: 1rem;--bs-modal-header-padding: 1rem 1rem;--bs-modal-header-border-color: var(--bs-border-color);--bs-modal-header-border-width: var(--bs-border-width);--bs-modal-title-line-height: 1.5;--bs-modal-footer-gap: .5rem;--bs-modal-footer-bg: ;--bs-modal-footer-border-color: var(--bs-border-color);--bs-modal-footer-border-width: 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diff --git a/index.html b/index.html
index 4486fea1..c5b5ca71 100644
--- a/index.html
+++ b/index.html
@@ -5,14 +5,8 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-<meta name="description" content="A library of compartmental epidemic models taken from the
-    published literature, and classes to represent populations with
-    heterogeneous characteristics, public health response measures
-    including non-pharmaceutical interventions on social contacts,
-    non-pharmaceutical and pharmaceutical interventions that affect
-    disease transmissibility, vaccination regimes, and disease
-    seasonality, which can be combined to compose epidemic scenarios.">
-<title>A Library of Compartmental Epidemic Scenario Models • epidemics</title>
+<meta name="description" content="A library of compartmental epidemic models taken from the published literature, and classes to represent affected populations, public health response measures including non-pharmaceutical interventions on social contacts, non-pharmaceutical and pharmaceutical interventions that affect disease transmissibility, vaccination regimes, and disease seasonality, which can be combined to compose epidemic scenario models.">
+<title>Composable Epidemic Scenario Modelling • epidemics</title>
 <!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="favicon-16x16.png">
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-<meta property="og:description" content="A library of compartmental epidemic models taken from the
-    published literature, and classes to represent populations with
-    heterogeneous characteristics, public health response measures
-    including non-pharmaceutical interventions on social contacts,
-    non-pharmaceutical and pharmaceutical interventions that affect
-    disease transmissibility, vaccination regimes, and disease
-    seasonality, which can be combined to compose epidemic scenarios.">
+<!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Composable Epidemic Scenario Modelling">
+<meta property="og:description" content="A library of compartmental epidemic models taken from the published literature, and classes to represent affected populations, public health response measures including non-pharmaceutical interventions on social contacts, non-pharmaceutical and pharmaceutical interventions that affect disease transmissibility, vaccination regimes, and disease seasonality, which can be combined to compose epidemic scenario models.">
 <meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg">
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@@ -47,12 +35,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
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-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
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@@ -98,11 +86,10 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
       </ul>
-<form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
-</form>
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+<ul class="navbar-nav">
+<li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json">
+</form></li>
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     <span class="fab fa fab fa-github fa-lg"></span>
@@ -118,13 +105,13 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <div class="row">
   <main id="main" class="col-md-9"><div class="section level1">
 <div class="page-header">
-<img src="logo.svg" class="logo" alt=""><h1 id="epidemics-a-library-of-compartmental-epidemic-scenario-models-">epidemics: A library of compartmental epidemic scenario models <a class="anchor" aria-label="anchor" href="#epidemics-a-library-of-compartmental-epidemic-scenario-models-"></a>
+<img src="logo.svg" class="logo" alt=""><h1 id="epidemics-composable-epidemic-scenario-modelling-">epidemics: Composable epidemic scenario modelling <a class="anchor" aria-label="anchor" href="#epidemics-composable-epidemic-scenario-modelling-"></a>
 </h1>
 </div>
 <!-- badges: start -->
 
-<p><em>epidemics</em> is an R package that provides a convenient interface to a library of compartmental models that can help to model epidemic scenarios for directly transmitted respiratory infections such as influenza or Covid-19 as well haemorrhagic fevers such as Ebola virus disease.</p>
-<p>The models in <em>epidemics</em> implement methods outlined in Bjørnstad et al. (<a href="#ref-bjornstad2020a">2020a</a>) and Bjørnstad et al. (<a href="#ref-bjornstad2020">2020b</a>). The models in <em>epidemics</em> can help provide rough estimates of the course of epidemics, and the effectiveness of pharmaceutical and non-pharmaceutical interventions.</p>
+<p><em>epidemics</em> is an R package that provides modular representations of populations and public health response measures, allowing them to be combined with epidemiological model structures curated from the published literature, to conveniently compose and compare epidemic scenario models.</p>
+<p>The models in <em>epidemics</em> focus on directly transmitted infections, and implement methods outlined in Bjørnstad et al. (<a href="#ref-bjornstad2020a">2020a</a>) and Bjørnstad et al. (<a href="#ref-bjornstad2020">2020b</a>). The models in <em>epidemics</em> can help provide rough estimates of the course of epidemics, and the effectiveness of pharmaceutical and non-pharmaceutical interventions.</p>
 <p><em>epidemics</em> relies on <a href="https://gitlab.com/libeigen/eigen" class="external-link">Eigen</a> via <a href="https://cran.r-project.org/package=RcppEigen" class="external-link">{RcppEigen}</a>, and on <a href="https://www.boost.org/doc/libs/1_82_0/libs/numeric/odeint/doc/html/index.html" class="external-link">Boost Odeint</a> via <a href="https://cran.r-project.org/package=BH" class="external-link">{BH}</a>, and is developed at the <a href="https://www.lshtm.ac.uk/research/centres/centre-mathematical-modelling-infectious-diseases" class="external-link">Centre for the Mathematical Modelling of Infectious Diseases</a> at the London School of Hygiene and Tropical Medicine as part of the <a href="https://data.org/initiatives/epiverse/" class="external-link">Epiverse-TRACE initiative</a>.</p>
 <div class="section level2">
 <h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#installation"></a>
@@ -132,7 +119,7 @@ <h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#i
 <p>The current development version of <em>epidemics</em> can be installed from <a href="https://github.com/" class="external-link">GitHub</a> using the <em>pak</em> package.</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw">if</span><span class="op">(</span><span class="op">!</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://pak.r-lib.org/" class="external-link">"pak"</a></span><span class="op">)</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"pak"</span><span class="op">)</span></span>
-<span><span class="fu">pak</span><span class="fu">::</span><span class="fu"><a href="https://pak.r-lib.org/reference/pak.html" class="external-link">pak</a></span><span class="op">(</span><span class="st">"epiverse-trace/epidemics"</span><span class="op">)</span></span></code></pre></div>
+<span><span class="fu">pak</span><span class="fu">::</span><span class="fu"><a href="https://pak.r-lib.org/reference/pkg_install.html" class="external-link">pkg_install</a></span><span class="op">(</span><span class="st">"epiverse-trace/epidemics"</span><span class="op">)</span></span></code></pre></div>
 <div class="section level3">
 <h3 id="installation-notes">Installation Notes<a class="anchor" aria-label="anchor" href="#installation-notes"></a>
 </h3>
@@ -239,11 +226,11 @@ <h2 id="package-vignettes">Package vignettes<a class="anchor" aria-label="anchor
 <div class="section level2">
 <h2 id="package-models">Package models<a class="anchor" aria-label="anchor" href="#package-models"></a>
 </h2>
-<p><em>epidemics</em> currently provides three models:</p>
+<p><em>epidemics</em> provides a convenient interface to a library of compartmental models that can help to model epidemic scenarios for directly transmitted respiratory infections such as influenza or Covid-19 as well haemorrhagic fevers such as Ebola virus disease:</p>
 <ol style="list-style-type: decimal">
-<li><p>A deterministic SEIR-V model with susceptible, exposed, infectious, recovered, and vaccinated compartments (SEIR-V), allowing for heterogeneity in social contacts, the implementation of a group-specific non-pharmaceutical intervention that reduces social contacts, and a vaccination regime with group-specific start and end dates,</p></li>
-<li><p>The deterministic Vacamole model developed at <a href="https://www.rivm.nl/" class="external-link">RIVM, the Dutch Public Health Institute</a> for the Covid-19 pandemic, with a focus on scenario modelling for hospitalisation and vaccination (<a href="#ref-ainslie2022">Ainslie et al. 2022</a>),</p></li>
-<li><p>A stochastic, discrete-time, compartmental SEIR model suitable for modelling haemorrhagic fevers such as Ebola Virus Disease, including hospitalisation and hospital and funeral transmissions, adapted from Li et al. (<a href="#ref-li2019">2019</a>) and Getz and Dougherty (<a href="#ref-getz2018">2018</a>),</p></li>
+<li><p>A deterministic SEIR-V model with susceptible, exposed, infectious, recovered, and vaccinated compartments (SEIR-V), allowing for heterogeneity in social contacts, the implementation of a group-specific non-pharmaceutical intervention that reduces social contacts, and a vaccination regime with group-specific start and end dates;</p></li>
+<li><p>The deterministic Vacamole model developed at <a href="https://www.rivm.nl/" class="external-link">RIVM, the Dutch Public Health Institute</a> for the Covid-19 pandemic, with a focus on scenario modelling for hospitalisation and vaccination (<a href="#ref-ainslie2022">Ainslie et al. 2022</a>);</p></li>
+<li><p>A stochastic, discrete-time, compartmental SEIR model suitable for modelling haemorrhagic fevers such as Ebola Virus Disease, including hospitalisation and hospital and funeral transmissions, adapted from Li et al. (<a href="#ref-li2019">2019</a>) and Getz and Dougherty (<a href="#ref-getz2018">2018</a>);</p></li>
 <li><p>An initial implementation of a compartmental model for diphtheria in the context of internally displaced persons camps, including a reporting rate, hospitalisation rate, and delays in entering and leaving hospital, taken from Finger et al. (<a href="#ref-finger2019">2019</a>).</p></li>
 </ol>
 <p>More models are planned to be added in the near future. Please get in touch if you would like to see your model added to the <em>epidemics</em> model library — we are happy to help with translating it into our framework, with a special focus on making the model applicable to LMIC settings.</p>
@@ -267,7 +254,7 @@ <h2 id="help">Help<a class="anchor" aria-label="anchor" href="#help"></a>
 <div class="section level2">
 <h2 id="contribute">Contribute<a class="anchor" aria-label="anchor" href="#contribute"></a>
 </h2>
-<p>Contributions to <em>epidemics</em> are welcomed. Please follow the <a href="https://github.com/epiverse-trace/epidemics/blob/main/.github/CONTRIBUTING.md" class="external-link">package contributing guide</a>.</p>
+<p>Contributions to <em>epidemics</em> are welcomed via <a href="https://github.com/epiverse-trace/epidemics/pulls" class="external-link">pull requests</a>.</p>
 </div>
 <div class="section level2">
 <h2 id="code-of-conduct">Code of conduct<a class="anchor" aria-label="anchor" href="#code-of-conduct"></a>
@@ -343,29 +330,18 @@ <h2 data-toc-skip>Developers</h2>
 </ul>
 </div>
 
-<div class="dev-status">
-<h2 data-toc-skip>Dev status</h2>
-<ul class="list-unstyled">
-<li><a href="https://opensource.org/license/mit/" class="external-link"><img src="https://img.shields.io/badge/License-MIT-blue.svg" alt="License: MIT"></a></li>
-<li><a href="https://github.com/epiverse-trace/epidemics/actions/workflows/R-CMD-check.yaml" class="external-link"><img src="https://github.com/epiverse-trace/epidemics/actions/workflows/R-CMD-check.yaml/badge.svg" alt="R-CMD-check"></a></li>
-<li><a href="https://app.codecov.io/gh/epiverse-trace/epidemics?branch=main" class="external-link"><img src="https://codecov.io/gh/epiverse-trace/epidemics/branch/main/graph/badge.svg" alt="Codecov test coverage"></a></li>
-<li><a href="https://www.repostatus.org/#wip" class="external-link"><img src="https://www.repostatus.org/badges/latest/wip.svg" alt="Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public."></a></li>
-<li><a href="https://CRAN.R-project.org/package=epidemics" class="external-link"><img src="https://www.r-pkg.org/badges/version/epidemics" alt="CRAN status"></a></li>
-</ul>
-</div>
+
 
   </aside>
 </div>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p>
-<p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p>
-<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer>
diff --git a/news/index.html b/news/index.html
index 40c5daca..86b47401 100644
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@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Changelog • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Changelog"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Changelog • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Changelog"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="active nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -82,7 +81,56 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
     </div>
 
     <div class="section level2">
-<h2 class="pkg-version" data-toc-text="development version" id="epidemics-development-version">epidemics (development version)<a class="anchor" aria-label="anchor" href="#epidemics-development-version"></a></h2>
+<h2 class="pkg-version" data-toc-text="0.3.0" id="epidemics-030">epidemics 0.3.0<a class="anchor" aria-label="anchor" href="#epidemics-030"></a></h2>
+<p>This is a minor version release of <em>epidemics</em> is the end point of this project that allows <a href="https://github.com/orgs/epiverse-trace/projects/36" class="external-link">vector inputs to the Ebola model</a> (<a href="https://github.com/epiverse-trace/epidemics/issues/211" class="external-link">#211</a>, <a href="https://github.com/epiverse-trace/epidemics/issues/212" class="external-link">#212</a>).</p>
+<div class="section level3">
+<h3 id="breaking-changes-0-3-0">Breaking changes<a class="anchor" aria-label="anchor" href="#breaking-changes-0-3-0"></a></h3>
+<ol style="list-style-type: decimal"><li><p>The Ebola model run with a single parameter set and a single set of composable (i.e., functionality before this vignette) now runs 100 replicates of the model by default, and the output returns the additional column name “replicate” (<a href="https://github.com/epiverse-trace/epidemics/issues/211" class="external-link">#211</a>).</p></li>
+<li><p>The Ebola model disallows rate interventions on, and time-dependence for, the ‘infectiousness rate’ and the ‘removal rate’ as these control the number of epidemiological sub-compartments and cannot be allowed to vary during run time.</p></li>
+<li><p>The default behaviour of <code><a href="../reference/epidemic_size.html">epidemic_size()</a></code> is to exclude the ‘dead’ compartment from epidemic size calculations; this has changed from including it by default, as most models don’t have a ‘dead’ compartment (<a href="https://github.com/epiverse-trace/epidemics/issues/212" class="external-link">#212</a>);</p></li>
+</ol></div>
+<div class="section level3">
+<h3 id="model-functions-0-3-0">Model functions<a class="anchor" aria-label="anchor" href="#model-functions-0-3-0"></a></h3>
+<ol style="list-style-type: decimal"><li><p>The Ebola model code has been split into a two-level structure similar to the ODE models. The user facing function <code><a href="../reference/model_ebola.html">model_ebola()</a></code> now handles input checking and some cross-checking, and makes combinations of infection parameter sets and scenarios, and handles output. The internal model function <code><a href="../reference/dot-model_ebola_internal.html">.model_ebola_internal()</a></code> is now called over combinations of parameters and scenario elements (<a href="https://github.com/epiverse-trace/epidemics/issues/211" class="external-link">#211</a>).</p></li>
+<li><p><code><a href="../reference/dot-model_ebola_internal.html">.model_ebola_internal()</a></code> relies on functionality from the {withr} package to preserve the random number seed between parameter set-scenario combinations, and to ensure that each <span class="math inline"><em>i</em></span>-th replicate of each scenario starts with the same random number stream.</p></li>
+</ol></div>
+<div class="section level3">
+<h3 id="model-structures-0-3-0">Model structures<a class="anchor" aria-label="anchor" href="#model-structures-0-3-0"></a></h3>
+</div>
+<div class="section level3">
+<h3 id="classes-0-3-0">Classes<a class="anchor" aria-label="anchor" href="#classes-0-3-0"></a></h3>
+<ol style="list-style-type: decimal"><li><p>The <code>&lt;intervention&gt;</code> helper functions <code><a href="../reference/cumulative_rate_intervention.html">.cumulative_rate_intervention()</a></code> and <code><a href="../reference/dot-intervention_on_rates.html">.intervention_on_rates()</a></code> have been renamed to include the prefix <code>.</code> to indicate they are internal functions (<a href="https://github.com/epiverse-trace/epidemics/issues/211" class="external-link">#211</a>).</p></li>
+<li><p>Small updates to <code><a href="../reference/cross_checking_inputs.html">.cross_check_intervention()</a></code> to better handle intervention sets where contacts interventions are optional (the Ebola model) (<a href="https://github.com/epiverse-trace/epidemics/issues/211" class="external-link">#211</a>).</p></li>
+</ol></div>
+<div class="section level3">
+<h3 id="helper-functions-0-3-0">Helper functions<a class="anchor" aria-label="anchor" href="#helper-functions-0-3-0"></a></h3>
+<ol style="list-style-type: decimal"><li><p><code><a href="../reference/prepare_ebola_args.html">.check_prepare_args_ebola()</a></code> is a new argument cross-checking and preparation function for the Ebola model (<a href="https://github.com/epiverse-trace/epidemics/issues/212" class="external-link">#212</a>).</p></li>
+<li>
+<p><code><a href="../reference/epidemic_size.html">epidemic_size()</a></code> is substantially updated (<a href="https://github.com/epiverse-trace/epidemics/issues/212" class="external-link">#212</a>):</p>
+<ul><li><p>Added option for <code>time</code> which returns epidemic size at a specific time point, overriding the <code>stage</code> argument, defaults to <code>NULL</code> as the intended use of the function is to return the final size;</p></li>
+<li><p>Added option to return epidemic sizes at multiple stages or time points (<code>stage</code> and <code>time</code> can be vectors);</p></li>
+<li><p>Added option to simplify the output to a vector, which is <code>TRUE</code> by default to keep consistency with previous functionality;</p></li>
+<li><p>Added functionality to handle replicates from the Ebola model;</p></li>
+<li><p>Added tests for new functionality.</p></li>
+</ul></li>
+<li><p>Added function <code><a href="../reference/output_to_df.html">.output_to_df_ebola()</a></code> to handle output from the Ebola model (<a href="https://github.com/epiverse-trace/epidemics/issues/211" class="external-link">#211</a>).</p></li>
+</ol></div>
+<div class="section level3">
+<h3 id="documentation-0-3-0">Documentation<a class="anchor" aria-label="anchor" href="#documentation-0-3-0"></a></h3>
+<ol style="list-style-type: decimal"><li><p>Updates to the Ebola model vignette showing new functionality.</p></li>
+<li><p>Updates to the design decisions vignette documenting decisions taken for the Ebola model.</p></li>
+<li><p>Updated sections on handling social contacts data in the ‘Getting started’ and ‘Modelling interventions on social contacts’ vignettes, added reference to Wallinga et al. 2006 <a href="https://doi.org/10.1093/aje/kwj317" class="external-link uri">https://doi.org/10.1093/aje/kwj317</a> (<a href="https://github.com/epiverse-trace/epidemics/issues/217" class="external-link">#217</a>).</p></li>
+<li><p>Enables auto development mode for the website in <code>_pkgdown.yml</code>, and manually specify Bootstrap version 5 (<a href="https://github.com/epiverse-trace/epidemics/issues/213" class="external-link">#213</a>).</p></li>
+<li><p>Updates WORDLIST.</p></li>
+<li><p>Updates installation instructions in the Readme; link under ‘Contribute’ correctly directs to pull requests page (<a href="https://github.com/epiverse-trace/epidemics/issues/217" class="external-link">#217</a>).</p></li>
+</ol></div>
+<div class="section level3">
+<h3 id="package-0-3-0">Package<a class="anchor" aria-label="anchor" href="#package-0-3-0"></a></h3>
+<ol style="list-style-type: decimal"><li><p>{withr} moved from Suggests to Imports due to use in seed management.</p></li>
+<li><p>Added <a href="https://github.com/bahadzie" class="external-link">@bahadzie</a> as contributor and <a href="https://github.com/jamesmbaazam" class="external-link">@jamesmbaazam</a> as reviewer.</p></li>
+<li><p>Updates to the GitHub Actions workflows and linter config file.</p></li>
+<li><p>Updates the license year to 2024 in all files with the year.</p></li>
+</ol></div>
 </div>
     <div class="section level2">
 <h2 class="pkg-version" data-toc-text="0.2.0" id="epidemics-020">epidemics 0.2.0<a class="anchor" aria-label="anchor" href="#epidemics-020"></a></h2>
@@ -116,7 +164,7 @@ <h3 id="helper-functions-0-2-0">Helper functions<a class="anchor" aria-label="an
 <ol style="list-style-type: decimal"><li><p>Internal helper functions <code>.check_args_model_*()</code> and <code>.prepare_args_model_*()</code> have been combined into single functions <code>.check_prepare_args_*()</code> that are called both for their output and for input checking side effects.</p></li>
 <li><p>The new internal functions <code><a href="../reference/dot-prepare_population.html">.prepare_population()</a></code>, <code><a href="../reference/cross_checking_inputs.html">.cross_check_intervention()</a></code>, <code><a href="../reference/cross_checking_inputs.html">.cross_check_vaccination()</a></code>, <code><a href="../reference/cross_checking_inputs.html">.cross_check_timedep()</a></code>, and <code><a href="../reference/cross_checking_inputs.html">.cross_check_popchange()</a></code> check and prepare a model population and check other inputs for compatibility with it. These are used in <code>.check_prepare_args_*()</code>.</p></li>
 <li><p>New internal functions have been added to check and recycle lists of vectors; original implementations by <a href="https://github.com/TimTaylor" class="external-link">@TimTaylor</a>.</p></li>
-<li><p><code>output_to_df()</code> is renamed to <code><a href="../reference/dot-output_to_df.html">.output_to_df()</a></code>.</p></li>
+<li><p><code><a href="../reference/output_to_df.html">output_to_df()</a></code> is renamed to <code><a href="../reference/output_to_df.html">.output_to_df()</a></code>.</p></li>
 </ol></div>
 <div class="section level3">
 <h3 id="documentation-0-2-0">Documentation<a class="anchor" aria-label="anchor" href="#documentation-0-2-0"></a></h3>
@@ -204,11 +252,11 @@ <h3 id="miscellaneous-0-1-0">Miscellaneous<a class="anchor" aria-label="anchor"
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/pkgdown.js b/pkgdown.js
index 5fccd9c0..9bd6621e 100644
--- a/pkgdown.js
+++ b/pkgdown.js
@@ -30,10 +30,10 @@
   /* Clipboard --------------------------*/
 
   function changeTooltipMessage(element, msg) {
-    var tooltipOriginalTitle=element.getAttribute('data-original-title');
-    element.setAttribute('data-original-title', msg);
+    var tooltipOriginalTitle=element.getAttribute('data-bs-original-title');
+    element.setAttribute('data-bs-original-title', msg);
     $(element).tooltip('show');
-    element.setAttribute('data-original-title', tooltipOriginalTitle);
+    element.setAttribute('data-bs-original-title', tooltipOriginalTitle);
   }
 
   if(ClipboardJS.isSupported()) {
@@ -60,7 +60,7 @@
         e.clearSelection();
       });
 
-      clipboard.on('error', function() {
+      clipboard.on('error', function(e) {
         changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy');
       });
 
diff --git a/pkgdown.yml b/pkgdown.yml
index 40b16cc2..133b2e6b 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -1,6 +1,6 @@
 pandoc: 3.1.11
-pkgdown: 2.0.7
-pkgdown_sha: ~
+pkgdown: 2.0.9.9000
+pkgdown_sha: 9850459324cc6ec144931cdd30b11983760e5b8b
 articles:
   design-principles: design-principles.html
   epidemics: epidemics.html
@@ -14,7 +14,7 @@ articles:
   modelling_scenarios: modelling_scenarios.html
   modelling_time_dependence: modelling_time_dependence.html
   modelling_vaccination: modelling_vaccination.html
-last_built: 2024-03-22T16:14Z
+last_built: 2024-04-23T13:07Z
 urls:
   reference: https://epiverse-trace.github.io/epidemics/reference
   article: https://epiverse-trace.github.io/epidemics/articles
diff --git a/reference/as.intervention.html b/reference/as.intervention.html
index 64ca396c..a7c37b21 100644
--- a/reference/as.intervention.html
+++ b/reference/as.intervention.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Convert a list to a intervention object"><title>Convert a list to a intervention object — as.intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Convert a list to a intervention object — as.intervention"><meta property="og:description" content="Convert a list to a intervention object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Convert a list to a intervention object"><title>Convert a list to a intervention object — as.intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Convert a list to a intervention object — as.intervention"><meta property="og:description" content="Convert a list to a intervention object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -144,11 +143,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/as.vaccination.html b/reference/as.vaccination.html
index d7b3d6a2..71d9a837 100644
--- a/reference/as.vaccination.html
+++ b/reference/as.vaccination.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Convert a list to a vaccination object"><title>Convert a list to a vaccination object — as.vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Convert a list to a vaccination object — as.vaccination"><meta property="og:description" content="Convert a list to a vaccination object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Convert a list to a vaccination object"><title>Convert a list to a vaccination object — as.vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Convert a list to a vaccination object — as.vaccination"><meta property="og:description" content="Convert a list to a vaccination object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -138,11 +137,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/assert_intervention.html b/reference/assert_intervention.html
index 88c919fc..6a18ec93 100644
--- a/reference/assert_intervention.html
+++ b/reference/assert_intervention.html
@@ -2,7 +2,7 @@
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Assert that objects of the intervention class have the properties expected
 by an epidemic model. See intervention() and specific model functions
 to check the intervention properties required by each model. This
-function is for internal use in argument checking functions."><title>Assert properties of a intervention object — assert_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assert properties of a intervention object — assert_intervention"><meta property="og:description" content="Assert that objects of the intervention class have the properties expected
+function is for internal use in argument checking functions."><title>Assert properties of a intervention object — assert_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assert properties of a intervention object — assert_intervention"><meta property="og:description" content="Assert that objects of the intervention class have the properties expected
 by an epidemic model. See intervention() and specific model functions
 to check the intervention properties required by each model. This
 function is for internal use in argument checking functions."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -18,12 +18,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -67,10 +67,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -133,11 +132,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/assert_population.html b/reference/assert_population.html
index ca83a286..4a73152a 100644
--- a/reference/assert_population.html
+++ b/reference/assert_population.html
@@ -2,7 +2,7 @@
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Assert that objects of the population class have the parameters expected by
 an epidemic model. See population() and specific epidemic functions
 to check the population parameters required by each model. This
-function is for internal use in argument checking functions."><title>Assert properties of a population object — assert_population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assert properties of a population object — assert_population"><meta property="og:description" content="Assert that objects of the population class have the parameters expected by
+function is for internal use in argument checking functions."><title>Assert properties of a population object — assert_population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assert properties of a population object — assert_population"><meta property="og:description" content="Assert that objects of the population class have the parameters expected by
 an epidemic model. See population() and specific epidemic functions
 to check the population parameters required by each model. This
 function is for internal use in argument checking functions."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -18,12 +18,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -67,10 +67,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -131,11 +130,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/assert_vaccination.html b/reference/assert_vaccination.html
index 8f713106..676cd247 100644
--- a/reference/assert_vaccination.html
+++ b/reference/assert_vaccination.html
@@ -2,7 +2,7 @@
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Assert that objects of the vaccination class have the parameters expected
 by an epidemic model. See vaccination() and specific epidemic functions
 to check the vaccination properties required by each model. This
-function is for internal use in argument checking functions."><title>Assert properties of a vaccination object — assert_vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assert properties of a vaccination object — assert_vaccination"><meta property="og:description" content="Assert that objects of the vaccination class have the parameters expected
+function is for internal use in argument checking functions."><title>Assert properties of a vaccination object — assert_vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Assert properties of a vaccination object — assert_vaccination"><meta property="og:description" content="Assert that objects of the vaccination class have the parameters expected
 by an epidemic model. See vaccination() and specific epidemic functions
 to check the vaccination properties required by each model. This
 function is for internal use in argument checking functions."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -18,12 +18,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -67,10 +67,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -130,11 +129,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/cross_checking_inputs.html b/reference/cross_checking_inputs.html
index 62191b83..baf5d5f7 100644
--- a/reference/cross_checking_inputs.html
+++ b/reference/cross_checking_inputs.html
@@ -2,7 +2,7 @@
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Check model elements for compatibility with the population in an epidemic
 model, returning compatible dummy values when model elements are not applied,
 and erroring appropriately when model elements are not compatible with the
-population characteristics."><title>Cross-check model elements — cross_checking_inputs • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Cross-check model elements — cross_checking_inputs"><meta property="og:description" content="Check model elements for compatibility with the population in an epidemic
+population characteristics."><title>Cross-check model elements — cross_checking_inputs • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Cross-check model elements — cross_checking_inputs"><meta property="og:description" content="Check model elements for compatibility with the population in an epidemic
 model, returning compatible dummy values when model elements are not applied,
 and erroring appropriately when model elements are not compatible with the
 population characteristics."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -18,12 +18,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -67,10 +67,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -162,11 +161,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/cumulative_contacts_intervention.html b/reference/cumulative_contacts_intervention.html
index c2855588..619b0ad4 100644
--- a/reference/cumulative_contacts_intervention.html
+++ b/reference/cumulative_contacts_intervention.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Calculate the Cumulative Effect of Interventions on Social Contacts
-Scale a Contact Matrix by all Active Interventions on Social Contacts"><title>Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention"><meta property="og:description" content="Calculate the Cumulative Effect of Interventions on Social Contacts
+Scale a Contact Matrix by all Active Interventions on Social Contacts"><title>Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention"><meta property="og:description" content="Calculate the Cumulative Effect of Interventions on Social Contacts
 Scale a Contact Matrix by all Active Interventions on Social Contacts"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@@ -14,12 +14,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -63,10 +63,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -140,11 +139,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/cumulative_rate_intervention.html b/reference/cumulative_rate_intervention.html
index 2ab43dac..276e7df2 100644
--- a/reference/cumulative_rate_intervention.html
+++ b/reference/cumulative_rate_intervention.html
@@ -1,5 +1,5 @@
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@@ -12,12 +12,12 @@
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-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
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@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
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-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
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@@ -88,7 +87,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">cumulative_rate_intervention</span><span class="op">(</span><span class="va">t</span>, <span class="va">time_begin</span>, <span class="va">time_end</span>, <span class="va">reduction</span><span class="op">)</span></span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">.cumulative_rate_intervention</span><span class="op">(</span><span class="va">t</span>, <span class="va">time_begin</span>, <span class="va">time_end</span>, <span class="va">reduction</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
@@ -118,7 +117,7 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
     
 
-<p><code>cumulative_rate_intervention()</code> returns a number of the proportion
+<p><code>.cumulative_rate_intervention()</code> returns a number of the proportion
 reduction in a model rate parameter.</p>
 
 
@@ -131,11 +130,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
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-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
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+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/reference/dot-intervention_on_rates.html b/reference/dot-intervention_on_rates.html
new file mode 100644
index 00000000..abdb98ab
--- /dev/null
+++ b/reference/dot-intervention_on_rates.html
@@ -0,0 +1,140 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Apply interventions to rate parameters"><title>Apply interventions to rate parameters — .intervention_on_rates • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Apply interventions to rate parameters — .intervention_on_rates"><meta property="og:description" content="Apply interventions to rate parameters"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+    <a class="navbar-brand me-2" href="../index.html">epidemics</a>
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+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
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+      <ul class="navbar-nav me-auto"><li class="nav-item">
+  <a class="nav-link" href="../articles/epidemics.html">Get started</a>
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+  <a class="nav-link" href="../reference/index.html">Reference</a>
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+<li class="nav-item dropdown">
+  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
+  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
+    <h6 class="dropdown-header" data-toc-skip>Modelling interventions</h6>
+    <a class="dropdown-item" href="../articles/modelling_interventions.html">Getting started with modelling interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_multiple_interventions.html">Modelling overlapping and sequential interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_rate_interventions.html">Modelling other interventions that change transmission rates</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling vaccination</h6>
+    <a class="dropdown-item" href="../articles/modelling_vaccination.html">Modelling the effect of a vaccination campaign</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling seasonality</h6>
+    <a class="dropdown-item" href="../articles/modelling_time_dependence.html">Modelling time-dependence and seasonality in transmission dynamics</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Other modelling vignettes</h6>
+    <a class="dropdown-item" href="../articles/modelling_scenarios.html">Modelling parameter uncertainty and epidemic scenarios</a>
+    <a class="dropdown-item" href="../articles/finalsize_comparison.html">Reducing parameters required for final size estimation</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Guides to library models</h6>
+    <a class="dropdown-item" href="../articles/model_vacamole.html">Modelling leaky vaccination and hospitalisation outcomes with Vacamole</a>
+    <a class="dropdown-item" href="../articles/model_ebola.html">Modelling responses to a stochastic Ebola virus epidemic</a>
+    <a class="dropdown-item" href="../articles/model_diphtheria.html">Modelling a diphtheria outbreak in a humanitarian camp setting</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
+    <a class="dropdown-item" href="../articles/design-principles.html">Design Principles for epidemics</a>
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+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.svg" class="logo" alt=""><h1>Apply interventions to rate parameters</h1>
+      <small class="dont-index">Source: <a href="https://github.com/epiverse-trace/epidemics/blob/HEAD/R/intervention.R" class="external-link"><code>R/intervention.R</code></a></small>
+      <div class="d-none name"><code>dot-intervention_on_rates.Rd</code></div>
+    </div>
+
+    <div class="ref-description section level2">
+    <p>Apply interventions to rate parameters</p>
+    </div>
+
+    <div class="section level2">
+    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">.intervention_on_rates</span><span class="op">(</span><span class="va">t</span>, <span class="va">interventions</span>, <span class="va">parameters</span><span class="op">)</span></span></code></pre></div>
+    </div>
+
+    <div class="section level2">
+    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
+    <dl><dt>t</dt>
+<dd><p>A single number for the simulation time.</p></dd>
+
+
+<dt>interventions</dt>
+<dd><p>A named list of <code>list</code>-like objects that each have at
+least the three members <code>"time_begin"</code>, <code>"time_end"</code>, and <code>"reduction"</code>.
+These are used to calculate the effect on each of the named parameters in the
+simulation.</p></dd>
+
+
+<dt>parameters</dt>
+<dd><p>A named list of numeric parameters affected by
+<code>interventions</code>.
+This represents the model parameters, such as the transmission rate,
+\(\beta\), or the recovery rate, \(\gamma\).</p></dd>
+
+</dl></div>
+    <div class="section level2">
+    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
+    
+
+<p>A named list of the same length as <code>parameters</code>, with the same names.
+These parameters can then be used in a timestep of an ODE model.</p>
+    </div>
+
+  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+    </nav></aside></div>
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
+</div>
+
+    </footer></div>
+
+  
+
+  
+
+  </body></html>
+
diff --git a/reference/dot-model_default_cpp.html b/reference/dot-model_default_cpp.html
index 01336509..abd1b22a 100644
--- a/reference/dot-model_default_cpp.html
+++ b/reference/dot-model_default_cpp.html
@@ -2,7 +2,7 @@
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="A compartmental model with an optional non-pharmaceutical
 intervention and an optional vaccination regime.
 This function is intended to only be called internally from
-model_default_cpp()."><title>Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp"><meta property="og:description" content="A compartmental model with an optional non-pharmaceutical
+model_default_cpp()."><title>Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp"><meta property="og:description" content="A compartmental model with an optional non-pharmaceutical
 intervention and an optional vaccination regime.
 This function is intended to only be called internally from
 model_default_cpp()."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
@@ -18,12 +18,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -67,10 +67,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -199,11 +198,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/dot-model_diphtheria_cpp.html b/reference/dot-model_diphtheria_cpp.html
index 0b3d669e..64394236 100644
--- a/reference/dot-model_diphtheria_cpp.html
+++ b/reference/dot-model_diphtheria_cpp.html
@@ -3,7 +3,7 @@
 account for case reporting rate, delays in seeking hospitalisation, and the
 time spent in the hospitalised compartment.
 This function is intended to only be called internally from
-model_diphtheria_cpp()."><title>Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp"><meta property="og:description" content="A compartmental model for diphtheria with parameters to help
+model_diphtheria_cpp()."><title>Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp"><meta property="og:description" content="A compartmental model for diphtheria with parameters to help
 account for case reporting rate, delays in seeking hospitalisation, and the
 time spent in the hospitalised compartment.
 This function is intended to only be called internally from
@@ -20,12 +20,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -69,10 +69,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
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     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -197,11 +196,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
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 </div>
 
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diff --git a/reference/dot-model_ebola_internal.html b/reference/dot-model_ebola_internal.html
new file mode 100644
index 00000000..f31a4e7e
--- /dev/null
+++ b/reference/dot-model_ebola_internal.html
@@ -0,0 +1,219 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Internal code for the Ebola model"><title>Internal code for the Ebola model — .model_ebola_internal • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Internal code for the Ebola model — .model_ebola_internal"><meta property="og:description" content="Internal code for the Ebola model"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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+    
+    <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
+    <a class="navbar-brand me-2" href="../index.html">epidemics</a>
+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
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+  <a class="nav-link" href="../articles/epidemics.html">Get started</a>
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+  <a class="nav-link" href="../reference/index.html">Reference</a>
+</li>
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+  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
+  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
+    <h6 class="dropdown-header" data-toc-skip>Modelling interventions</h6>
+    <a class="dropdown-item" href="../articles/modelling_interventions.html">Getting started with modelling interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_multiple_interventions.html">Modelling overlapping and sequential interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_rate_interventions.html">Modelling other interventions that change transmission rates</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling vaccination</h6>
+    <a class="dropdown-item" href="../articles/modelling_vaccination.html">Modelling the effect of a vaccination campaign</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling seasonality</h6>
+    <a class="dropdown-item" href="../articles/modelling_time_dependence.html">Modelling time-dependence and seasonality in transmission dynamics</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Other modelling vignettes</h6>
+    <a class="dropdown-item" href="../articles/modelling_scenarios.html">Modelling parameter uncertainty and epidemic scenarios</a>
+    <a class="dropdown-item" href="../articles/finalsize_comparison.html">Reducing parameters required for final size estimation</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Guides to library models</h6>
+    <a class="dropdown-item" href="../articles/model_vacamole.html">Modelling leaky vaccination and hospitalisation outcomes with Vacamole</a>
+    <a class="dropdown-item" href="../articles/model_ebola.html">Modelling responses to a stochastic Ebola virus epidemic</a>
+    <a class="dropdown-item" href="../articles/model_diphtheria.html">Modelling a diphtheria outbreak in a humanitarian camp setting</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
+    <a class="dropdown-item" href="../articles/design-principles.html">Design Principles for epidemics</a>
+  </div>
+</li>
+<li class="nav-item">
+  <a class="nav-link" href="../news/index.html">Changelog</a>
+</li>
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
+  <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
+    <span class="fab fa fab fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul></div>
+
+    
+  </div>
+</nav><div class="container template-reference-topic">
+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.svg" class="logo" alt=""><h1>Internal code for the Ebola model</h1>
+      <small class="dont-index">Source: <a href="https://github.com/epiverse-trace/epidemics/blob/HEAD/R/model_ebola.R" class="external-link"><code>R/model_ebola.R</code></a></small>
+      <div class="d-none name"><code>dot-model_ebola_internal.Rd</code></div>
+    </div>
+
+    <div class="ref-description section level2">
+    <p>Internal code for the Ebola model</p>
+    </div>
+
+    <div class="section level2">
+    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">.model_ebola_internal</span><span class="op">(</span></span>
+<span>  <span class="va">initial_state</span>,</span>
+<span>  <span class="va">erlang_subcompartments</span>,</span>
+<span>  <span class="va">transmission_rate</span>,</span>
+<span>  <span class="va">infectiousness_rate</span>,</span>
+<span>  <span class="va">removal_rate</span>,</span>
+<span>  <span class="va">prop_community</span>,</span>
+<span>  <span class="va">etu_risk</span>,</span>
+<span>  <span class="va">funeral_risk</span>,</span>
+<span>  <span class="va">intervention</span>,</span>
+<span>  <span class="va">time_dependence</span>,</span>
+<span>  <span class="va">time_end</span>,</span>
+<span>  <span class="va">replicates</span>,</span>
+<span>  <span class="va">local_seeds</span></span>
+<span><span class="op">)</span></span></code></pre></div>
+    </div>
+
+    <div class="section level2">
+    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
+    <dl><dt>erlang_subcompartments</dt>
+<dd><p>A numeric, integer-like vector for the number
+of Erlang sub-compartments assumed for the exposed, infectious, and
+hospitalised compartments. Defaults to 2.</p></dd>
+
+
+<dt>transmission_rate</dt>
+<dd><p>A numeric vector for the rate at which individuals
+move from the susceptible to the exposed compartment upon contact with an
+infectious individual. Often denoted as \(\beta\), with
+\(\beta = R_0 / \text{infectious period}\).
+See <strong>Details</strong> for default values.</p></dd>
+
+
+<dt>infectiousness_rate</dt>
+<dd><p>A numeric vector for the rate at which individuals
+move from the exposed to the infectious compartment. Often denoted as
+\(\sigma\), with \(\sigma = 1.0 / \text{pre-infectious period}\).
+This value does not depend upon the number of infectious individuals in the
+population.
+See <strong>Details</strong> for default values.</p></dd>
+
+
+<dt>removal_rate</dt>
+<dd><p>A numeric vector for the rate at which infectious
+individuals transition from the infectious or hospitalised compartments to
+the funeral or removed compartments.
+This model does not distinguish between recoveries and deaths.
+Denoted in Getz and Dougherty as \(\gamma^I\) (see <strong>Details</strong>).</p></dd>
+
+
+<dt>prop_community</dt>
+<dd><p>A numeric vector for the proportion of infectious
+individuals who remain in the community and are not hospitalised for
+treatment. Defaults to 0.9.</p></dd>
+
+
+<dt>etu_risk</dt>
+<dd><p>A numeric vector for the relative risk of onward transmission
+of EVD from hospitalised individuals, with values between 0.0 and 1.0, where
+0.0 indicates that hospitalisation completely prevents onward transmission,
+and 1.0 indicates that hospitalisation does not prevent onward transmission
+at all; values are relative to the baseline transmission rate \(\beta\).
+Defaults to 0.7.</p></dd>
+
+
+<dt>funeral_risk</dt>
+<dd><p>A numeric vector for the relative risk of onward
+transmission of EVD from funerals of individuals who died with EVD.
+Must be between 0.0 and 1.0, where 0.0 indicates that there is no onward
+transmission, and 1.0 indicates that funeral transmission is equivalent to
+the baseline transmission rate in the community \(\beta\).
+Defaults to 0.5.</p></dd>
+
+
+<dt>intervention</dt>
+<dd><p>An optional named list of <code>&lt;rate_intervention&gt;</code> objects
+representing optional pharmaceutical or non-pharmaceutical interventions
+applied to the model parameters listed above. May also be a list of such
+lists, in which case each set of interventions is treated as a separate
+scenario. See <strong>Details</strong> below.</p></dd>
+
+
+<dt>time_dependence</dt>
+<dd><p>An optional named list where each element is a
+function with the first two arguments being the current simulation <code>time</code>,
+and <code>x</code>, a value that is dependent on <code>time</code>
+(<code>x</code> represents a model parameter).
+List names must correspond to model parameters modified by the function.
+Alternatively, may be a list of such lists, in which case each set of
+functions is treated as a distinct scenario.
+See <strong>Details</strong> for more information, as well as the vignette on time-
+dependence <code>vignette("time_dependence", package = "epidemics")</code>.</p></dd>
+
+
+<dt>time_end</dt>
+<dd><p>A numeric, integer-like vector for the maximum number of</p></dd>
+
+
+<dt>replicates</dt>
+<dd><p>A single number for replicates to run. Defaults to 100.
+timesteps over which to run the model, in days. Defaults to 100 days.</p></dd>
+
+</dl></div>
+    <div class="section level2">
+    <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
+    <p><strong>NOTE</strong> that all arguments to this internal function must be scalars for
+infection parameters or single intervention or time-dependence sets for
+composable elements.</p>
+    </div>
+
+  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+    </nav></aside></div>
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
+</div>
+
+    </footer></div>
+
+  
+
+  
+
+  </body></html>
+
diff --git a/reference/dot-model_vacamole_cpp.html b/reference/dot-model_vacamole_cpp.html
index be4e05c8..4c80bda7 100644
--- a/reference/dot-model_vacamole_cpp.html
+++ b/reference/dot-model_vacamole_cpp.html
@@ -7,7 +7,7 @@
 Manuscript describing the model and its application:
 https://doi.org/10.2807/1560-7917.ES.2022.27.44.2101090
 This function is intended to only be called internally from
-model_vacamole_cpp()."><title>Run the RIVM Vacamole model — .model_vacamole_cpp • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Run the RIVM Vacamole model — .model_vacamole_cpp"><meta property="og:description" content="Vacamole is a deterministic, compartmental epidemic model built
+model_vacamole_cpp()."><title>Run the RIVM Vacamole model — .model_vacamole_cpp • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Run the RIVM Vacamole model — .model_vacamole_cpp"><meta property="og:description" content="Vacamole is a deterministic, compartmental epidemic model built
 by Kylie Ainslie and others at RIVM, the Dutch Public Health Institute for
 the Covid-19 pandemic, with a focus on scenario modelling for
 hospitalisation and vaccination.
@@ -28,12 +28,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -77,10 +77,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -246,11 +245,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/dot-ode_model_default.html b/reference/dot-ode_model_default.html
index b8f4d3cc..15cd342d 100644
--- a/reference/dot-ode_model_default.html
+++ b/reference/dot-ode_model_default.html
@@ -1,7 +1,7 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Provides the ODEs for the default SEIR-V model in a format that
 is suitable for passing to deSolve::lsoda().
-See model_default() for a list of required parameters."><title>Ordinary Differential Equations for the Default Model — .ode_model_default • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Ordinary Differential Equations for the Default Model — .ode_model_default"><meta property="og:description" content="Provides the ODEs for the default SEIR-V model in a format that
+See model_default() for a list of required parameters."><title>Ordinary Differential Equations for the Default Model — .ode_model_default • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Ordinary Differential Equations for the Default Model — .ode_model_default"><meta property="og:description" content="Provides the ODEs for the default SEIR-V model in a format that
 is suitable for passing to deSolve::lsoda().
 See model_default() for a list of required parameters."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -16,12 +16,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -65,10 +65,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -88,7 +87,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="ref-description section level2">
     <p>Provides the ODEs for the default SEIR-V model in a format that
-is suitable for passing to <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code>.
+is suitable for passing to <code>deSolve::lsoda()</code>.
 See <code><a href="model_default.html">model_default()</a></code> for a list of required parameters.</p>
     </div>
 
@@ -125,11 +124,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/dot-ode_model_vacamole.html b/reference/dot-ode_model_vacamole.html
index d1836a6d..65846921 100644
--- a/reference/dot-ode_model_vacamole.html
+++ b/reference/dot-ode_model_vacamole.html
@@ -1,7 +1,7 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Provides the ODEs for the RIVM Vacamole model in a format that
 is suitable for passing to deSolve::lsoda().
-See model_vacamole() for a list of required parameters."><title>Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole"><meta property="og:description" content="Provides the ODEs for the RIVM Vacamole model in a format that
+See model_vacamole() for a list of required parameters."><title>Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole"><meta property="og:description" content="Provides the ODEs for the RIVM Vacamole model in a format that
 is suitable for passing to deSolve::lsoda().
 See model_vacamole() for a list of required parameters."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -16,12 +16,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -65,10 +65,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -88,7 +87,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="ref-description section level2">
     <p>Provides the ODEs for the RIVM Vacamole model in a format that
-is suitable for passing to <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code>.
+is suitable for passing to <code>deSolve::lsoda()</code>.
 See <code><a href="model_vacamole.html">model_vacamole()</a></code> for a list of required parameters.</p>
     </div>
 
@@ -125,11 +124,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/dot-prepare_population.html b/reference/dot-prepare_population.html
index 67fbb9f2..d2c53a16 100644
--- a/reference/dot-prepare_population.html
+++ b/reference/dot-prepare_population.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Prepare a &amp;lt;population&amp;gt; for an epidemic model"><title>Prepare a &lt;population&gt; for an epidemic model — .prepare_population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare a &lt;population&gt; for an epidemic model — .prepare_population"><meta property="og:description" content="Prepare a &amp;lt;population&amp;gt; for an epidemic model"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Prepare a &amp;lt;population&amp;gt; for an epidemic model"><title>Prepare a &lt;population&gt; for an epidemic model — .prepare_population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare a &lt;population&gt; for an epidemic model — .prepare_population"><meta property="og:description" content="Prepare a &amp;lt;population&amp;gt; for an epidemic model"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -112,11 +111,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/reference/epidemic_size.html b/reference/epidemic_size.html
index 3a63eba7..4f95271f 100644
--- a/reference/epidemic_size.html
+++ b/reference/epidemic_size.html
@@ -1,7 +1,7 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Get the size of the epidemic at any stage between the start and the end.
 This is calculated as the number of individuals recovered from infection
-at that stage of the epidemic."><title>Get the epidemic size — epidemic_size • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Get the epidemic size — epidemic_size"><meta property="og:description" content="Get the size of the epidemic at any stage between the start and the end.
+at that stage of the epidemic."><title>Get the epidemic size — epidemic_size • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Get the epidemic size — epidemic_size"><meta property="og:description" content="Get the size of the epidemic at any stage between the start and the end.
 This is calculated as the number of individuals recovered from infection
 at that stage of the epidemic."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -16,12 +16,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -65,10 +65,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -94,22 +93,37 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">epidemic_size</span><span class="op">(</span><span class="va">data</span>, stage <span class="op">=</span> <span class="fl">1</span>, by_group <span class="op">=</span> <span class="cn">TRUE</span>, include_deaths <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">epidemic_size</span><span class="op">(</span></span>
+<span>  <span class="va">data</span>,</span>
+<span>  stage <span class="op">=</span> <span class="fl">1</span>,</span>
+<span>  time <span class="op">=</span> <span class="cn">NULL</span>,</span>
+<span>  by_group <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>  include_deaths <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>  simplify <span class="op">=</span> <span class="cn">TRUE</span></span>
+<span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
     <dl><dt>data</dt>
 <dd><p>A table of model output, typically
-the output of <code><a href="model_default.html">model_default()</a></code> or similar functions.</p></dd>
+the output of <code>model_de  ault()</code> or similar functions.</p></dd>
 
 
 <dt>stage</dt>
-<dd><p>The stage of the epidemic at which to return the epidemic size;
-here, 0.0 represents the initial conditions of the epidemic (0% of model time
-), while 1.0 represents the end of the epidemic model (100% of model time).
-The values returned at <code>stage = 1.0</code> represent the <em>final size</em> of the
-epidemic.</p></dd>
+<dd><p>A numeric vector for the stage of the epidemic at which to
+return the epidemic size; here 0.0 represents the start time of the epidemic
+i.e., the initial conditions of the epidemic simulation, while 1.0 represents
+the end of the epidemic simulation model (100% of model time).
+Defaults to 1.0, at which stage returned values represent the <em>final size</em> of
+the epidemic.
+This value is overridden by any values passed to the <code>time</code> argument.</p></dd>
+
+
+<dt>time</dt>
+<dd><p>Alternative to <code>stage</code>, an integer-like vector for the timepoint
+of the epidemic at which to return the epidemic size.
+Overrides any values passed to <code>stage</code>.</p></dd>
 
 
 <dt>by_group</dt>
@@ -121,19 +135,36 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 <dt>include_deaths</dt>
 <dd><p>A logical value that indicates whether to count dead
 individuals in the epidemic size calculation.
-Defaults to <code>TRUE</code>, which makes the function look for a <code>"dead"</code> compartment
-in the data. If there is no such column, the function returns
-only the final number of recovered or removed individuals in each demographic
-group.</p></dd>
+Defaults to <code>FALSE</code>. Setting <code>include_deaths = TRUE</code> makes the function look
+for a <code>"dead"</code> compartment in the data. If there is no such column, the
+function returns only the final number of recovered or removed individuals in
+each demographic group.</p></dd>
+
+
+<dt>simplify</dt>
+<dd><p>A logical determining whether the epidemic size data should
+be simplified to a vector with one element for each demographic group.
+If the length of <code>stage</code> or <code>time</code> is $&gt;$ 1, this argument is overridden and
+the data are returned as a <code>&lt;data.table&gt;</code>.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
     
 
-<p>A single number when <code>by_group = FALSE</code>, or a vector of numbers of
-the same length as the number of demographic groups when <code>by_group = TRUE</code>.
-Returns the absolute sizes and not proportions.</p>
+<p>If <code>simplify == TRUE</code> and a single timepoint is requested, returns a vector
+of epidemic sizes of the same length as the number of demographic groups.
+If <code>by_group == FALSE</code>, sums the epidemic size to return an overall value for
+the full population.</p>
+
+
+<p>If multiple timepoints are requested, or if multiple replicates are present
+under a specially named column "replicate" (only from the Ebola model), no
+simplification to a vector is possible; returns a <code>&lt;data.table&gt;</code> of
+timepoints and epidemic sizes at each timepoint.</p>
+
+
+<p>All options return the absolute sizes and not proportions.</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -162,17 +193,18 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span>  population <span class="op">=</span> <span class="va">uk_population</span></span></span>
 <span class="r-in"><span><span class="op">)</span></span></span>
 <span class="r-in"><span></span></span>
-<span class="r-in"><span><span class="co"># get the final epidemic size</span></span></span>
+<span class="r-in"><span><span class="co"># get the final epidemic size if no other arguments are specified</span></span></span>
 <span class="r-in"><span><span class="fu">epidemic_size</span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> No 'dead' compartment found in `data`; counting only 'recovered' individuals in the epidemic size.</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> demo_group_1 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     481200.2 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 481200.2</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># get the epidemic size at the halfway point</span></span></span>
 <span class="r-in"><span><span class="fu">epidemic_size</span><span class="op">(</span><span class="va">data</span>, stage <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span></span></span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> No 'dead' compartment found in `data`; counting only 'recovered' individuals in the epidemic size.</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> demo_group_1 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>     81921.88 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 81921.88</span>
+<span class="r-in"><span></span></span>
+<span class="r-in"><span><span class="co"># alternatively, get the epidemic size at `time = 50`</span></span></span>
+<span class="r-in"><span><span class="fu">epidemic_size</span><span class="op">(</span><span class="va">data</span>, time <span class="op">=</span> <span class="fl">50</span><span class="op">)</span></span></span>
+<span class="r-msg co"><span class="r-pr">#&gt;</span> epidemic_size(): `time` provided will override any `stage` provided</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 81921.88</span>
 </code></pre></div>
     </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
@@ -180,11 +212,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/epidemics-package.html b/reference/epidemics-package.html
index a34371b5..b458defa 100644
--- a/reference/epidemics-package.html
+++ b/reference/epidemics-package.html
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@@ -77,13 +76,13 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
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   <main id="main" class="col-md-9"><div class="page-header">
-      <img src="../logo.svg" class="logo" alt=""><h1>epidemics: A Library of Compartmental Epidemic Scenario Models</h1>
+      <img src="../logo.svg" class="logo" alt=""><h1>epidemics: Composable Epidemic Scenario Modelling</h1>
       <small class="dont-index">Source: <a href="https://github.com/epiverse-trace/epidemics/blob/HEAD/R/epidemics-package.R" class="external-link"><code>R/epidemics-package.R</code></a></small>
       <div class="d-none name"><code>epidemics-package.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p>A library of compartmental epidemic models taken from the published literature, and classes to represent populations with heterogeneous characteristics, public health response measures including non-pharmaceutical interventions on social contacts, non-pharmaceutical and pharmaceutical interventions that affect disease transmissibility, vaccination regimes, and disease seasonality, which can be combined to compose epidemic scenarios.</p>
+    <p>A library of compartmental epidemic models taken from the published literature, and classes to represent affected populations, public health response measures including non-pharmaceutical interventions on social contacts, non-pharmaceutical and pharmaceutical interventions that affect disease transmissibility, vaccination regimes, and disease seasonality, which can be combined to compose epidemic scenario models.</p>
     </div>
 
 
@@ -101,8 +100,10 @@ <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a><
 <li><p>Edwin Van Leeuwen <a href="mailto:edwin.vanleeuwen@ukhsa.gov.uk">edwin.vanleeuwen@ukhsa.gov.uk</a> (<a href="https://orcid.org/0000-0002-2383-5305" class="external-link">ORCID</a>) [copyright holder]</p></li>
 </ul><p>Other contributors:</p><ul><li><p>Adam Kucharski <a href="mailto:adam.kucharski@lshtm.ac.uk">adam.kucharski@lshtm.ac.uk</a> (<a href="https://orcid.org/0000-0001-8814-9421" class="external-link">ORCID</a>) [contributor, reviewer]</p></li>
 <li><p>Tim Taylor <a href="mailto:tim.taylor@hiddenelephants.co.uk">tim.taylor@hiddenelephants.co.uk</a> (<a href="https://orcid.org/0000-0002-8587-7113" class="external-link">ORCID</a>) [contributor, reviewer]</p></li>
+<li><p>Banky Ahadzie <a href="mailto:bahadzie@gmail.com">bahadzie@gmail.com</a> [contributor]</p></li>
 <li><p>Hugo Gruson <a href="mailto:hugo.gruson@data.org">hugo.gruson@data.org</a> (<a href="https://orcid.org/0000-0002-4094-1476" class="external-link">ORCID</a>) [reviewer]</p></li>
 <li><p>Joshua W. Lambert <a href="mailto:joshua.lambert@lshtm.ac.uk">joshua.lambert@lshtm.ac.uk</a> (<a href="https://orcid.org/0000-0001-5218-3046" class="external-link">ORCID</a>) [reviewer]</p></li>
+<li><p>James M. Azam <a href="mailto:james.azam@lshtm.ac.uk">james.azam@lshtm.ac.uk</a> (<a href="https://orcid.org/0000-0001-5782-7330" class="external-link">ORCID</a>) [reviewer]</p></li>
 </ul></div>
 
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@@ -110,11 +111,11 @@ <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a><
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/reference/index.html b/reference/index.html
index e68f1395..4a5414bf 100644
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@@ -1,5 +1,5 @@
 <!DOCTYPE html>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Function reference • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Function reference"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -135,14 +134,14 @@ <h3 id="intervention">Intervention<a class="anchor" aria-label="anchor" href="#i
         <dd>Convert a list to a intervention object</dd>
       </dl><dl><dt>
           
-          <code><a href="intervention.html">intervention()</a></code> <code><a href="intervention.html">is_intervention()</a></code> <code><a href="intervention.html">is_contacts_intervention()</a></code> <code><a href="intervention.html">is_rate_intervention()</a></code> <code><a href="intervention.html">c(<i>&lt;contacts_intervention&gt;</i>)</a></code> <code><a href="intervention.html">c(<i>&lt;rate_intervention&gt;</i>)</a></code> 
+          <code><a href="dot-intervention_on_rates.html">.intervention_on_rates()</a></code> 
         </dt>
-        <dd>Create an intervention for an epidemic model</dd>
+        <dd>Apply interventions to rate parameters</dd>
       </dl><dl><dt>
           
-          <code><a href="intervention_on_rates.html">intervention_on_rates()</a></code> 
+          <code><a href="intervention.html">intervention()</a></code> <code><a href="intervention.html">is_intervention()</a></code> <code><a href="intervention.html">is_contacts_intervention()</a></code> <code><a href="intervention.html">is_rate_intervention()</a></code> <code><a href="intervention.html">c(<i>&lt;contacts_intervention&gt;</i>)</a></code> <code><a href="intervention.html">c(<i>&lt;rate_intervention&gt;</i>)</a></code> 
         </dt>
-        <dd>Apply interventions to rate parameters</dd>
+        <dd>Create an intervention for an epidemic model</dd>
       </dl><dl><dt>
           
           <code><a href="print_intervention.html">print(<i>&lt;intervention&gt;</i>)</a></code> <code><a href="print_intervention.html">print(<i>&lt;contact_intervention&gt;</i>)</a></code> <code><a href="print_intervention.html">print(<i>&lt;rate_intervention&gt;</i>)</a></code> 
@@ -198,7 +197,7 @@ <h3 id="vaccination">Vaccination<a class="anchor" aria-label="anchor" href="#vac
       </dl></div><div class="section level2">
       <h2 id="helper-functions">Helper functions<a class="anchor" aria-label="anchor" href="#helper-functions"></a></h2>
       
-      <p class="section-desc"></p><p>Functions to help with handling package classes and outputs.</p>
+      <div class="section-desc"><p>Functions to help with handling package classes and outputs.</p></div>
 
       
     </div><div id="" class="section level2">
@@ -222,11 +221,11 @@ <h2 id="helper-functions">Helper functions<a class="anchor" aria-label="anchor"
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/intervention.html b/reference/intervention.html
index 1887fb07..c63be6f5 100644
--- a/reference/intervention.html
+++ b/reference/intervention.html
@@ -12,7 +12,7 @@
 the reduction of contacts.
 Combine &amp;lt;intervention&amp;gt;-inheriting objects to create sequential or
 overlapping intervention regimes using c() on two or more
-&amp;lt;intervention&amp;gt;-inheriting objects."><title>Create an intervention for an epidemic model — intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create an intervention for an epidemic model — intervention"><meta property="og:description" content="Prepare an object of the &amp;lt;intervention&amp;gt; super-class that specifies a
+&amp;lt;intervention&amp;gt;-inheriting objects."><title>Create an intervention for an epidemic model — intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create an intervention for an epidemic model — intervention"><meta property="og:description" content="Prepare an object of the &amp;lt;intervention&amp;gt; super-class that specifies a
 modification of the model parameters.
 A &amp;lt;contacts_intervention&amp;gt; is used to simulate a non-pharmaceutical
 intervention (NPI) regime that reduces the population's social contacts.
@@ -38,12 +38,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -87,10 +87,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -135,10 +134,10 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 <span></span>
 <span><span class="fu">is_rate_intervention</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for contacts_intervention</span></span>
+<span><span class="co"># S3 method for class 'contacts_intervention'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for rate_intervention</span></span>
+<span><span class="co"># S3 method for class 'rate_intervention'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
     </div>
 
@@ -319,11 +318,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/intervention_constructor.html b/reference/intervention_constructor.html
index eb686e4a..bc0bb64f 100644
--- a/reference/intervention_constructor.html
+++ b/reference/intervention_constructor.html
@@ -1,7 +1,7 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Constructor for the  super-class and sub-classes
 Constructor for a new &amp;lt;contacts_intervention&amp;gt;
-Constructor for a new &amp;lt;rate_intervention&amp;gt;"><title>Constructor for the  super-class and sub-classes — intervention_constructor • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Constructor for the  super-class and sub-classes — intervention_constructor"><meta property="og:description" content="Constructor for the  super-class and sub-classes
+Constructor for a new &amp;lt;rate_intervention&amp;gt;"><title>Constructor for the  super-class and sub-classes — intervention_constructor • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Constructor for the  super-class and sub-classes — intervention_constructor"><meta property="og:description" content="Constructor for the  super-class and sub-classes
 Constructor for a new &amp;lt;contacts_intervention&amp;gt;
 Constructor for a new &amp;lt;rate_intervention&amp;gt;"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -16,12 +16,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -65,10 +65,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -157,11 +156,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/model_default.html b/reference/model_default.html
index 4558f135..e0d210a2 100644
--- a/reference/model_default.html
+++ b/reference/model_default.html
@@ -9,7 +9,7 @@
 arguments are mandatory, while passing an intervention and vaccination
 are optional and can be used to simulate scenarios with different epidemic
 responses or different levels of the same type of response.
-See Details for more information.'><title>Model an SEIR-V epidemic with interventions — model_default • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model an SEIR-V epidemic with interventions — model_default"><meta property="og:description" content='Simulate an epidemic using a deterministic, compartmental
+See Details for more information.'><title>Model an SEIR-V epidemic with interventions — model_default • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model an SEIR-V epidemic with interventions — model_default"><meta property="og:description" content='Simulate an epidemic using a deterministic, compartmental
 epidemic model with the compartments
 "susceptible", "exposed", "infectious", "recovered", and "vaccinated".
 This model can accommodate heterogeneity in social contacts among demographic
@@ -32,12 +32,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -81,10 +81,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -305,11 +304,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/reference/model_diphtheria.html b/reference/model_diphtheria.html
index f7028e6d..e76ee9ed 100644
--- a/reference/model_diphtheria.html
+++ b/reference/model_diphtheria.html
@@ -7,7 +7,7 @@
 This model allows for a proportion of each demographic group to be vaccinated
 at the start of the outbreak, and thus to not contribute to the outbreak.
 The model also allows for changes to the number of susceptibles in each age
-group to model influxes or evacuations from camps.'><title>Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria"><meta property="og:description" content='Simulate a diphtheria outbreak using a deterministic,
+group to model influxes or evacuations from camps.'><title>Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria"><meta property="og:description" content='Simulate a diphtheria outbreak using a deterministic,
 compartmental ordinary differential equation model with the compartments
 "susceptible", "exposed", "infectious", "hospitalised", and"recovered".
 The model is based on Finger et al. (2019) and is intended to be used in the
@@ -28,12 +28,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -77,10 +77,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -372,11 +371,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/reference/model_ebola.html b/reference/model_ebola.html
index 02cf16e2..af3cadec 100644
--- a/reference/model_ebola.html
+++ b/reference/model_ebola.html
@@ -6,7 +6,7 @@
 2013 -- 2016.
 See Details for more information.
 model_ebola_cpp() is an Rcpp implementation of this model that currently
-lags behind the R implementation, and is likely to be removed."><title>Model an Ebola virus disease epidemic — model_ebola • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model an Ebola virus disease epidemic — model_ebola"><meta property="og:description" content="Simulate an epidemic using a discrete-time, stochastic SEIR
+lags behind the R implementation, and is likely to be removed."><title>Model an Ebola virus disease epidemic — model_ebola • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model an Ebola virus disease epidemic — model_ebola"><meta property="og:description" content="Simulate an epidemic using a discrete-time, stochastic SEIR
 compartmental model with compartments based on Li et al. (2019), and with
 Erlang passage times based on a model developed by Getz and Dougherty (2017),
 developed to model the West African Ebola virus disease (EVD) outbreak of
@@ -26,12 +26,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -75,10 +75,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -111,8 +110,8 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">model_ebola</span><span class="op">(</span></span>
 <span>  <span class="va">population</span>,</span>
-<span>  erlang_subcompartments <span class="op">=</span> <span class="fl">2</span>,</span>
 <span>  transmission_rate <span class="op">=</span> <span class="fl">1.5</span><span class="op">/</span><span class="fl">12</span>,</span>
+<span>  erlang_subcompartments <span class="op">=</span> <span class="fl">2</span>,</span>
 <span>  infectiousness_rate <span class="op">=</span> <span class="va">erlang_subcompartments</span><span class="op">/</span><span class="fl">5</span>,</span>
 <span>  removal_rate <span class="op">=</span> <span class="va">erlang_subcompartments</span><span class="op">/</span><span class="fl">12</span>,</span>
 <span>  prop_community <span class="op">=</span> <span class="fl">0.9</span>,</span>
@@ -120,7 +119,8 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 <span>  funeral_risk <span class="op">=</span> <span class="fl">0.5</span>,</span>
 <span>  intervention <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  time_dependence <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span>  time_end <span class="op">=</span> <span class="fl">100</span></span>
+<span>  time_end <span class="op">=</span> <span class="fl">100</span>,</span>
+<span>  replicates <span class="op">=</span> <span class="fl">100</span></span>
 <span><span class="op">)</span></span></code></pre></div>
     </div>
 
@@ -137,21 +137,22 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 is one.</p></dd>
 
 
-<dt>erlang_subcompartments</dt>
-<dd><p>The number of Erlang subcompartments assumed
-for the exposed, infectious, and hospitalised compartments. Defaults to 2.</p></dd>
-
-
 <dt>transmission_rate</dt>
-<dd><p>A single number for the rate at which individuals
+<dd><p>A numeric vector for the rate at which individuals
 move from the susceptible to the exposed compartment upon contact with an
 infectious individual. Often denoted as \(\beta\), with
 \(\beta = R_0 / \text{infectious period}\).
 See <strong>Details</strong> for default values.</p></dd>
 
 
+<dt>erlang_subcompartments</dt>
+<dd><p>A numeric, integer-like vector for the number
+of Erlang sub-compartments assumed for the exposed, infectious, and
+hospitalised compartments. Defaults to 2.</p></dd>
+
+
 <dt>infectiousness_rate</dt>
-<dd><p>A single number for the rate at which individuals
+<dd><p>A numeric vector for the rate at which individuals
 move from the exposed to the infectious compartment. Often denoted as
 \(\sigma\), with \(\sigma = 1.0 / \text{pre-infectious period}\).
 This value does not depend upon the number of infectious individuals in the
@@ -160,64 +161,84 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 
 
 <dt>removal_rate</dt>
-<dd><p>The rate at which infectious individuals transition from
-the infectious or hospitalised compartments to the funeral or removed
-compartments. This model does not distinguish between recoveries and
-deaths. Denoted in Getz and Dougherty as \(\gamma^I\) (see <strong>Details</strong>).</p></dd>
+<dd><p>A numeric vector for the rate at which infectious
+individuals transition from the infectious or hospitalised compartments to
+the funeral or removed compartments.
+This model does not distinguish between recoveries and deaths.
+Denoted in Getz and Dougherty as \(\gamma^I\) (see <strong>Details</strong>).</p></dd>
 
 
 <dt>prop_community</dt>
-<dd><p>The proportion of infectious individuals who remain in
-the community and are not hospitalised for treatment. Defaults to 0.5</p></dd>
+<dd><p>A numeric vector for the proportion of infectious
+individuals who remain in the community and are not hospitalised for
+treatment. Defaults to 0.9.</p></dd>
 
 
 <dt>etu_risk</dt>
-<dd><p>The relative risk of onward transmission of EVD from
-hospitalised individuals. Must be a single value between 0.0 and 1.0, where
+<dd><p>A numeric vector for the relative risk of onward transmission
+of EVD from hospitalised individuals, with values between 0.0 and 1.0, where
 0.0 indicates that hospitalisation completely prevents onward transmission,
 and 1.0 indicates that hospitalisation does not prevent onward transmission
-at all. <code>etu_risk</code> is used to scale the value of transmission_rate for the
-transmission_rate \(\beta\). Defaults to 0.2.</p></dd>
+at all; values are relative to the baseline transmission rate \(\beta\).
+Defaults to 0.7.</p></dd>
 
 
 <dt>funeral_risk</dt>
-<dd><p>The relative risk of onward transmission of EVD from
-funerals of individuals who died with EVD.
-Must be a single value between 0.0 and 1.0, where
-0.0 indicates that there is no onward transmission, and 1.0 indicates that
-funeral transmission is equivalent to transmission in the community.
-<code>funeral_risk</code> is used to scale the value of transmission_rate for the
-transmission_rate \(\beta\). Defaults to 0.5.</p></dd>
+<dd><p>A numeric vector for the relative risk of onward
+transmission of EVD from funerals of individuals who died with EVD.
+Must be between 0.0 and 1.0, where 0.0 indicates that there is no onward
+transmission, and 1.0 indicates that funeral transmission is equivalent to
+the baseline transmission rate in the community \(\beta\).
+Defaults to 0.5.</p></dd>
 
 
 <dt>intervention</dt>
-<dd><p>A named list of <code>&lt;rate_intervention&gt;</code> objects
+<dd><p>An optional named list of <code>&lt;rate_intervention&gt;</code> objects
 representing optional pharmaceutical or non-pharmaceutical interventions
-applied to the model parameters listed above.</p></dd>
+applied to the model parameters listed above. May also be a list of such
+lists, in which case each set of interventions is treated as a separate
+scenario. See <strong>Details</strong> below.</p></dd>
 
 
 <dt>time_dependence</dt>
-<dd><p>A named list where each name
-is a model parameter, and each element is a function with
-the first two arguments being the current simulation <code>time</code>, and <code>x</code>, a value
-that is dependent on <code>time</code> (<code>x</code> represents a model parameter).
+<dd><p>An optional named list where each element is a
+function with the first two arguments being the current simulation <code>time</code>,
+and <code>x</code>, a value that is dependent on <code>time</code>
+(<code>x</code> represents a model parameter).
+List names must correspond to model parameters modified by the function.
+Alternatively, may be a list of such lists, in which case each set of
+functions is treated as a distinct scenario.
 See <strong>Details</strong> for more information, as well as the vignette on time-
 dependence <code>vignette("time_dependence", package = "epidemics")</code>.</p></dd>
 
 
 <dt>time_end</dt>
-<dd><p>The maximum number of timesteps over which to run the model,
-in days. Defaults to 100 days.</p></dd>
+<dd><p>A numeric, integer-like vector for the maximum number of</p></dd>
+
+
+<dt>replicates</dt>
+<dd><p>A single number for replicates to run. Defaults to 100.
+timesteps over which to run the model, in days. Defaults to 100 days.</p></dd>
 
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
     
 
-<p>A <code>&lt;data.table&gt;</code> in
-long format with the columns "time", "compartment", "age_group", and "value",
-that gives the number of individuals in each model compartment over time (
-from 1 to <code>time_end</code>).</p>
+<p>A <code>&lt;data.table&gt;</code>.
+If the model parameters and composable elements are all scalars, a single
+<code>&lt;data.table&gt;</code> with the columns "time", "compartment", "age_group", and
+"value", giving the number of individuals per demographic group
+in each compartment at each timestep in long (or "tidy") format is returned.</p>
+
+
+<p>If the model parameters or composable elements are lists or list-like,
+a nested <code>&lt;data.table&gt;</code> is returned with a list column "data", which holds
+the compartmental values described above.
+Other columns hold parameters and composable elements relating to the model
+run. Columns "scenario" and "param_set" identify combinations of composable
+elements (population, interventions, vaccination regimes), and infection
+parameters, respectively.</p>
     </div>
     <div class="section level2">
     <h2 id="details-discrete-time-ebola-virus-disease-model">Details: Discrete-time Ebola virus disease model<a class="anchor" aria-label="anchor" href="#details-discrete-time-ebola-virus-disease-model"></a></h2>
@@ -299,6 +320,40 @@ <h3 id="implementing-vaccination">Implementing vaccination<a class="anchor" aria
 way that is consistent with the effect of vaccination.
 An example is shown in the vignette about this model; run this code to open
 the vignette: <code>vignette("ebola_model", package = "epidemics")</code></p>
+</div>
+
+<div class="section">
+<h3 id="vector-inputs">Vector inputs<a class="anchor" aria-label="anchor" href="#vector-inputs"></a></h3>
+
+<div class="section">
+<h4 id="vector-parameter-inputs">Vector parameter inputs<a class="anchor" aria-label="anchor" href="#vector-parameter-inputs"></a></h4>
+
+
+<p>The model infection parameters and the model duration may be passed as
+numeric or integer-like vectors (as appropriate to the parameter), to
+simulate the effect of parameter uncertainty.
+All parameter vectors must be of the same length, or any one parameter vector
+may have a length &gt; 1 while all other have a length of 1. In the first case,
+each i-th combination of parameters is treated as a parameter set. In the
+second case, all single value parameters (scalars) are recycled to the same
+length as the non-scalar parameter.</p>
+<p>The model is run for $N$ stochastic realisations of each parameter set.
+Random number seeds are preserved across parameter sets, so that differences
+in outcomes in each j-th run are due to differences in parameters alone.</p>
+</div>
+
+<div class="section">
+<h4 id="vector-inputs-for-composable-elements">Vector inputs for composable elements<a class="anchor" aria-label="anchor" href="#vector-inputs-for-composable-elements"></a></h4>
+
+
+<p>The <code>intervention</code> and <code>time_dependence</code> arguments also accept vectorised
+inputs in the form of lists of intervention and time dependence sets.
+Each combination of intervention and time-dependence sets is treated as a
+distinct 'scenario', and realisations of each parameter set are run for each
+scenario.</p>
+</div>
+
+
 </div>
 
     </div>
@@ -333,13 +388,14 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># view some data</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">data</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   time demography_group  compartment    value</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1    1     demo_group_1  susceptible 13999972</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2    1     demo_group_1      exposed       14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3    1     demo_group_1   infectious       14</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4    1     demo_group_1 hospitalised        0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5    1     demo_group_1      funeral        0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6    1     demo_group_1      removed        0</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>     time demography_group  compartment    value replicate</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>    &lt;int&gt;           &lt;char&gt;       &lt;char&gt;    &lt;num&gt;     &lt;int&gt;</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 1:     0     demo_group_1  susceptible 13999972         1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2:     0     demo_group_1      exposed       14         1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3:     0     demo_group_1   infectious       14         1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 4:     0     demo_group_1 hospitalised        0         1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 5:     0     demo_group_1      funeral        0         1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 6:     0     demo_group_1      removed        0         1</span>
 </code></pre></div>
     </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
@@ -347,11 +403,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/model_vacamole.html b/reference/model_vacamole.html
index 5ad570d2..192fc1c7 100644
--- a/reference/model_vacamole.html
+++ b/reference/model_vacamole.html
@@ -3,7 +3,7 @@
 developed at RIVM, the National Institute for Public Health and the
 Environment in the Netherlands.
 This model is aimed at estimating the impact of 'leaky' vaccination on an
-epidemic. See Details and References for more information."><title>Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole"><meta property="og:description" content="Simulate an epidemic using the Vacamole model for Covid-19
+epidemic. See Details and References for more information."><title>Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole"><meta property="og:description" content="Simulate an epidemic using the Vacamole model for Covid-19
 developed at RIVM, the National Institute for Public Health and the
 Environment in the Netherlands.
 This model is aimed at estimating the impact of 'leaky' vaccination on an
@@ -20,12 +20,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
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-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -69,10 +69,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -378,11 +377,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/reference/new_infections.html b/reference/new_infections.html
index e0fe0eb1..0d19933c 100644
--- a/reference/new_infections.html
+++ b/reference/new_infections.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
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+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Get new infections over model time"><title>Get new infections over model time — new_infections • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Get new infections over model time — new_infections"><meta property="og:description" content="Get new infections over model time"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
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     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -164,11 +163,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
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-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
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diff --git a/reference/output_to_df.html b/reference/output_to_df.html
new file mode 100644
index 00000000..26d2443e
--- /dev/null
+++ b/reference/output_to_df.html
@@ -0,0 +1,148 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Return ODE model output as a data.table
+Return Ebola model output as a table"><title>Return ODE model output as a data.table — output_to_df • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Return ODE model output as a data.table — output_to_df"><meta property="og:description" content="Return ODE model output as a data.table
+Return Ebola model output as a table"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
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+  function gtag(){dataLayer.push(arguments);}
+  gtag('js', new Date());
+
+  gtag('config', 'G-XZ471458FQ');
+</script></head><body>
+    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
+    
+
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
+    
+    <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
+    <a class="navbar-brand me-2" href="../index.html">epidemics</a>
+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
+
+    
+    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
+      <span class="navbar-toggler-icon"></span>
+    </button>
+
+    <div id="navbar" class="collapse navbar-collapse ms-3">
+      <ul class="navbar-nav me-auto"><li class="nav-item">
+  <a class="nav-link" href="../articles/epidemics.html">Get started</a>
+</li>
+<li class="active nav-item">
+  <a class="nav-link" href="../reference/index.html">Reference</a>
+</li>
+<li class="nav-item dropdown">
+  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
+  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
+    <h6 class="dropdown-header" data-toc-skip>Modelling interventions</h6>
+    <a class="dropdown-item" href="../articles/modelling_interventions.html">Getting started with modelling interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_multiple_interventions.html">Modelling overlapping and sequential interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_rate_interventions.html">Modelling other interventions that change transmission rates</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling vaccination</h6>
+    <a class="dropdown-item" href="../articles/modelling_vaccination.html">Modelling the effect of a vaccination campaign</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling seasonality</h6>
+    <a class="dropdown-item" href="../articles/modelling_time_dependence.html">Modelling time-dependence and seasonality in transmission dynamics</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Other modelling vignettes</h6>
+    <a class="dropdown-item" href="../articles/modelling_scenarios.html">Modelling parameter uncertainty and epidemic scenarios</a>
+    <a class="dropdown-item" href="../articles/finalsize_comparison.html">Reducing parameters required for final size estimation</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Guides to library models</h6>
+    <a class="dropdown-item" href="../articles/model_vacamole.html">Modelling leaky vaccination and hospitalisation outcomes with Vacamole</a>
+    <a class="dropdown-item" href="../articles/model_ebola.html">Modelling responses to a stochastic Ebola virus epidemic</a>
+    <a class="dropdown-item" href="../articles/model_diphtheria.html">Modelling a diphtheria outbreak in a humanitarian camp setting</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
+    <a class="dropdown-item" href="../articles/design-principles.html">Design Principles for epidemics</a>
+  </div>
+</li>
+<li class="nav-item">
+  <a class="nav-link" href="../news/index.html">Changelog</a>
+</li>
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
+  <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
+    <span class="fab fa fab fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul></div>
+
+    
+  </div>
+</nav><div class="container template-reference-topic">
+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.svg" class="logo" alt=""><h1>Return ODE model output as a data.table</h1>
+      <small class="dont-index">Source: <a href="https://github.com/epiverse-trace/epidemics/blob/HEAD/R/helpers.R" class="external-link"><code>R/helpers.R</code></a></small>
+      <div class="d-none name"><code>output_to_df.Rd</code></div>
+    </div>
+
+    <div class="ref-description section level2">
+    <p>Return ODE model output as a data.table</p>
+<p>Return Ebola model output as a table</p>
+    </div>
+
+    <div class="section level2">
+    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">.output_to_df</span><span class="op">(</span><span class="va">output</span>, <span class="va">population</span>, <span class="va">compartments</span><span class="op">)</span></span>
+<span></span>
+<span><span class="fu">.output_to_df_ebola</span><span class="op">(</span><span class="va">output</span>, <span class="va">population</span>, <span class="va">compartments</span><span class="op">)</span></span></code></pre></div>
+    </div>
+
+    <div class="section level2">
+    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
+    <dl><dt>output</dt>
+<dd><p>The model output, which must be a two element list (for
+epidemic) models, with the names "x" and "time", where "x" represents the
+condition of each compartment at each timestep in "time".</p></dd>
+
+
+<dt>population</dt>
+<dd><p>A <code>&lt;population&gt;</code> object corresponding to the population
+used in the epidemic model.
+The <code>&lt;population&gt;</code> object is used to generate the names of the demographic
+groups, if these are named.</p></dd>
+
+
+<dt>compartments</dt>
+<dd><p>A vector for the model compartment names.</p></dd>
+
+</dl></div>
+    <div class="section level2">
+    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
+    
+
+<p>A <code>&lt;data.table&gt;</code> with the columns "compartment", "demography_group",
+"value", and "time"; these specify the epidemiological compartment, the
+name of the demography group, the number of individuals of that group in the
+compartment, and the model timestep, respectively.
+Names for the demographic groups are generated if no names are provided in
+the <code>population</code> object; these are of the form "demo_group_X".</p>
+    </div>
+
+  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+    </nav></aside></div>
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
+</div>
+
+    </footer></div>
+
+  
+
+  
+
+  </body></html>
+
diff --git a/reference/population.html b/reference/population.html
index 5511b4c5..d014e2c5 100644
--- a/reference/population.html
+++ b/reference/population.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Construct a new population for an epidemic model
-Check whether an object is a &amp;lt;population&amp;gt;"><title>Construct a new population for an epidemic model — population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Construct a new population for an epidemic model — population"><meta property="og:description" content="Construct a new population for an epidemic model
+Check whether an object is a &amp;lt;population&amp;gt;"><title>Construct a new population for an epidemic model — population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Construct a new population for an epidemic model — population"><meta property="og:description" content="Construct a new population for an epidemic model
 Check whether an object is a &amp;lt;population&amp;gt;"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@@ -14,12 +14,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -63,10 +63,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -178,11 +177,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/prepare_default_args.html b/reference/prepare_default_args.html
index 81fb10ac..abf45a95 100644
--- a/reference/prepare_default_args.html
+++ b/reference/prepare_default_args.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Prepare arguments to model_default() for
-.model_default_cpp()."><title>Prepare arguments to default model function — prepare_default_args • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare arguments to default model function — prepare_default_args"><meta property="og:description" content="Prepare arguments to model_default() for
+.model_default_cpp()."><title>Prepare arguments to default model function — prepare_default_args • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare arguments to default model function — prepare_default_args"><meta property="og:description" content="Prepare arguments to model_default() for
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@@ -14,12 +14,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -63,10 +63,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
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-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
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     <footer><div class="pkgdown-footer-left">
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 </div>
 
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diff --git a/reference/prepare_diphtheria_args.html b/reference/prepare_diphtheria_args.html
index 02066f19..26213daa 100644
--- a/reference/prepare_diphtheria_args.html
+++ b/reference/prepare_diphtheria_args.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Prepare arguments to model_diphtheria() for
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@@ -14,12 +14,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
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-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
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@@ -63,10 +63,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
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   <a class="nav-link" href="../news/index.html">Changelog</a>
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     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
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 </div>
 
 <div class="pkgdown-footer-right">
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diff --git a/reference/prepare_ebola_args.html b/reference/prepare_ebola_args.html
new file mode 100644
index 00000000..d93c2373
--- /dev/null
+++ b/reference/prepare_ebola_args.html
@@ -0,0 +1,150 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Prepare arguments to model_ebola() for
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+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
+
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+    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
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+    <h6 class="dropdown-header" data-toc-skip>Modelling interventions</h6>
+    <a class="dropdown-item" href="../articles/modelling_interventions.html">Getting started with modelling interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_multiple_interventions.html">Modelling overlapping and sequential interventions targeting social contacts</a>
+    <a class="dropdown-item" href="../articles/modelling_rate_interventions.html">Modelling other interventions that change transmission rates</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling vaccination</h6>
+    <a class="dropdown-item" href="../articles/modelling_vaccination.html">Modelling the effect of a vaccination campaign</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Modelling seasonality</h6>
+    <a class="dropdown-item" href="../articles/modelling_time_dependence.html">Modelling time-dependence and seasonality in transmission dynamics</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Other modelling vignettes</h6>
+    <a class="dropdown-item" href="../articles/modelling_scenarios.html">Modelling parameter uncertainty and epidemic scenarios</a>
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+    <h6 class="dropdown-header" data-toc-skip>Guides to library models</h6>
+    <a class="dropdown-item" href="../articles/model_vacamole.html">Modelling leaky vaccination and hospitalisation outcomes with Vacamole</a>
+    <a class="dropdown-item" href="../articles/model_ebola.html">Modelling responses to a stochastic Ebola virus epidemic</a>
+    <a class="dropdown-item" href="../articles/model_diphtheria.html">Modelling a diphtheria outbreak in a humanitarian camp setting</a>
+    <div class="dropdown-divider"></div>
+    <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
+    <a class="dropdown-item" href="../articles/design-principles.html">Design Principles for epidemics</a>
+  </div>
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+<li class="nav-item">
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+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.svg" class="logo" alt=""><h1>Prepare arguments to ebola model function</h1>
+      <small class="dont-index">Source: <a href="https://github.com/epiverse-trace/epidemics/blob/HEAD/R/check_args_ebola.R" class="external-link"><code>R/check_args_ebola.R</code></a></small>
+      <div class="d-none name"><code>prepare_ebola_args.Rd</code></div>
+    </div>
+
+    <div class="ref-description section level2">
+    <p>Prepare arguments to <code><a href="model_ebola.html">model_ebola()</a></code> for
+<code><a href="dot-model_ebola_internal.html">.model_ebola_internal()</a></code>.</p>
+    </div>
+
+    <div class="section level2">
+    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">.check_prepare_args_ebola</span><span class="op">(</span><span class="va">mod_args</span><span class="op">)</span></span></code></pre></div>
+    </div>
+
+    <div class="section level2">
+    <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
+    <dl><dt>mod_args</dt>
+<dd><p>A named list of composable elements; must include a
+<code>&lt;population&gt;</code>.</p></dd>
+
+</dl></div>
+    <div class="section level2">
+    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
+    
+
+<p>A list of model arguments suitable for <code><a href="dot-model_ebola_internal.html">.model_ebola_internal()</a></code>, if all
+elements of <code>mod_args</code> are suitable for the Ebola model.
+If any of the model composable elements are not suitable, has the side-effect
+of throwing errors to the user.
+If any elements of <code>mod_args</code> are <code>NULL</code>, returns dummy placeholder values
+for those elements.</p>
+
+
+<p>The returned list of prepared model arguments is a named list consisting of:</p><ul><li><p><code>"initial_state"</code>: the initial conditions of the simulation, which is the
+number of individuals in each compartment. No age stratification allowed.</p></li>
+<li><p><code>"intervention"</code>: either a list of <code>&lt;rate_intervention&gt;</code> objects, or a
+dummy <code>&lt;rate_intervention&gt;</code> if there are no interventions specified by the
+user.</p></li>
+<li><p><code>"time_dependence"</code>: the time-dependence composable element passed by the
+user. Input checks on this element occur in the higher level model function.</p></li>
+</ul></div>
+    <div class="section level2">
+    <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
+    <p><code>.check_prepare_args_ebola()</code> prepares arguments for
+<code><a href="dot-model_ebola_internal.html">.model_ebola_internal()</a></code>, by converting some of the arguments
+collected in <code>mod_args</code> into simpler structures that are appropriate for the
+internal model function.</p>
+    </div>
+
+  </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+    </nav></aside></div>
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
+</div>
+
+    </footer></div>
+
+  
+
+  
+
+  </body></html>
+
diff --git a/reference/prepare_vacamole_args.html b/reference/prepare_vacamole_args.html
index 601929a5..29650a95 100644
--- a/reference/prepare_vacamole_args.html
+++ b/reference/prepare_vacamole_args.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Prepare arguments to model_vacamole() for
-.model_vacamole_cpp()."><title>Prepare arguments to Vacamole epidemic function — prepare_vacamole_args • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare arguments to Vacamole epidemic function — prepare_vacamole_args"><meta property="og:description" content="Prepare arguments to model_vacamole() for
+.model_vacamole_cpp()."><title>Prepare arguments to Vacamole epidemic function — prepare_vacamole_args • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Prepare arguments to Vacamole epidemic function — prepare_vacamole_args"><meta property="og:description" content="Prepare arguments to model_vacamole() for
 .model_vacamole_cpp()."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@@ -14,12 +14,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -63,10 +63,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -143,11 +142,11 @@ <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/print.population.html b/reference/print.population.html
index e4bd6007..3c7efe26 100644
--- a/reference/print.population.html
+++ b/reference/print.population.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Print a &amp;lt;population&amp;gt; object"><title>Print a &lt;population&gt; object — print.population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Print a &lt;population&gt; object — print.population"><meta property="og:description" content="Print a &amp;lt;population&amp;gt; object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Print a &amp;lt;population&amp;gt; object"><title>Print a &lt;population&gt; object — print.population • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Print a &lt;population&gt; object — print.population"><meta property="og:description" content="Print a &amp;lt;population&amp;gt; object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -88,7 +87,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for population</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for class 'population'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
     </div>
 
@@ -115,11 +114,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/print.vaccination.html b/reference/print.vaccination.html
index e87ad42c..0c30e02a 100644
--- a/reference/print.vaccination.html
+++ b/reference/print.vaccination.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Print a &amp;lt;vaccination&amp;gt; object"><title>Print a &lt;vaccination&gt; object — print.vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Print a &lt;vaccination&gt; object — print.vaccination"><meta property="og:description" content="Print a &amp;lt;vaccination&amp;gt; object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Print a &amp;lt;vaccination&amp;gt; object"><title>Print a &lt;vaccination&gt; object — print.vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Print a &lt;vaccination&gt; object — print.vaccination"><meta property="og:description" content="Print a &amp;lt;vaccination&amp;gt; object"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Google tag (gtag.js) --><script async src="https://www.googletagmanager.com/gtag/js?id=G-XZ471458FQ"></script><script>
@@ -12,12 +12,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -61,10 +61,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -88,7 +87,7 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for vaccination</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for class 'vaccination'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
     </div>
 
@@ -115,11 +114,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/print_intervention.html b/reference/print_intervention.html
index 171608ae..a1b01a0d 100644
--- a/reference/print_intervention.html
+++ b/reference/print_intervention.html
@@ -1,7 +1,7 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Print an object of the &amp;lt;intervention&amp;gt; super-class
 Print objects of the &amp;lt;contact_intervention&amp;gt; class
-Print objects of the &amp;lt;rate_intervention&amp;gt; class"><title>Print an object of the &lt;intervention&gt; super-class — print_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Print an object of the &lt;intervention&gt; super-class — print_intervention"><meta property="og:description" content="Print an object of the &amp;lt;intervention&amp;gt; super-class
+Print objects of the &amp;lt;rate_intervention&amp;gt; class"><title>Print an object of the &lt;intervention&gt; super-class — print_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Print an object of the &lt;intervention&gt; super-class — print_intervention"><meta property="og:description" content="Print an object of the &amp;lt;intervention&amp;gt; super-class
 Print objects of the &amp;lt;contact_intervention&amp;gt; class
 Print objects of the &amp;lt;rate_intervention&amp;gt; class"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
@@ -16,12 +16,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -65,10 +65,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -94,13 +93,13 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for intervention</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for class 'intervention'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for contact_intervention</span></span>
+<span><span class="co"># S3 method for class 'contact_intervention'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for rate_intervention</span></span>
+<span><span class="co"># S3 method for class 'rate_intervention'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
     </div>
 
@@ -130,11 +129,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/vaccination.html b/reference/vaccination.html
index 5d2b648b..5c788894 100644
--- a/reference/vaccination.html
+++ b/reference/vaccination.html
@@ -5,7 +5,7 @@
 end times, as well as different vaccination rates, for each demographic group
 in the epidemic modelling scenario.
 Combine &amp;lt;vaccination&amp;gt; objects to create multi-dose vaccination regimes
-using c() on two or more &amp;lt;vaccination&amp;gt; objects."><title>Construct a new vaccination regime for an epidemic model — vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Construct a new vaccination regime for an epidemic model — vaccination"><meta property="og:description" content="Prepare a &amp;lt;vaccination&amp;gt; object that specifies a vaccination regime for use
+using c() on two or more &amp;lt;vaccination&amp;gt; objects."><title>Construct a new vaccination regime for an epidemic model — vaccination • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Construct a new vaccination regime for an epidemic model — vaccination"><meta property="og:description" content="Prepare a &amp;lt;vaccination&amp;gt; object that specifies a vaccination regime for use
 in an epidemic model.
 These objects can handle different vaccination start and
 end times, as well as different vaccination rates, for each demographic group
@@ -24,12 +24,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -73,10 +73,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -110,7 +109,7 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 <span></span>
 <span><span class="fu">is_vaccination</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># S3 method for vaccination</span></span>
+<span><span class="co"># S3 method for class 'vaccination'</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
     </div>
 
@@ -263,11 +262,11 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/validate_intervention.html b/reference/validate_intervention.html
index f7f2dcd2..0f096cf4 100644
--- a/reference/validate_intervention.html
+++ b/reference/validate_intervention.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Validate objects that inherit from the  class
-Validate objects that inherit from the  class"><title>Validate objects that inherit from the  class — validate_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Validate objects that inherit from the  class — validate_intervention"><meta property="og:description" content="Validate objects that inherit from the  class
+Validate objects that inherit from the  class"><title>Validate objects that inherit from the  class — validate_intervention • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Validate objects that inherit from the  class — validate_intervention"><meta property="og:description" content="Validate objects that inherit from the  class
 Validate objects that inherit from the  class"><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@@ -14,12 +14,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -63,10 +63,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -117,11 +116,11 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
 </div>
 
 <div class="pkgdown-footer-right">
-  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.9.9000.</p>
 </div>
 
     </footer></div>
diff --git a/reference/vector_recycling.html b/reference/vector_recycling.html
index 687ab1be..1268af10 100644
--- a/reference/vector_recycling.html
+++ b/reference/vector_recycling.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Internal functions to check whether vectors can be recycled and
-to recycle vectors."><title>Vector recyclability checks and vector recycling — vector_recycling • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Vector recyclability checks and vector recycling — vector_recycling"><meta property="og:description" content="Internal functions to check whether vectors can be recycled and
+to recycle vectors."><title>Vector recyclability checks and vector recycling — vector_recycling • epidemics</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.11/clipboard.min.js" integrity="sha512-7O5pXpc0oCRrxk8RUfDYFgn0nO1t+jLuIOQdOMRp4APB7uZ4vSjspzp5y6YDtDs4VzUSTbWzBFZ/LKJhnyFOKw==" crossorigin="anonymous" referrerpolicy="no-referrer"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Vector recyclability checks and vector recycling — vector_recycling"><meta property="og:description" content="Internal functions to check whether vectors can be recycled and
 to recycle vectors."><meta property="og:image" content="https://epiverse-trace.github.io/epidemics/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
@@ -14,12 +14,12 @@
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
     
 
-    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark"><div class="container">
+    <nav class="navbar fixed-top navbar-dark navbar-expand-lg bg-dark" data-bs-theme="dark"><div class="container">
     
     <a href="https://epiverse-trace.github.io/" class="external-link"><img src="../logo_white.svg" id="logo" alt="Epiverse-TRACE"></a>
     <a class="navbar-brand me-2" href="../index.html">epidemics</a>
 
-    <small class="nav-text text-muted me-auto version-number" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.2.0.9000</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">0.3.0</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -63,10 +63,9 @@ <h6 class="dropdown-header" data-toc-skip>Package design and architecture</h6>
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-      </ul><form class="form-inline my-2 my-lg-0" role="search">
-        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
-
-      <ul class="navbar-nav"><li class="nav-item">
+      </ul><ul class="navbar-nav"><li><form class="form-inline" role="search">
+<input type="search" class="form-control" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
+<li class="nav-item">
   <a class="external-link nav-link" href="https://github.com/epiverse-trace/epidemics/" aria-label="github">
     <span class="fab fa fab fa-github fa-lg"></span>
      
@@ -131,11 +130,11 @@ <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a><
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
+  <p>Developed by Pratik Gupte, Rosalind Eggo, Edwin Van Leeuwen.</p>
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-[{"path":"https://epiverse-trace.github.io/epidemics/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 epidemics authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"scope","dir":"Articles","previous_headings":"","what":"Scope","title":"Design Principles for epidemics","text":"epidemics aims help public health practitioners - rather research-focussed modellers - rapidly simulate disease outbreak scenarios, aims balance flexibility, performance, user-friendliness, maintainability. epidemics trades away flexibility defining model structures gain ease defining epidemic scenario components affected populations model events. epidemics attempts balance performance maintainability minimum sufficient use C++, attempting write domain-specific language (odin). broadly applicable, epidemics provides ‘library’ compartmental models adapted published literature. models focus broad types diseases settings, rather specific diseases scenarios. Thus models intended applicable range diseases.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"output","dir":"Articles","previous_headings":"","what":"Output","title":"Design Principles for epidemics","text":"function outputs expected return structure inherits <data.frame>, make processing easier users. exact structure output - whether list <data.frame>s, <data.table> <tibble>, nested version tabular data classes - yet fixed. eventual stable output type must allow users conveniently access epidemic trajectory data, identify filter intervention scenarios comparisons among , allow interoperability data science tools Tidyverse.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"package-architecture","dir":"Articles","previous_headings":"","what":"Package architecture","title":"Design Principles for epidemics","text":"Fig. 1: epidemics designed allow easy combination composable elements model structure taken library published models, sensible default parameters, allow public health practitioners conveniently model epidemic scenarios efficacy response strategies.  Fig. 2: epidemics package architecture, ODE model stack. epidemics includes multiple internal functions R C++ check inputs suitable model, cross-check inputs compatible . Function names indicate behaviour (e.g. assert_*()), similarly named functions called similar places model function bodies. Partly, reflects privileged positions model components (population, components checked), also composable elements (time-dependence) may vectorised.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"epidemic-modelling","dir":"Articles","previous_headings":"Design decisions","what":"Epidemic modelling","title":"Design Principles for epidemics","text":"notes refer broad decisions individual models – see individual model vignettes published sources modelling decisions. two broad types models: Deterministic models implemented solutions systems ordinary different equations (ODEs), Stochastic models discrete timesteps individuals move compartments probabilistically. epidemics models’ compartmental transitions fixed. Users create new links compartments, although links compartments can disallowed modifying model parameters. models’ epidemiological parameter sets unique, although parameters shared among models. can changed users although reasonable default values provided. model components - population affected epidemic, policy responses form interventions - called composable elements. Composable elements can expected modified users match situation. model components except population optional. model allows unique sets composable elements considered suitable expected use case. E.g. Ebola model allow modelling vaccination regime, considered unlikely Ebola outbreaks. allowed set composable elements subject change, open user requests. effect interventions modelled additive, multiplicative. intervention X% reduction contacts overlaps intervention Y% reduction, cumulative effect contacts \\(C\\) \\(C \\times 1 - (X + Y)\\), rather \\(C \\times (1 - X)(1 - Y)\\). Additive effects considered easier users understand multiplicative effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"ode-systems-and-models","dir":"Articles","previous_headings":"Design decisions","what":"ODE systems and models","title":"Design Principles for epidemics","text":"common method defining solving ODEs R write ODE system R pass solvers deSolve::lsoda() deSolve package. opted approach (referred ‘R-deSolve’). possible write ODE compartmental transitions C++, expose C++ code R, eventually passing ODE system deSolve solvers (referred ‘Rcpp-deSolve’). also opted approach, involves substantial interconversion complex objects structured lists (model composable elements) R C++ solver timestep, reducing performance. ODE systems written C++, solved using Boost odeint solvers fixed step sizes. means within call model_*(), R objects converted use C++ (scalar arguments case), passed back forth multiple times. odeint provided package BH (Boost Headers), making convenient use Rcpp packages. r2sundials package provides Rcpp-friendly interface SUNDIALS ODE solvers, documentation less clear overall, seems recommend use RcppArmadillo RcppXPtrUtils; evaluated use. odeint imposes certain constraints ODE systems. functionality easily define ‘events’ (also called ‘callbacks’) combine ODE system. means ODE systems encapsulate information timing events (interventions) effect. Equations describing right-hand side model ODE systems \\(x' = f(x)\\) thus written structs overloaded function call operator makes FunctionObject types. struct thus holds epidemiological parameters composable elements, passed reference operations, reducing copying. See simple example Boost documentation. can passed function solver, epidemiological parameters calculated solver timestep function time composable elements (applicable). epidemics relies Eigen C++ library provided RcppEigen represent matrices initial conditions. Eigen matrices among types accepted initial states odeint solvers. Alternatives include Boost Basic Linear Algebra Library (uBLAS) standard library arrays vectors; partial list - include Eigen - provided Boost, Armadillo matrices may also supported. use Eigen matrices Eigen offers broad well documented support matrix operations, easy conversion Rcpp types, also conforms previous use Eigen finalsize. models’ C++ code two levels underlie R source code - C++ source code C++ headers. make header code (model ODEs helper functions) shareable can re-used Rcpp packages explored blog post. epidemics defines C++ namespaces package headers clearly indicate certain functionalities sit. model structures namespace epidemics, namespaces vaccination, intervention, time_dependence contain C++ code handle composable elements (calculating effect cumulative interventions). namespace odetools defines initial state type, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"stochastic-models","dir":"Articles","previous_headings":"Design decisions","what":"Stochastic models","title":"Design Principles for epidemics","text":"epidemics includes single stochastic model adapted earlier implementations, hence common design decisions stochastic models likely worked models added. input output types correspond ODE model types. model written R although may change future.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"classes","dir":"Articles","previous_headings":"Design decisions","what":"Classes","title":"Design Principles for epidemics","text":"major composable elements bundled custom S3 classes inherit lists, expected understandable elements epidemic response: <population>, <intervention> superclass, <vaccination>. composable elements take form named, structured lists. defined classes expected less used, used advanced modellers comfortable working lists directly. key element composable elements inheriting lists can easily handled within C++ code interpreted Rcpp lists. matrix objects referring demography-group coefficients follow ‘demography--rows’ pattern finalsize, rows represent demography groups, columns represent coefficients. includes initial conditions matrix <population>s, columns epidemiological compartments, also vaccination rates <vaccination>, contacts reductions <contacts_intervention>s. Interventions may <contacts_intervention> <rate_intervention> class, inherit abstract super-class <intervention>. inheritance structure chosen maintain coherence intervention types, keep option open unifying classes single concrete type future. composable elements except population optional. Model functions internally generate dummy values composable elements allowed model, required C++ code. <intervention> <vaccination> objects may combined objects (sub)-class using c() method (sub)-class, resulting object (sub)-class. interpretation class however slightly different: <intervention>: Combining two interventions sub-class understood represent combined application multiple epidemic response strategies, e.g. closing schools also closing workplaces, introducing mask mandates different intervals. <vaccination>: Combining two vaccination objects results two-dose vaccination regime, rather two separate vaccination campaigns (delivering single dose). epidemics focuses initial pandemic response phase vaccination expected available scale, rather long-term vaccination campaigns endemic infections.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"function-vectorisation","dir":"Articles","previous_headings":"Design decisions","what":"Function vectorisation","title":"Design Principles for epidemics","text":"epidemics moving towards allowing vectors lists passed model function arguments, easily allow incorporation parameter uncertainty comparisons multiple scenarios (maintaining comparability across scenarios function call). Consequently, function call may consist many 1000s model runs (see PR #176 vignette scenario modelling). model epidemiological parameters allowed passed numeric vectors (currently ODE models). includes time_end, allows runs different durations within single function call. use case taken report aimed calculate epidemic size given period uncertainty start time (hence duration). epidemics follows Tidyverse rules vector recycling epidemiological parameters. Arguments intervention vaccination accepting composable elements allowed passed lists inputs. case intervention, list lists, element list <intervention> objects (typically one <contacts_intervention> variable number <rate_intervention>s): referred intervention set. composable elements may currently scalar values, may change future (see issue #181 passing lists populations). Model functions internally create combinations composable elements, combination referred scenario, also combine scenario set epidemiological parameters. ensure comparability across scenarios.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"miscellaneous-decisions","dir":"Articles","previous_headings":"","what":"Miscellaneous decisions","title":"Design Principles for epidemics","text":"epidemics follows finalsize example following Google’s C++ code style, using Cpplint Cppcheck static code analysis options Clang-tidy work well Rcpp code; see blog post . Function naming: Function names aim contain verbs indicate function behaviour. Internal input checking functions follow checkmate naming style (e.g. assert_*()). Function naming: Internal functions aim begin . (e.g. .model_default_cpp()) clearly indicate direct use.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"dependencies","dir":"Articles","previous_headings":"","what":"Dependencies","title":"Design Principles for epidemics","text":"aim restrict number hard dependencies maintaining user-friendliness. checkmate: useful input-checking package used across Epiverse packages; cli glue: convenience packages pretty printing methods; reconsidered lighten package dependencies; data.table: lightweight dependency handle data model outputs, especially used nested list column functionality. Rcpp: provides linking C++ R; RcppEigen: provides matrix classes suitable use Boost odeint; BH: provides Boost odeint ODE solvers; stats utils: already installed R, used Ebola model, hence liable removed future. wider range packages taken soft dependencies make vignettes user-friendly. bench: benchmark epidemics finalsize; bookdown, knitr, rmarkdown: packages generate vignettes format ; dplyr, tibble, tidyr: show processing model outputs; EpiEstim: show links upstream packages estimate R vignette; finalsize: comparison epidemics vignette; ggplot2, scales, colorspace: packages plotting; socialmixr: obtain social contacts matrices; spelling: spell-checking; testthat (>= 3.0.0): unit tests; withr: seed management.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"contribute","dir":"Articles","previous_headings":"","what":"Contribute","title":"Design Principles for epidemics","text":"special requirements contributing epidemics, contributions new models clearly motivated, fall within scope package, target disease type situation already covered existing models, ideally already peer-reviewed. general, please follow package contributing guide.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/epidemics.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Getting started with epidemic scenario modelling components","text":"Prepare population contact data. Prepare initial conditions age group. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE ) #> Using POLYMOD social contact data. To cite this in a publication, use the 'get_citation()' function #> Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix)  # view contact matrix and demography contact_matrix #>                   #> contact.age.group     [,1]     [,2]     [,3] #>           [0,20)  7.883663 2.794154 1.565665 #>           [20,40) 3.120220 4.854839 2.624868 #>           40+     3.063895 4.599893 5.005571  demography_vector #>   [0,20)  [20,40)      40+  #> 14799290 16526302 28961159 # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix)  # view initial conditions initial_conditions #>                S E     I R V #> [0,20)  0.999999 0 1e-06 0 0 #> [20,40) 0.999999 0 1e-06 0 0 #> 40+     0.999999 0 1e-06 0 0 uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )  uk_population #> <population> object #>  #>  Population name:  #> \"UK\" #>  #>  Demography  #> [0,20): 14,799,290 (20%) #> [20,40): 16,526,302 (30%) #> 40+: 28,961,159 (50%) #>  #>  Contact matrix  #>                   #> contact.age.group   [0,20)  [20,40)      40+ #>           [0,20)  7.883663 2.794154 1.565665 #>           [20,40) 3.120220 4.854839 2.624868 #>           40+     3.063895 4.599893 5.005571"},{"path":"https://epiverse-trace.github.io/epidemics/articles/epidemics.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Getting started with epidemic scenario modelling components","text":"","code":"# run an epidemic model using `epidemic` output <- model_default(   population = uk_population,   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/epidemics.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Getting started with epidemic scenario modelling components","text":"Plot epidemic time, showing number individuals exposed infected compartments.","code":"# plot figure of epidemic curve filter(output, compartment %in% c(\"exposed\", \"infectious\")) %>%   ggplot(     aes(       x = time,       y = value,       col = demography_group,       linetype = compartment     )   ) +   geom_line() +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 500e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"different-use-cases-of-finalsize-and-epidemics","dir":"Articles","previous_headings":"","what":"Different use cases of finalsize and epidemics","title":"Reducing parameters required for final size estimation","text":"finalsize epidemics can used calculate epidemic final size, aimed different use cases. finalsize assumes infection population characteristics fixed initial conditions. infection, includes properties transmission rate, population, includes social contacts demographic groups, proportion demographic groups specific levels susceptibility infection. advantage finalsize requires define initial transmission rate infection susceptibility population, rather time-dependent processes drive epidemic shape, duration infectiousness latent period infection. questions relating epidemic shape, rather shape, results much simpler set inputs. However, also means finalsize used model temporal dynamics epidemic response, used answer policy questions temporal component, implement interventions. epidemics includes number scenario models, assumptions. models allow modification initial characteristics outbreak due range events. infection, includes interventions (masking treatments) reduce number forward transmissions deaths, also seasonal effects may increase decrease transmission rate. population, initial conditions social contacts can influenced interventions well. makes much easier model temporal dynamics public-health policy decisions taken epidemic response epidemics many features allow modelling. However, requires inputs defined, including time-dependent infections processes. can also difficult model scenarios complicated susceptibility structure required, demographic groups underlying immunity infection due past exposure vaccination. Thus epidemics likely especially useful outbreaks novel pathogens (Covid-19 pandemic) little population immunity infection. easier configure finalsize ---box scenarios complex demographic patterns underlying susceptibility (immunity ) infection, potentially due history previous outbreaks policy responses (vaccination). Thus, model temporal dynamics, can quickly provide useful initial estimates final size outbreaks, without write compartmental models implement multiple policy decisions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"converting-scenarios-between-finalsize-and-epidemics","dir":"Articles","previous_headings":"","what":"Converting scenarios between finalsize and epidemics","title":"Reducing parameters required for final size estimation","text":", show example show model similar scenario using finalsize epidemics. example, might want study full epidemic dynamics future, start simpler final size estimate meantime. show build equivalent models, allowing extensions model epidemic temporal dynamics (using epidemics) later. illustration, use epidemics model effect vaccination trajectory epidemic. finalsize allow implementation dynamic vaccination calendar, can model reduced susceptibility infection population, due prior vaccination. two methods comparable model vaccination epidemics occurring main wave epidemic, sets underlying susceptibility.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"prepare-population-and-model-parameters","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Prepare population and model parameters","title":"Reducing parameters required for final size estimation","text":"first prepare population (modelled U.K.), initial conditions, model parameters, passing epidemics::model_default(). example include interventions vaccination regimes. Code prepare model inputs folded brevity. See “Get started” vignette explanation prepare inputs. model spread influenza pandemic potential, assuming $R_0 = $ 1.5, pre-infectious period 3 days, infectious period 7 days. leads following model parameters transmission rate \\(\\beta\\), rate transition exposed infectious \\(\\sigma\\), recovery rate \\(\\gamma\\).","code":"# load contact and population data from socialmixr::polymod polymod <- polymod contact_data <- contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix)  # initial conditions: one in every 1 million is infected initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions ) rownames(initial_conditions) <- rownames(contact_matrix) # prepare the population to model as affected by the epidemic # the contact_matrix, demography_vector, and initial_conditions # have been prepared in the folded code above uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )  # view the population uk_population #>  #>  Population name:  #>  Demography  #> [0,20): 14,799,290 (20%) #> [20,40): 16,526,302 (30%) #> 40+: 28,961,159 (50%) #>  #>  Contact matrix  #>                   #> contact.age.group   [0,20)  [20,40)      40+ #>           [0,20)  7.883663 2.794154 1.565665 #>           [20,40) 3.120220 4.854839 2.624868 #>           40+     3.063895 4.599893 5.005571 # simulate pandemic parameters transmission_rate <- 1.5 / 7 infectiousness_rate <- 1 / 3 recovery_rate <- 1 / 7"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"implementing-vaccination-in-epidemics","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Implementing vaccination in epidemics","title":"Reducing parameters required for final size estimation","text":"simplicity, implement vaccination regime vaccines delivered individuals age 40 course roughly six months (150 days) main epidemic peak. assume 1 every 1000 individuals age group vaccinated every day; translates approximately 28,900 individuals per day. assume vaccination non-leaky, protecting vaccinated individuals infection, due model structure ‘default’ SEIR-V model epidemics use . New modelling vaccination using epidemics? may help read “Modelling vaccination campaign” vignette first. first create <vaccination> object represent vaccination regime. pass vaccination regime epidemic function optional vaccination argument, model 600 days epidemic. obtain ‘final’ epidemic size using epidemics::epidemic_size().","code":"# prepare a vaccination object vaccinate_elders <- vaccination(   name = \"vaccinate elders\",   time_begin = matrix(1, nrow(contact_matrix)),   time_end = matrix(150, nrow(contact_matrix)),   nu = matrix(c(0.0, 0.0, 0.001)) ) # model epidemic with vaccination prior to the main epidemic wave output <- model_default(   population = uk_population,   transmission_rate = transmission_rate,   infectiousness_rate = infectiousness_rate,   recovery_rate = recovery_rate,   vaccination = vaccinate_elders,   time_end = 600, increment = 1.0 )  # Calculate the epidemic size using the helper function finalsize_dat <- tibble(   demography_group = names(demography_vector),   value = epidemic_size(output) / demography_vector )  # View the data finalsize_dat #> # A tibble: 3 × 2 #>   demography_group value #>   <chr>            <dbl> #> 1 [0,20)           0.617 #> 2 [20,40)          0.525 #> 3 40+              0.343"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"calculating-individuals-vaccinated-in-epidemic-model","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Calculating individuals vaccinated in epidemic model","title":"Reducing parameters required for final size estimation","text":"compare results ODE model analytical method, necessary set population’s susceptibility demography--susceptibility matrices reflect proportion individuals age group vaccinated outbreak. , need calculate total proportion individuals age group vaccinated end epidemic model run.","code":"# Proportion of the individuals vaccinated p_vacc <- filter(output, compartment == \"vaccinated\", time == max(time)) p_vacc <- p_vacc$value / demography_vector"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"implementing-vaccination-in-finalsize","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Implementing vaccination in finalsize","title":"Reducing parameters required for final size estimation","text":"use proportion individuals vaccinated age group set matrices pass susceptibility p_susceptibility arguments finalsize::final_size(). New final size estimation heterogeneity susceptibility infection? may help read “Modelling heterogeneous susceptibility” vignette, “Guide constructing susceptibility matrices” finalsize first. create susceptibility matrix two groups, ‘unvaccinated’, full susceptibility, ‘vaccinated’, immune infection. create demography--susceptibility matrix reflect individuals >40 age group vaccinated. Since vaccination implemented age groups, assume individuals groups fully susceptible. calculate expected final size using modified susceptibility matrices, combine data output ODE model previous example. need scale contact matrix appropriately. can print data compare values, similar. However, note epidemics::epidemic_size() can used time point epidemic, finalsize::final_size() returns size end epidemic, showing epidemics suitable examine temporal dynamics.","code":"# create the susceptibility matrix susceptibility <- matrix(   data = 1,   nrow = length(demography_vector),   ncol = 2,   dimnames = list(     names(demography_vector),     c(\"unvaccinated\", \"vaccinated\")   ) ) # Second column holds the vaccinated (who are protected fully) susceptibility[, \"vaccinated\"] <- 0  # Assume susceptibility varies within age groups p_susceptibility <- matrix(   data = 1.0,   nrow = length(demography_vector),   ncol = 2,   dimnames = list(     names(demography_vector),     c(\"unvaccinated\", \"vaccinated\")   ) ) p_susceptibility[, \"vaccinated\"] <- p_vacc p_susceptibility[, \"unvaccinated\"] <- 1 - p_vacc # Define population in each age group scalar <- max(eigen(contact_data$matrix)$values) contact_matrix <- (contact_data$matrix / demography_vector) / scalar # Calculate the proportion of individuals infected in each age group dat1 <- final_size(   r0 = 1.5,   contact_matrix = contact_matrix,   demography_vector = demography_vector,   susceptibility = susceptibility,   p_susceptibility = p_susceptibility )  # Final size returns the proportion infected in each susceptibility group # (i.e. non vaccinated and vaccinated) # here we calculate the proportion of infected for the age group as a whole dat3 <- dat1 %>%   select(     -susceptibility,     final_size = p_infected   ) %>%   filter(susc_grp == \"unvaccinated\") %>%   select(-susc_grp)  fs <- dat3$unvaccinated * p_susceptibility[, \"unvaccinated\"]  finalsize_dat <- finalsize_dat %>%   select(demo_grp = demography_group, seir_v = value) %>%   left_join(dat3) finalsize_dat #> # A tibble: 3 × 3 #>   demo_grp seir_v final_size #>   <chr>     <dbl>      <dbl> #> 1 [0,20)    0.617      0.660 #> 2 [20,40)   0.525      0.542 #> 3 40+       0.343      0.272 # note that epidemic_size() returns the absolute values # epidemic size after 10% of the epidemic model run epidemic_size(data = output, stage = 0.1) #>   [0,20)  [20,40)      40+  #> 574.4348 488.3563 585.5760  # epidemic size at 50% epidemic_size(data = output, stage = 0.5) #>  [0,20) [20,40)     40+  #> 5565772 4890178 5254726"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"consideration-of-computational-speed","dir":"Articles","previous_headings":"","what":"Consideration of computational speed","title":"Reducing parameters required for final size estimation","text":"important reason use finalsize final size calculations may speed — finalsize::final_size() much faster epidemics::epidemic_size() applied epidemics::model_default(). makes much suitable high-performance applications fitting data. benchmarking shows total time taken 1,000 runs using methods low, methods used scan across multiple values input parameters, dealing parameter uncertainty. Note model runs using epidemics implement complex compartmental structure, multiple interventions vaccination regimes likely slower example shown . However, users choose finalsize assumptions underlying final size calculation met. example, cases vaccinations concurrent large number infections, interventions applied reduce transmission, final size assumptions met. cases, users advised use dynamical model epidemics instead.","code":"# run benchmarks using {bench} benchmark <- mark(   analytical_method = final_size(     r0 = 1.5,     contact_matrix = contact_matrix,     demography_vector = demography_vector,     susceptibility = susceptibility,     p_susceptibility = p_susceptibility   ),   ode_model = epidemic_size(     model_default(       population = uk_population,       transmission_rate = transmission_rate,       infectiousness_rate = infectiousness_rate,       recovery_rate = recovery_rate,       vaccination = vaccinate_elders,       time_end = 600, increment = 1.0     )   ),   iterations = 1000,   time_unit = \"s\",   check = FALSE )  # view the total time for 1000 runs in seconds select(as_tibble(benchmark), expression, total_time) #> # A tibble: 2 × 2 #>   expression        total_time #>   <bch:expr>             <dbl> #> 1 analytical_method      0.456 #> 2 ode_model             10.1"},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_diphtheria.html","id":"modelling-an-outbreak-with-pre-existing-immunity","dir":"Articles","previous_headings":"","what":"Modelling an outbreak with pre-existing immunity","title":"Modelling a diphtheria outbreak in a humanitarian camp setting","text":"create population object corresponding Kutupalong camp Cox’s Bazar, Bangladesh 2017-18, rounded nearest 100, described Additional file 1 provided Finger et al. (2019). population three age groups, < 5 years, 5 – 14 years, \\(\\geq\\) 15 years. assume one individual infectious age group. assume, following Finger et al. (2019), 20% 5 – 14 year-olds vaccinated (immune ) diphtheria prior start outbreak, coverage much lower among age groups. run model default parameters, assuming : diphtheria \\(R_0\\) 4.0 mean infectious period 4.5 days, giving transmission rate (\\(\\beta\\)) 0.889; diphtheria pre-infectious incubation period 3 days, giving infectiousness rate (\\(\\sigma\\)) 0.33; recovery rate diphtheria 0.33. also make several assumptions regarding clinical progression reporting. Specifically: case reporting (3% infections reported cases), proportion reported cases needing hospitalisation (1%), time taken cases needing hospitalisation seek admitted hospital (5 days, giving daily hospitalisation rate 0.2 among cases), time spent hospital (5 days, giving daily hospitalisation recovery rate 0.2). Finally, assume interventions seasonal effects affect dynamics transmission outbreak. run model plot outcomes. Figure 1: Model results single run showing number individuals infectious diphtheria 100 days outbreak.","code":"# three age groups with five compartments SEIHR n_age_groups <- 3 demography_vector <- c(83000, 108200, 224600) initial_conditions <- matrix(0, nrow = n_age_groups, ncol = 5)  # 1 individual in each group is infectious initial_conditions[, 1] <- demography_vector - 1 initial_conditions[, 3] <- rep(1, n_age_groups)  # camp social contact rates are assumed to be uniform within and between # age groups camp_pop <- population(   contact_matrix = matrix(1, nrow = n_age_groups, ncol = n_age_groups),   demography_vector = demography_vector,   initial_conditions = initial_conditions / demography_vector )  camp_pop #>  #>  Population name:  #>  Demography  #> Dem. grp. 1: 83,000 (20%) #> Dem. grp. 2: 108,200 (30%) #> Dem. grp. 3: 224,600 (50%) #>  #>  Contact matrix  #>              Dem. grp. 1: Dem. grp. 2: Dem. grp. 3: #> Dem. grp. 1:            1            1            1 #> Dem. grp. 2:            1            1            1 #> Dem. grp. 3:            1            1            1 # 20% of 5-14 year-olds are vaccinated prop_vaccinated <- c(0.05, 0.2, 0.05) data <- model_diphtheria(   population = camp_pop,   prop_vaccinated = prop_vaccinated ) filter(data, compartment == \"infectious\") %>%   ggplot() +   geom_line(     aes(time, value, colour = demography_group)   ) +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\",     labels = c(\"<5\", \"5-15\", \">15\")   ) +   expand_limits(     x = c(0, 101)   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     y = \"Individuals infectious\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_diphtheria.html","id":"modelling-an-outbreak-with-changing-population-sizes","dir":"Articles","previous_headings":"","what":"Modelling an outbreak with changing population sizes","title":"Modelling a diphtheria outbreak in a humanitarian camp setting","text":"now model outbreak, increase susceptible individuals towards end outbreak, illustrate effect influx non-immune individuals outbreak dynamics. example, assume prior immunity among new arrivals population. prepare population change schedule named list giving times change, corresponding changes demographic group. Note model assumes changes apply susceptible compartment, assume wider population entering camp yet affected diphtheria (.e. infected recovered arrival), already infected hospitalised individuals leave camp. , population size camp increases 75% overall, similar reported values Kutupalong camp scenario (Finger et al. 2019). Figure 2: Model results single run showing number individuals infectious diphtheria 100 days outbreak, increase camp population size. Shaded blue region shows number individuals susceptible infection (right-hand side Y axis). example shows increase number susceptibles population can lead rise transmission potential infection therefore extend duration outbreak.","code":"# susceptibles increase by about 12%, 92%, and 89% of initial sizes pop_change <- list(   time = 70,   values = list(     c(1e4, 1e5, 2e5)   ) ) data <- model_diphtheria(   population = camp_pop,   population_change = pop_change )  # summarise population change in susceptibles data_pop_size <- filter(data, compartment == \"susceptible\") %>%   group_by(time) %>%   summarise(     total_susceptibles = sum(value)   ) ggplot() +   geom_area(     data = data_pop_size,     aes(time, total_susceptibles / 10),     fill = \"steelblue\", alpha = 0.5   ) +   geom_line(     data = filter(data, compartment == \"infectious\"),     aes(time, value, colour = demography_group)   ) +   geom_vline(     xintercept = pop_change$time,     colour = \"red\",     linetype = \"dashed\",     linewidth = 0.2   ) +   annotate(     geom = \"text\",     x = pop_change$time,     y = 20e3,     label = \"Population increase\",     angle = 90,     vjust = \"inward\",     colour = \"red\"   ) +   scale_y_continuous(     labels = scales::comma,     sec.axis = dup_axis(       trans = function(x) x * 10,       name = \"Individuals susceptible\"     )   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group (individuals infectious)\",     labels = c(\"<5\", \"5-15\", \">15\")   ) +   expand_limits(     x = c(0, 101)   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     y = \"Individuals infectious\"   )"},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Prepare population data — model, need total population size initial conditions. can create <population> object dummy values contact matrix, assign total size demography vector. prepare population total size 14 million, corresponding population Guinea, West African country 2014 Ebola virus epidemic originated. assume 1 person initially infected infectious, 10 people exposed yet become infectious.","code":"population_size <- 14e6  # prepare initial conditions as proportions initial_conditions <- c(   S = population_size - 11, E = 10, I = 1, H = 0, F = 0, R = 0 ) / population_size # prepare a <population> object guinea_population <- population(   name = \"Guinea\",   contact_matrix = matrix(1), # note dummy value   demography_vector = 14e6, # 14 million, no age groups   initial_conditions = matrix(     initial_conditions,     nrow = 1   ) )  guinea_population #>  #>  Population name:  #>  Demography  #> Dem. grp. 1: 14,000,000 (100%) #>  #>  Contact matrix  #>              Dem. grp. 1: #> Dem. grp. 1:            1"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"prepare-model-parameters","dir":"Articles","previous_headings":"","what":"Prepare model parameters","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"use default model parameters, beginning \\(R_0\\) taken value estimated ebola Guinea (Althaus 2014). assume ebola mean infectious period 12 days, time exposure symptom onset — pre-infectious period — 5 days. Together, give following values: Transmission rate (\\(\\beta\\)): 0.125, Infectiousness rate (\\(\\gamma^E\\) Getz Dougherty (2018)): 0.4, Removal rate (\\(\\gamma^\\) Getz Dougherty (2018)): 0.1667 model yet explicit “deaths” compartment, rather, “removed” compartment holds individuals recovered died buried safely. Functionally, similar part model dynamics. assume 10% infectious individuals hospitalised, hospitalisation achieves modest 30% reduction transmission hospitalised individuals still susceptible. assume also deaths hospital lead ebola-safe funerals, infections result . assume infectious individuals hospitalised die community, funerals potentially ebola-safe. assume transmission rate ebola funerals 50% baseline transmission rate. can also interpreted proportion funerals ebola-safe.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"run model using function model_ebola(). C++ equivalent model, found much faster R-version, made available users. model run 100 days, data reported day. appropriate period obtain initial predictions outbreak, response efforts non-pharmaceutical interventions vaccination campaigns likely launched bring outbreak control.","code":"# set seed to get consistent results set.seed(0)  # run the epidemic model using `epidemic` # we call the model \"ebola\" from the library data <- model_ebola(   population = guinea_population,   time_end = 100 )  # view the head of the output head(data) #>   time demography_group  compartment    value #> 1    1     demo_group_1  susceptible 13999989 #> 2    1     demo_group_1      exposed       10 #> 3    1     demo_group_1   infectious        1 #> 4    1     demo_group_1 hospitalised        0 #> 5    1     demo_group_1      funeral        0 #> 6    1     demo_group_1      removed        0"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"plot ebola epidemic time, showing number individuals exposed infectious. Figure 1: Model results single run showing number individuals exposed infectious compartments 100 days outbreak. model assumes 1 initially infectious person exposed 10 others.","code":"# plot figure of epidemic curve filter(data, compartment %in% c(\"exposed\", \"infectious\")) %>%   ggplot(     aes(       x = time,       y = value,       colour = compartment     )   ) +   geom_line() +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = NULL,     labels = c(\"Exposed\", \"Infectious\")   ) +   expand_limits(     x = c(0, 101)   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"consensus-estimates-from-multiple-model-iterations","dir":"Articles","previous_headings":"","what":"Consensus estimates from multiple model iterations","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Since ebola model stochastic one, model results vary run. can run model multiple times — , 100 times — plot number infectious people, get consensus idea ebola outbreak might look like. plot data. Figure 2: Model results 100 runs showing number individuals infectious compartments 100 days outbreak. models assume 1 initially infectious person exposed 10 others. simple summary using mean (black line standard error shaded red regions), plotted individual model runs (grey) show can wide variation individual outbreak trajectories. observe model stochasticity leads wide variation model outcomes, simulation replicates lead exponential growth outbreak within first 100 days. However, number replicates, outbreak low daily incidence within simulation time, although replicates might show exponential growth later. can find ‘final size’ replicate using epidemic_size() function original simulation data. Note final size refers final size 365 days, duration simulation. Figure 3: Histogram final outbreak sizes 100 ebola outbreaks. taken 100 model runs presented earlier figure, show outbreaks may affect fewer 500 individuals within first 100 days. see replicates affect 600 individuals within first 100 days, replicates fewer 500 cases, suggesting responses halt spread ebola quite effective real outbreaks.","code":"# set seed for consistent output set.seed(1)  # run the simulation 100 times data <- lapply(   X = seq(100),   FUN = function(x) {     data <- model_ebola(       population = guinea_population,       time_end = 100     )      # add replicate number and return data     data$replicate <- x     data   } )  # use data.table to collect the data data_timeseries <- bind_rows(data) filter(data_timeseries, compartment == \"infectious\") %>%   ggplot() +   geom_line(     aes(time, value, group = replicate),     alpha = 0.3, colour = \"grey50\"   ) +   stat_summary(     aes(time, value),     geom = \"ribbon\",     fill = \"red\", alpha = 0.5   ) +   stat_summary(     aes(time, value),     geom = \"line\"   ) +   scale_y_continuous(     labels = scales::comma   ) +   expand_limits(     x = c(0, 101)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     y = \"Individuals infectious with ebola\"   ) # apply the function over each replicate data_final_size <- lapply(   X = data,   FUN = epidemic_size, include_deaths = FALSE, by_group = FALSE ) data_final_size <- unlist(data_final_size) # plot a histogram of the replicates ggplot() +   geom_histogram(     aes(data_final_size),     fill = \"steelblue\"   ) +   scale_x_continuous(     labels = scales::comma   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Epidemic size at 100 days\",     y = \"Number of replicates\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"applying-interventions-that-reduce-transmission","dir":"Articles","previous_headings":"","what":"Applying interventions that reduce transmission","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"intervention reduces transmission can applied passing <rate_intervention> transmission rate parameter, beta. begin initial simple example models intervention begins 15 days outbreak, reduces transmission 20%. can pass intervention model function’s intervention argument. Figure 4: Effect implementing intervention reduces transmission 30% ebola outbreak. intervention begins 15th day (dotted vertical line), active remainder model duration. Applying intervention leads many fewer individuals infectious ebola outbreak. see applying intervention reduces transmission can effective reducing number individuals infected outbreak.","code":"# create an intervention on the transmission rate reduce_transmission <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.2 ) # set a seed for comparison with the baseline model set.seed(0)  # run the epidemic model and save data as the baseline data_baseline <- model_ebola(   population = guinea_population,   time_end = 100 )  set.seed(0) # note that the intervention is passed within a list, # where it is named for the rate it is targeting data_intervention <- model_ebola(   population = guinea_population,   intervention = list(     transmission_rate = reduce_transmission   ),   time_end = 100 )  # assign scenario names data_baseline$scenario <- \"baseline\" data_intervention$scenario <- \"intervention\"  # bind the data together data_scenarios <- bind_rows(data_baseline, data_intervention) filter(data_scenarios, compartment == \"removed\") %>%   ggplot() +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(time, value, colour = scenario)   ) +   scale_colour_brewer(     palette = \"Set1\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Intervention\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"modelling-the-roll-out-of-vaccination","dir":"Articles","previous_headings":"","what":"Modelling the roll-out of vaccination","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"can also model rollout vaccination EVD, model structured differently models epidemics, vaccination must modelled differently . model_ebola() accept vaccination regime <vaccination> object, can still model effect vaccination gradual decrease transmission rate \\(\\beta\\) time. done using time dependence functionality epidemics. New implementing parameter time dependence epidemics? may help read vignette time dependence functionality first! first define function suitable time_dependence argument. function assumes baseline transmission rate ebola decreases time, 5% reduction day due vaccination. Figure 5: Effect implementing vaccination regime gradually reduces ebola transmission time, using time dependence functionality. Similar functionality can used model parameters flexibly allowed <rate_intervention> class.","code":"# we assume a maximum time of 100 days, and a 5% daily reduction # we assume that this vaccination begins on the 15th day time_dep_vax <- function(     time, x, max_time = 100, time_start = 15,     reduction = 0.05) {   if (time < time_start) {     x   } else {     x * ((1.0 - reduction)^(time / max_time))   } } # set a seed for comparison with the baseline model set.seed(0) # note that the intervention is passed within a list, # where it is named for the rate it is targeting data_apply_vax <- model_ebola(   population = guinea_population,   time_dependence = list(     transmission_rate = time_dep_vax   ),   time_end = 100 )  # assign scenario name data_apply_vax$scenario <- \"apply_vaccination\"  # bind the data together data_scenarios <- bind_rows(data_baseline, data_apply_vax) filter(data_scenarios, compartment == \"removed\") %>%   ggplot() +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(time, value, colour = scenario)   ) +   scale_colour_brewer(     palette = \"Set1\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Vaccination campaign\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"modelling-a-multi-pronged-ebola-response","dir":"Articles","previous_headings":"","what":"Modelling a multi-pronged ebola response","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Since EVD severe disease high case fatality risk, responses outbreak may require simultaneous implementation number measures reduce transmission end outbreak quickly. can use EVD model existing functionality epidemics model implementation multi-pronged response ebola aims improve: detection treatment cases, safety hospitals risk community transmission, safety funeral practices reduce risk transmission dead bodies. , show effects interventions separately, showing combined effect.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"improving-hospitalisation","dir":"Articles","previous_headings":"Modelling a multi-pronged ebola response","what":"Improving hospitalisation","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"first model intervention begins 15 days outbreak, reduces proportion individuals infectious community 30%, thus improving proportion hospitalised. can pass interventions model function’s intervention argument named list, names indicating model parameters target. Figure 6: Effect implementing intervention reduces proportion infectious cases community transferring hospitalisation setting.","code":"# create an intervention on the transmission rate improve_hospitalisation <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.3 ) # set a seed for comparison with the baseline model set.seed(0) # note that the intervention is passed within a list, # where it is named for the rate it is targeting data_improve_hosp <- model_ebola(   population = guinea_population,   intervention = list(     prop_community = improve_hospitalisation   ),   time_end = 100 )  # assign scenario name data_improve_hosp$scenario <- \"improve_hosp\"  # bind the data together data_scenarios <- bind_rows(data_baseline, data_improve_hosp) filter(data_scenarios, compartment == \"removed\") %>%   ggplot() +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(time, value, colour = scenario)   ) +   scale_colour_brewer(     palette = \"Set1\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Improved hospitalisation\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"improve-etu-safety","dir":"Articles","previous_headings":"Modelling a multi-pronged ebola response","what":"Improve ETU safety","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"next model intervention improve safety ETUs reducing transmission risk 70%, alongside earlier improvement hospitalisation. Figure 7: Effect implementing intervention reduces risk ebola transmission hospitalisation context. Note reason intervention little effect likely effective proportion cases hospitalised high. model, large majority cases remain community, improving safety ETUs effective intervention.","code":"# create an intervention on the transmission rate improve_etu_safety <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.7 ) # set a seed for comparison with the baseline model set.seed(0) # note that the intervention is passed within a list, # where it is named for the rate it is targeting data_improve_etu <- model_ebola(   population = guinea_population,   intervention = list(     etu_risk = improve_etu_safety   ),   time_end = 100 )  # assign scenario name data_improve_etu$scenario <- \"improve_etu\"  # bind the data together data_scenarios <- bind_rows(data_baseline, data_improve_etu) filter(data_scenarios, compartment == \"removed\") %>%   ggplot() +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(time, value, colour = scenario)   ) +   scale_colour_brewer(     palette = \"Set1\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Improve ETU safety\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"improve-funeral-safety","dir":"Articles","previous_headings":"Modelling a multi-pronged ebola response","what":"Improve funeral safety","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"next model intervention improve safety funeral practices, reducing transmission risk associated funerals 50%. Figure 8: Effect implementing intervention reduces risk ebola transmission funeral context.","code":"# create an intervention on the transmission rate reduce_funeral_risk <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.5 ) # set a seed for comparison with the baseline model set.seed(0) # note that the intervention is passed within a list, # where it is named for the rate it is targeting data_improve_funeral <- model_ebola(   population = guinea_population,   intervention = list(     funeral_risk = reduce_funeral_risk   ),   time_end = 100 )  # assign scenario name data_improve_funeral$scenario <- \"improve_funeral\"  # bind the data together data_scenarios <- bind_rows(data_baseline, data_improve_funeral) filter(data_scenarios, compartment == \"removed\") %>%   ggplot() +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(time, value, colour = scenario)   ) +   scale_colour_brewer(     palette = \"Set1\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Improve funeral safety\")   ) +   scale_y_sqrt() +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"combined-interventions","dir":"Articles","previous_headings":"Modelling a multi-pronged ebola response","what":"Combined interventions","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Figure 9: Effect implementing multiple simultaneous interventions reduce transmission ebola outbreak, beginning 15th day (dotted vertical line), remaining active remainder model duration. Applying interventions substantially reduces final size outbreak, potential plateau outbreak size reached 100 days.","code":"# set a seed for comparison with the baseline model set.seed(0) # note that the intervention is passed within a list, # where it is named for the rate it is targeting data_combined_interventions <- model_ebola(   population = guinea_population,   intervention = list(     transmission_rate = reduce_transmission,     prop_community = improve_hospitalisation,     etu_risk = improve_etu_safety,     funeral_risk = reduce_funeral_risk   ),   time_end = 100 )  # assign scenario name data_combined_interventions$scenario <- \"combined_interventions\"  # bind the data together data_scenarios <- bind_rows(data_baseline, data_combined_interventions) filter(data_scenarios, compartment == \"removed\") %>%   ggplot() +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(time, value, colour = scenario)   ) +   scale_colour_brewer(     palette = \"Set1\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Combined interventions\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"details-discrete-time-ebola-virus-disease-model","dir":"Articles","previous_headings":"","what":"Details: Discrete-time Ebola virus disease model","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"model compartments adopted consensus model Ebola virus disease presented Li et al. (2019), transitions epidemiological compartments modelled using Erlang sub-compartments adapted Getz Dougherty (2018); see References. R code model adapted code Ha Minh Lam initially made available Epirecipes (https://github.com/epirecipes/epicookbook) MIT license. transition rates exposed infectious, infectious funeral compartments (also hospitalised removed), \\(\\gamma^E\\) \\(\\gamma^\\) Getz Dougherty’s notation, passed user infectiousness_rate removal_rate respectively. shape Erlang distributions passage times exposed infectious compartments (\\(k^E\\) \\(k^\\)) recommended set 2 sensible choice, default value erlang_sbubcompartments argument, can allowed vary (independently). Getz Dougherty’s equation (6) gives relationship parameters mean pre-infectious \\(\\rho^E\\) infectious \\(\\rho^\\) periods. \\[\\gamma^E = \\dfrac{k^E}{\\rho^E} = \\dfrac{2}{\\rho^E} ~\\text{}~ \\gamma^= \\dfrac{k^}{\\rho^} = \\dfrac{2}{\\rho^}\\] discrete time model, \\(\\gamma^E\\) \\(\\gamma^\\) used determine passage times newly exposed infectious individuals respective compartments (thus allowing variation passage times).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"hospitalisation-funerals-and-removal","dir":"Articles","previous_headings":"Details: Discrete-time Ebola virus disease model","what":"Hospitalisation, funerals, and removal","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Li et al. (2019) present consensus model EVD individuals can follow multiple pathways infectious compartment — hospitalisation, funeral transmission, safe burial recovery (removed), possibility skipping compartments sequence (e.g. directly infectious removed, infectious hospitalisation removed etc.). model simplifies transitions two pathways: Infectious → funeral → removed (safe burial) Infectious → hospitalised → removed (recovery safe burial) proportion, 1.0 - prop_community, infectious individuals transferred hospitalised compartment timestep, compartment represents Ebola Treatment Units (ETUs), individuals hospitalised compartment considered infectious longer community. passage time individuals hospitalised compartment similar individuals infectious compartment (.e., infectious community), means infectious individual \\(N\\) timesteps exiting infectious compartment exit hospitalised compartment time. Hospitalised individuals can contribute transmission Ebola susceptibles depending value \\(p_\\text{ETU}\\), probability (proportion) hospitalised cases contributing infection susceptibles. interpreted relative risk Ebola virus treatment units (ETUs), range 0.0 – 1.0, 0.0 indicates hospitalisation prevents onward transmission entirely, 1.0 indicates hospitalisation reduce transmission . passed argument etu_risk. assume deaths hospital lead Ebola-safe funerals, individuals exiting hospitalised compartment move ‘removed’ compartment, holds recoveries deaths. assume infectious individuals hospitalised die, deaths outside hospital lead funerals potentially Ebola-safe, contribution funerals Ebola transmission determined \\(p_\\text{funeral}\\), can interpreted relative risk funerals, passed funeral_risk argument. Values closer 0.0 indicate low risk Ebola transmission funerals, values closer 1.0 indicate risk similar transmission community. Individuals assumed spend single timestep funeral transmission compartment, move ‘removed’ compartment. Individuals ‘removed’ compartment affect model dynamics.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"modifications-for-epidemics","dir":"Articles","previous_headings":"","what":"Modifications for epidemics","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"made modifications ODE model Vacamole order make general thus potentially applicable wider range settings. Specifically, dropped ICU ICU2H compartment potentially less relevant context intensive care capacity low. added transitions infectious () hospitalised (H) compartments death (D), may general assumption hospital capacity low (relatively → D) treatments poor (relatively H → D). assume, first pass implementation vaccination primarily reduces adverse outcomes, modification transition rates (\\(\\beta_V,\\eta_{V},\\omega_V\\)): \\(\\beta_V\\): transmission rate \\(\\beta\\) individuals fully vaccinated compartment \\(V_2\\); \\(\\eta_{V}\\): hospitalisation rate \\(\\eta\\) fully vaccinated, infected individuals (\\(I_V\\) → \\(H_V\\)); \\(\\omega_V\\): mortality rate fully vaccinated individuals stage post infection (, H). details ODE system version Vacamole included epidemics can found end page.","code":"library(epidemics) library(dplyr) library(tidyr) library(ggplot2) library(colorspace) library(scales)"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"Prepare population contact data. Prepare initial conditions age group. Vacamole model 11 compartments therefore requires matrix 11 columns. Prepare time days model epidemic, outbreak beginning day zero. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-6  # // 0| 1| 2|3| 4|5| 6|7| 8|9|10 # // S|V1|V2|E|EV|I|IV|H|HV|D|R  # make initial conditions - order is important initial_conditions <- c(   S = 1 - initial_i,   V1 = 0, V2 = 0,   E = 0, EV = 0,   I = initial_i, IV = 0,   H = 0, HV = 0, D = 0, R = 0 ) initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) epidemic_days <- 300 uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"prepare-a-two-dose-vaccination-campaign","dir":"Articles","previous_headings":"","what":"Prepare a two dose vaccination campaign","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"prepare two-dose vaccination campaign concatenating two single dose vaccination regimes, .e., applying function c() two vaccination objects. possible combine multiple vaccination objects together using c() — limitation vaccination regimes combined way must number demographic groups. possible add single dose two-vaccination regime using c() two vaccination objects two one dose, respectively.","code":"# prepare a two dose vaccination regime for a single age group # prepare the first dose dose_1 <- vaccination(   name = \"two-dose vaccination\", # name given to first dose   nu = matrix(1e-2, nrow = 3),   time_begin = matrix(30, nrow = 3),   time_end = matrix(epidemic_days, nrow = 3) )  # prepare the second dose with a 30 day interval in start date dose_2 <- vaccination(   name = \"two-dose vaccination\", # name given to first dose   nu = matrix(1e-2, nrow = 3),   time_begin = matrix(60, nrow = 3),   time_end = matrix(epidemic_days, nrow = 3) )  # use `c()` to combine the two doses double_vaccination <- c(dose_1, dose_2)  # print to visualise double_vaccination #>  #>  Vaccination name:  #>  Begins at:  #>      dose_1 dose_2 #> [1,]     30     60 #> [2,]     30     60 #> [3,]     30     60 #>  #>  Ends at:  #>      dose_1 dose_2 #> [1,]    300    300 #> [2,]    300    300 #> [3,]    300    300 #>  #>  Vaccination rate:  #>      dose_1 dose_2 #> [1,]   0.01   0.01 #> [2,]   0.01   0.01 #> [3,]   0.01   0.01"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"model-epidemic-using-vacamole","dir":"Articles","previous_headings":"","what":"Model epidemic using Vacamole","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"First, run model vaccination. default behaviour, vaccination regime need specified included. model’s default parameters : Transmission rate (\\(\\beta\\), transmission_rate): 0.186, resulting \\(R_0\\) = 1.3 infectious period 7 days, given \\(\\beta = R_0 / \\text{infectious period}\\). Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.5, assuming pre-infectious period 2 days, given \\(\\sigma = 1 / \\text{pre-infectious period}\\). Hospitalisation rate (\\(\\eta\\), hospitalistion_rate): 1.0 / 1000, assuming one every thousand infectious individuals hospitalised. Mortality rate (\\(\\omega\\), mortality_rate): 1.0 / 1000, assuming one every thousand infectious hospitalised individuals dies. Recovery rate (\\(\\gamma\\), recovery_rate): 0.143, assuming infectious period 7 days, given \\(\\gamma = 1 / \\text{infectious period}\\). Susceptibility reduction vaccination (susc_reduction_vax): 0.2, assuming 20% reduction susceptibility individuals doubly vaccinated. Hospitalisation reduction vaccination (hosp_reduction_vax): 0.2, assuming 20% reduction hospitalisation individuals doubly vaccinated. Mortality reduction vaccination (mort_reduction_vax): 0.2, assuming 20% reduction mortality individuals doubly vaccinated. Next run model two dose vaccination regime.","code":"# note model will automatically account for no vaccination data <- model_vacamole(   population = uk_population,   time_end = epidemic_days ) data_vaccination <- model_vacamole(   population = uk_population,   vaccination = double_vaccination, # note vaccination object for two doses   time_end = epidemic_days )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"visualise-model-outcomes","dir":"Articles","previous_headings":"","what":"Visualise model outcomes","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"First, calculate total number infections resulting recoveries deaths course simulation; epidemic’s final size.  Finally, can compare peak hospital bed occupancy scenario — can rough indication much hospital capacity required pandemic characteristics occur, well another way examine effect vaccination reducing requirement. example demonstrates implementing vaccination can substantially reduce peak hospital occupancy (100%) compared scenario vaccines deployed.","code":"# collect data from the two scenarios data_scenarios <- list(data, data_vaccination)  # get deaths and recoveries from infection data_scenarios <- Map(   data_scenarios, c(\"no_vax\", \"vax\"),   f = function(df, sc) {     df_ <- distinct(df, demography_group)      # get total deaths per group     df_$total_deaths <- filter(       df, time == max(time), compartment == \"dead\"     ) %>% pull(value)      # get total recoveries per group using helper function `epidemic_size()`     # do not count dead     df_$total_recovered <- epidemic_size(df, include_deaths = FALSE)      # add scenario information     df_$scenario <- sc      # return data     df_   } )  # collect data data_scenarios <- bind_rows(data_scenarios)  # transform to long format data_scenarios <- pivot_longer(   data_scenarios,   cols = c(\"total_deaths\", \"total_recovered\"),   names_to = \"measure\" ) ggplot(data_scenarios) +   geom_col(     aes(demography_group, value, fill = scenario),     position = \"dodge\",     colour = \"black\"   ) +   facet_wrap(     facets = vars(measure),     scales = \"free_y\",     labeller = labeller(       measure = c(         total_deaths = \"Total deaths\",         total_recovered = \"Epidemic size (infections without deaths)\"       )     )   ) +   scale_fill_discrete_qualitative(     palette = \"Dynamic\",     labels = c(\"No vaccination\", \"Vaccination\"),     name = \"Scenario\",     na.value = \"lightgrey\"   ) +   scale_y_continuous(     labels = label_comma(       scale = 1e-6, suffix = \"M\"     )   ) +   theme_bw() +   theme(     legend.position = \"bottom\",     legend.key.height = unit(2, \"mm\"),     strip.background = element_blank(),     strip.text = element_text(       face = \"bold\",       size = 11     )   ) +   expand_limits(     x = c(0.5, length(unique(data_scenarios$demography_group)) + 0.5)   ) +   coord_cartesian(     expand = FALSE   ) +   labs(     x = \"Age group\",     y = \"No. of individuals\",     title = \"Effect of vaccination on deaths and total infections\"   ) # collect data from the two scenarios data_scenarios <- list(data, data_vaccination)  peak_hospital_occupancy <- vapply(data_scenarios, function(df) {   # get highest hospital occupancy   # first get total hospitalisations among vaccinated and un- or part-vacc.   df <- filter(     df,     grepl(       pattern = \"hospitalised\", x = compartment,       fixed = TRUE     )   ) %>%     # summarise all hospitalised over time, aggregating away age groups     summarise(       total_hosp = sum(value), .by = \"time\"     ) %>%     # filter for the time point with highest hospital occupancy     filter(total_hosp == max(total_hosp)) %>%     # get the value     pull(total_hosp) }, FUN.VALUE = numeric(1))  # set names for comprehensibility names(peak_hospital_occupancy) <- c(\"No vaccination\", \"Vaccination\")  # show peak hospital occupancy in a readable format format(peak_hospital_occupancy, big.mark = \",\", digits = 1) #> No vaccination    Vaccination  #>        \"1,813\"        \"    8\""},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"vacamole-ode-system-for-epidemics","dir":"Articles","previous_headings":"","what":"Vacamole ODE system for {epidemics}","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"Vacamole ODE system adapted {epidemics} : Susceptibles vaccinated, partially vaccinated (considered unprotected) can transition exposed vaccinated: \\[dS = -\\beta S(+I_V) - \\nu_1 S\\] Two sequential vaccination compartments, lower conversion rate two-dose vaccinated individuals (considered protected) exposed: \\[dV_1 = \\nu_1S - \\beta V_1(+I_V) - \\nu_2V_1\\] \\[dV_2 = \\nu_2V_1 - \\beta_VV_2(+I_V)\\] Two parallel exposed compartments, similar conversion infectious: \\[dE = \\beta (S+V_1)(+I_V) - \\sigma E\\] \\[dE_V = \\beta_VV_2(+I_V) - \\sigma E_V\\] Two parallel infectious compartments, lower hospitalisation mortality rate vaccinated: \\[dI = \\sigma E - \\gamma - \\eta - \\omega \\] \\[dI_V = \\sigma E_V - \\gamma I_V - \\eta_{V} I_V - \\omega_V I_V\\] Two parallel hospitalisation compartments, lower mortality rate vaccinated: \\[dH = \\eta - \\gamma H - \\eta_2 H - \\omega H\\] \\[dH_V = \\eta_{V} - \\gamma H_V - \\omega_V H_V\\] Single recovered compartment: \\[dR = \\gamma(+ H + I_V + H_V)\\] Single mortality compartment: \\[dD = \\omega(+ H) + \\omega_V(I_V + H_V)\\]","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Getting started with modelling interventions targeting social contacts","text":"Prepare population contact data. Prepare initial conditions age group. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE ) #> Using POLYMOD social contact data. To cite this in a publication, use the 'get_citation()' function #> Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"prepare-an-intervention","dir":"Articles","previous_headings":"","what":"Prepare an intervention","title":"Getting started with modelling interventions targeting social contacts","text":"Prepare intervention simulate school closures.","code":"# prepare an intervention with a differential effect on age groups close_schools <- intervention(   name = \"School closure\",   type = \"contacts\",   time_begin = 200,   time_end = 300,   reduction = matrix(c(0.5, 0.001, 0.001)) )  # examine the intervention object close_schools #> <contacts_intervention> object #>  #>  Intervention name:  #> \"School closure\" #>  #>  Begins at:  #> [1] 200 #>  #>  Ends at:  #> [1] 300 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1     0.500 #> Demo. grp. 2     0.001 #> Demo. grp. 3     0.001"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Getting started with modelling interventions targeting social contacts","text":"","code":"# run an epidemic model using `epidemic` output <- model_default(   population = uk_population,   intervention = list(contacts = close_schools),   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Getting started with modelling interventions targeting social contacts","text":"Plot epidemic time, showing number individuals exposed infected compartments.","code":"# plot figure of epidemic curve filter(output, compartment %in% c(\"exposed\", \"infectious\")) %>%   ggplot(     aes(       x = time,       y = value,       col = demography_group,       linetype = compartment     )   ) +   geom_line() +   annotate(     geom = \"rect\",     xmin = close_schools$time_begin,     xmax = close_schools$time_end,     ymin = 0, ymax = 500e3,     fill = alpha(\"red\", alpha = 0.2),     lty = \"dashed\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 400e3,     angle = 90,     label = \"School closure\"   ) +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 500e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"prepare population contact data U.K., epidemiological compartments matching default epidemic model (SEIR-V). assume one every million people infected infectious, translating 67 total infections U.K. population 67 million. code steps similar “Getting started vignette” hidden , although can expanded reference.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-4 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"examine-the-baseline","dir":"Articles","previous_headings":"","what":"Examine the baseline","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"first examine baseline scenario — interventions implemented slow spread epidemic — visualise outcomes terms daily new infections. simulate epidemic using model_default(), calling default model outlined “Get started vignette”. show one instance plotting code using ggplot2 package , instances hidden keep vignette short. Figure 1: model infectious disease epidemic, assuming directly transmitted infection influenza, \\(R_0\\) 1.3, infectious period 5 days, pre-infectious period 1.5 days. baseline scenario, epidemic continue approximately 400 days, one year, peak new infections 150th 180th day different age groups. scenario, epidemic expected final size around 23 million individuals infected overall. following sections shall iteratively model effects applying non-pharmaceutical interventions reduce contacts examine whether epidemic’s final size reduced, whether peak infections can spread time.","code":"# no intervention baseline scenario data_baseline <- model_default(   population = uk_population,   time_end = 400, increment = 1.0 )  # get new infections data_baseline_infections <- new_infections(data_baseline, by_group = TRUE) # visualise the spread of the epidemic in terms of new infections # plot figure of epidemic curve plot_baseline <- ggplot() +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_baseline"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"modelling-overlapping-interventions","dir":"Articles","previous_headings":"","what":"Modelling overlapping interventions","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"shall prepare multiple interventions plausibly implemented course epidemic. can use c() function combine two intervention objects single intervention accommodates effect interventions. multiple intervention can passed — single intervention object — epidemic model model_default(). can combine number intervention objects single intervention object passed model_default(). cumulative effect interventions handled automatically C++ code underlying epidemics. Remember two multiple interventions can also combined using c(). important careful make sure interventions intend combine concatenated together. example, c(combined_interventions, combined_interventions) valid, effectively double effect school workplace closures example. simulate epidemic using model_default() function, calling default model outlined “Get started vignette”. simulate epidemic 600 days. Figure 3: Epidemic model two overlapping interventions early phase outbreak: school closures target infections among younger people, workplace closures target infections among working-age adults. scenario school closures 6 months well workplace closures 2 months, epidemic still continue approximately 600 days, one half years, number days 10,000 daily cases reduced, typically occur intervention workplaces lifted. scenario, epidemic expected final size around 22 million individuals infected overall — similar school closures intervention. distinct peak new infections schools simulated re-open, nearly 100,000 new infections days.","code":"# combine interventions using `c()` combined_interventions <- c(   close_schools, close_workplaces )  # visualise the combined intervention object combined_interventions #>  #>  Intervention name:  #>  Begins at:  #>      npi_1 npi_2 #> [1,]    60    80 #>  #>  Ends at:  #>      npi_1 npi_2 #> [1,]   240   140 #>  #>  Reduction:  #>              Interv. 1 Interv. 2 #> Demo. grp. 1      0.30      0.01 #> Demo. grp. 2      0.01      0.30 #> Demo. grp. 3      0.01      0.01 # get data from an epidemic model with both interventions data_combined <- model_default(   population = uk_population,   intervention = list(contacts = combined_interventions),   time_end = 600, increment = 1.0 )  # get data on new infections data_infections <- new_infections(data_combined, by_group = TRUE) plot_intervention_cases <-   ggplot() +   geom_vline(     xintercept = c(       close_schools$time_begin,       close_schools$time_end     ),     linetype = \"dotted\"   ) +   geom_vline(     xintercept = c(       close_workplaces$time_begin,       close_workplaces$time_end     ),     colour = \"red\",     linetype = \"dotted\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 50000,     label = \"Schools closed\"   ) +   annotate(     geom = \"text\",     x = mean(c(       close_workplaces$time_begin,       close_workplaces$time_end     )),     y = 30000,     colour = \"red\",     label = \"Workplaces\\nclosed\"   ) +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   geom_line(     data = data_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"solid\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_intervention_cases"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"school-closures","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"School closures","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"first example, shall model school closures, primarily aimed reducing infections among younger individuals transmit families. first prepare intervention simulates effect closing schools reduce contacts younger people. assume reduces contacts age group 0 – 19 30%, contacts age groups 1% (adults meet individuals age). intervention assumed last 6 months approximately 180 days, beginning 100th day outbreak — similar duration initial school closures Covid-19 pandemic 2020 U.K. simulate epidemic 600 days expect intervention spread disease incidence longer period. Figure 2: Epidemic model intervention targets infections among children closing schools six months, thus reducing children’s social contacts. school closures scenario, epidemic continue approximately 600 days, one half years, 10,000 daily new infections one year. scenario, epidemic expected final size around 22 million individuals infected overall.","code":"# prepare an intervention that models school closures for ~3 months (100 days) close_schools <- intervention(   name = \"School closure\",   type = \"contacts\",   time_begin = 60,   time_end = 60 + 180,   reduction = matrix(c(0.3, 0.01, 0.01)) )  # examine the intervention object close_schools #>  #>  Intervention name:  #>  Begins at:  #> [1] 60 #>  #>  Ends at:  #> [1] 240 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.30 #> Demo. grp. 2      0.01 #> Demo. grp. 3      0.01 # no intervention baseline scenario data_schools_closed <- model_default(   population = uk_population,   intervention = list(contacts = close_schools),   time_end = 600, increment = 1.0 )  # get new infections data_noschool_infections <- new_infections(data_schools_closed, by_group = TRUE) # visualise the spread of the epidemic in terms of new infections when # schools are closed plot_noschool <-   ggplot() +   geom_vline(     xintercept = c(       close_schools$time_begin,       close_schools$time_end     ),     linetype = \"dotted\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 1000,     label = \"Schools closed\"   ) +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   geom_line(     data = data_noschool_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"solid\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_noschool"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"workplace-closures","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"Workplace closures","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"General workplace closures broad-based measure aimed reducing infections among working age adults. shall prepare intervention simulates effect closing workplaces addition closing schools, assume reduces contacts age group 20 – 65 30%, contacts age groups 1% (assume individuals age groups meeting many individuals workplaces). intervention assumed last 60 days, beginning 80th day outbreak — simulates situation policymakers decide close workplaces three weeks deciding close schools, choose keep workplaces closed long (2 months 60 days vs. 6 months 180 days school closures).","code":"# prepare an intervention which mostly affects adults 20 -- 65 intervention_duration <- 60 close_workplaces <- intervention(   name = \"Workplace closure\",   type = \"contacts\",   time_begin = 80,   time_end = 80 + intervention_duration,   reduction = matrix(c(0.01, 0.3, 0.01)) )  # examine the intervention object close_workplaces #>  #>  Intervention name:  #>  Begins at:  #> [1] 80 #>  #>  Ends at:  #> [1] 140 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.01 #> Demo. grp. 2      0.30 #> Demo. grp. 3      0.01"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"combining-interventions","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"Combining interventions","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"can use c() function combine two intervention objects single intervention accommodates effect interventions. multiple intervention can passed — single intervention object — epidemic model model_default(). intervention object made multiple interventions first intervention specified treated baseline intervention, age-specific effect reducing contacts duration effect. interventions assumed additional percentage point increases effect active interventions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"re-applying-workplace-closures","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"Re-applying workplace closures","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"scenario combined interventions, daily new infections forecast exceed 50,000 397th day epidemic. final example, simulate re-implementing two months workplace closures, school closures, reduce infections. Combine multiple interventions object two interventions third intervention. simulate epidemic using model_default() function 600 days . Figure 4: Epidemic model two initial, overlapping interventions schools workplaces, followed later intervention workplaces. scenario school closures 6 months well two phases workplace closures 2 months , epidemic continue 600 days, one half years, number days 10,000 daily cases reduced, typically occur interventions workplaces lifted — similar previous example. scenario, epidemic expected final size around 15 million individuals infected overall — lower previous examples.","code":"# log the date that cases exceed 50000 daily start_date <- min(   which(     new_infections(data_combined, by_group = FALSE)[, new_infections > 50000]   ) )  # create a new workplace closures object workplace_closures_2 <- intervention(   type = \"contacts\",   time_begin = start_date,   time_end = start_date + 60,   reduction = matrix(c(0.01, 0.3, 0.01)) ) combined_interventions <- c(combined_interventions, workplace_closures_2) # get data from an epidemic model with both interventions data_combined <- model_default(   population = uk_population,   intervention = list(contacts = combined_interventions),   time_end = 600, increment = 1.0 )  # get data on new infections data_infections <- new_infections(data_combined, by_group = TRUE) plot_three_interventions <-   ggplot() +   geom_vline(     xintercept = c(       close_schools$time_begin,       close_schools$time_end     ),     linetype = \"dotted\"   ) +   geom_vline(     xintercept = c(       close_workplaces$time_begin,       close_workplaces$time_end,       workplace_closures_2$time_begin,       workplace_closures_2$time_end     ),     colour = \"red\",     linetype = \"dotted\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 50000,     label = \"Schools closed\"   ) +   annotate(     geom = \"text\",     x = c(       mean(         c(close_workplaces$time_begin, close_workplaces$time_end)       ),       mean(c(workplace_closures_2$time_begin, workplace_closures_2$time_end))     ),     y = 30000,     colour = \"red\",     label = c(\"Workplaces\\nclosed\", \"Workplaces\\nclosed\")   ) +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   geom_line(     data = data_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"solid\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_three_interventions"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_rate_interventions.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling other interventions that change transmission rates","text":"prepare population contact data U.K., epidemiological compartments matching default epidemic model (SEIR-V). assume one every million people infected infectious, translating 67 total infections U.K. population 67 million. code steps similar “Getting started vignette” hidden , although can expanded reference.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-4 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_rate_interventions.html","id":"modelling-an-intervention-on-the-transmission-rate","dir":"Articles","previous_headings":"","what":"Modelling an intervention on the transmission rate","title":"Modelling other interventions that change transmission rates","text":"model intervention transmission rate \\(\\beta\\) reduces 10%. represent interventions requiring people wear masks reduce transmission. first run baseline scenario — interventions implemented slow spread epidemic — visualise outcomes terms daily new infections. simulate epidemic using model_default(), calling default model outlined “Get started vignette”. examine effect mask mandate, simulate epidemic 200 days expect intervention spread disease incidence longer period. plot data examine effect implementing mask mandate daily number new infections.","code":"# prepare an intervention that models mask mandates for ~3 months (100 days) mask_mandate <- intervention(   name = \"mask mandate\",   type = \"rate\",   time_begin = 60,   time_end = 60 + 100,   reduction = 0.1 )  # examine the intervention object mask_mandate #>  #>  Intervention name:  #>  Begins at:  #>      [,1] #> [1,]   60 #>  #>  Ends at:  #>      [,1] #> [1,]  160 #>  #>  Reduction:  #> Interv. 1  #>       0.1  # check the object is_intervention(mask_mandate) #> [1] TRUE  is_contacts_intervention(mask_mandate) #> [1] FALSE  is_rate_intervention(mask_mandate) #> [1] TRUE # no intervention baseline scenario data <- model_default(   population = uk_population,   time_end = 200, increment = 1.0 )  # with a mask mandate data_masks <- model_default(   population = uk_population,   intervention = list(transmission_rate = mask_mandate),   time_end = 200, increment = 1.0 ) # get new infections in each scenario data <- new_infections(data, by_group = TRUE) data_masks <- new_infections(data_masks, by_group = TRUE)  # assign a scenario name to each scenario data$scenario <- \"baseline\" data_masks$scenario <- \"masks\"  # bind data together data_combined <- bind_rows(data, data_masks) ggplot(data_combined) +   geom_line(     aes(time, new_infections, col = demography_group, linetype = scenario)   ) +   coord_cartesian(     expand = FALSE   ) +   annotate(     geom = \"rect\",     xmin = mask_mandate[[\"time_begin\"]],     xmax = mask_mandate[[\"time_end\"]],     ymin = 0, ymax = 150e3,     fill = alpha(\"red\", alpha = 0.2),     lty = \"dashed\"   ) +   scale_y_continuous(     labels = scales::comma   ) +   scale_linetype_manual(     name = \"Scenario\",     values = c(       baseline = \"dashed\",       masks = \"solid\"     )   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 100e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"New infections\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"modelling-parameter-uncertainty","dir":"Articles","previous_headings":"","what":"Modelling parameter uncertainty","title":"Modelling parameter uncertainty and epidemic scenarios","text":"Uncertainty characteristics epidemic key element roadblock epidemic response (Shea et al. 2020). Epidemic dynamics can influenced two main sources uncertainty: intrinsic randomness transmission process, uncertain knowledge parameters underlying transmission process. focus latter, .e. uncertainty input parameters epidemic model. epidemics model functions can accept numeric vectors infection parameters; model run parameter combination using population model components (interventions, vaccinations) etc. allows users quickly obtain results range parameter values without repeatedly call model_*() loop similar; iteration performed internally. benefits vectorising inputs: Inputs checked , rather \\(N\\) times element parameter vector — improves performance manual iteration; Model output organised make filtering parameter values scenarios easier (). Note always possible pass single value infection parameter. Single values may referred “scalar” values “scalars”. Passing scalar infection parameters yield simple table model “time”, “demography group”, “compartment”, “value”, number individuals demographic group compartment model time point. Click “Code” see hidden code used set population vignette. details define populations initial model conditions please see “Getting started epidemic scenario modelling components” vignette. brief, model U.K. population three age groups, 0 – 19, 20 – 39, > 40, social contacts stratified age. unnest output’s “data” column order plot incidence curves transmission rate value. Figure 1: Incidence curves number new infections day epidemic given uncertainty R estimate; colours indicate \\(R\\) bins. Larger \\(R\\) values lead shorter epidemics higher peaks, lower R values lead spread epidemics lower peaks. Epidemics \\(R\\) < 1.0 ‘take ’ clearly visible. Linking incidence curves \\(R\\) values plot allows quick visual assessment potential outcomes epidemic whose \\(R\\) uncertain.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix)  # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions ) # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) # UK population created from hidden code uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions ) # select the parameter set and data columns with dplyr::select() # add the R value for visualisation # calculate new infections, and use tidyr to unnest the data column data <- select(output, param_set, transmission_rate, data) %>%   mutate(     r_value = r_samples,     new_infections = map(data, new_infections)   ) %>%   select(-data) %>%   unnest(new_infections) # plot the data filter(data) %>%   ggplot() +   geom_line(     aes(time, new_infections, col = r_value, group = param_set),     alpha = 0.3   ) +   # use qualitative scale to emphasize differences   scale_colour_fermenter(     palette = \"Dark2\",     name = \"R\",     breaks = c(0, 1, 1.5, 2.0, 3.0),     limits = c(0, 3)   ) +   scale_y_continuous(     name = \"New infections\",     labels = scales::label_comma(scale = 1e-3, suffix = \"K\")   ) +   labs(     x = \"Time (days since start of epidemic)\"   ) +   facet_grid(     cols = vars(demography_group)   ) +   theme_bw() +   theme(     legend.position = \"top\",     legend.key.height = unit(2, \"mm\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"obtaining-estimates-of-disease-transmission-rate","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Obtaining estimates of disease transmission rate","title":"Modelling parameter uncertainty and epidemic scenarios","text":"example, consider influenza pandemic potential (Ghani et al. 2010), prepare multiple samples estimated \\(R\\). reflects pandemic response scenarios \\(R\\) estimates always come uncertainty (due limitations data estimation methods). Sampling distribution \\(R\\) expected follow allows us better understand extent variance possible epidemic outcomes. obtain probability distribution function (PDF) distribution serial intervals; Gamma distribution shape \\(k\\) = 2.622 scale \\(\\theta\\) = 0.957 (Ghani et al. 2010). forthcoming Epiverse package epiparameter expected make substantially easier access use epidemiological parameters, serial interval, reported literature, making easier model scenarios differing intrinsic characteristics pathogen causing outbreak. use PDF estimate \\(R\\) 2009 influenza pandemic U.K., using EpiEstim package. use \\(R\\) estimate (mean standard deviation) EpiEstim generate 100 samples \\(R\\), assuming normally distributed. Users drawing parameters greater variance may wish draw larger number samples.","code":"# Get 2009 influenza data for school in Pennsylvania data(Flu2009) flu_early_data <- filter(Flu2009$incidence, dates < \"2009-05-10\")  # get the PDF of the distribution of serial intervals serial_pdf <- dgamma(seq(0, 25), shape = 2.622, scale = 0.957) # ensure probabilities add up to 1 by normalising them by the sum serial_pdf <- serial_pdf / sum(serial_pdf)  # Use EpiEstim to estimate R with uncertainty # Uses Gamma distribution by default output_R <- estimate_R(   incid = flu_early_data,   method = \"non_parametric_si\",   config = make_config(list(si_distr = serial_pdf)) )  # Plot output to visualise plot(output_R, \"R\")"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"passing-a-vector-of-transmission-rates","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Passing a vector of transmission rates","title":"Modelling parameter uncertainty and epidemic scenarios","text":", generate 100 samples \\(R\\), convert transmission rate (often denoted \\(\\beta\\)) dividing infectious period 7 days. Since EpiEstim estimates \\(Rt\\), instantaneous \\(R\\), shall use mean estimates time period, mean standard deviation, parameters distribution draw \\(R\\) samples model. output nested <data.table>, output run model unique transmission_rate contained <data.frame> list column \"data\".","code":"# get mean mean and sd over time r_estimate_mean <- mean(output_R$R$`Mean(R)`) r_estimate_sd <- mean(output_R$R$`Std(R)`)  # Generate 100 R samples r_samples <- with_seed(   seed = 1,   rnorm(     n = 100, mean = r_estimate_mean, sd = r_estimate_sd   ) )  infectious_period <- 7 beta <- r_samples / infectious_period # pass the vector of transmissibilities to the argument `transmission_rate` output <- model_default(   population = uk_population,   transmission_rate = beta,   time_end = 600 )  # view the output head(output) #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1977482                 0.5     0.1428571      600         1 #> 2:         0.2333557                 0.5     0.1428571      600         2 #> 3:         0.1885540                 0.5     0.1428571      600         3 #> 4:         0.2954036                 0.5     0.1428571      600         4 #> 5:         0.2397671                 0.5     0.1428571      600         5 #> 6:         0.1892204                 0.5     0.1428571      600         6 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #> 4: <population[4]>                                <list[1]>         1        1 #> 5: <population[4]>                                <list[1]>         1        1 #> 6: <population[4]>                                <list[1]>         1        1 #>                    data #>                  <list> #> 1: <data.table[9015x4]> #> 2: <data.table[9015x4]> #> 3: <data.table[9015x4]> #> 4: <data.table[9015x4]> #> 5: <data.table[9015x4]> #> 6: <data.table[9015x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"output-type-for-vector-parameter-inputs","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Output type for vector parameter inputs","title":"Modelling parameter uncertainty and epidemic scenarios","text":"output model_*() infection parameter passed vector nested <data.table>. similar nested <tibble>, can handled popular data science packages, Tidyverse. handling nested data can found section list-columns R Data Science documentation nested data tidyr package. Equivalent operations possible <data.table>s directly; see R Bloggers post unnesting data.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"passing-parameter-sets","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Passing parameter sets","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics model functions can accept multiple infection parameters vectors, long vectors length, length 1 (scalar values) shown .","code":"beta <- rnorm(n = 100, mean, sd) gamma <- rnorm(n = 100, mean, sd) # the recovery rate  model_default(   population,   transmission_rate = beta, # same length as gamma   infectiousness_rate = 0.5, # length 1   recovery_rate = gamma )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"passing-vectors-of-epidemic-duration","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Passing vectors of epidemic duration","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics allows duration model run varied, may useful examining variation start time epidemic affects outcomes fixed end point. example shows estimate potential variation final epidemic size range epidemic start times (hence durations, assuming fixed end).  NOTE: duration model runs varied, model output potentially distinct number rows.","code":"# draw samples of time_end max_time <- 600 duration <- max_time - with_seed(seed = 1, {   rnbinom(100, 1, 0.02) }) # view durations ggplot() +   geom_histogram(aes(duration)) +   theme_bw() +   labs(     x = \"Epidemic duration\",     y = \"Count\"   ) # pass the vector of durations to `time_end` output <- model_default(   population = uk_population,   time_end = duration )  # view the output head(output) #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571      589         1 #> 2:         0.1857143                 0.5     0.1428571      595         2 #> 3:         0.1857143                 0.5     0.1428571      568         3 #> 4:         0.1857143                 0.5     0.1428571      583         4 #> 5:         0.1857143                 0.5     0.1428571      589         5 #> 6:         0.1857143                 0.5     0.1428571      593         6 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #> 4: <population[4]>                                <list[1]>         1        1 #> 5: <population[4]>                                <list[1]>         1        1 #> 6: <population[4]>                                <list[1]>         1        1 #>                    data #>                  <list> #> 1: <data.table[8850x4]> #> 2: <data.table[8940x4]> #> 3: <data.table[8535x4]> #> 4: <data.table[8760x4]> #> 5: <data.table[8850x4]> #> 6: <data.table[8910x4]> # calculate the epidemic size to view the mean and SD of sizes epidemic_size_estimates <- select(output, param_set, data) %>%   mutate(     size = map(data, function(x) {       tibble(         demography_group = unique(x$demography_group),         size = epidemic_size(x)       )     })   ) %>%   select(size) %>%   unnest(size) %>%   summarise(     across(size, .fns = c(mean = mean, sd = sd)),     .by = \"demography_group\"   ) # view the range of epidemic sizes range(epidemic_size_estimates$size) #> [1]  Inf -Inf"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"modelling-scenarios-of-epidemic-response","dir":"Articles","previous_headings":"","what":"Modelling scenarios of epidemic response","title":"Modelling parameter uncertainty and epidemic scenarios","text":"Users may wish model epidemic trajectories outcomes multiple scenarios response measures. epidemics model functions can accept lists intervention sets vaccination regimes, allowing multiple intervention, vaccination, combined intervention--vaccination sets modelled population. benefits passing lists composable elements: Combinations intervention vaccination scenarios can conveniently created, model functions automatically create possible combinations arguments intervention vaccination; Input-checking cross-checking reduced checking element intervention vaccination list independently combination created (population, cross-checking); hence \\(N\\) intervention sets \\(M\\) vaccination regimes \\(N+M\\) cross-checks, rather \\(N \\time M\\) cross-checks; Model output organised provide scenario identifier, making subsetting easier (). may help read “Modelling non-pharmaceutical intervention targeting social contacts” “Modelling effect vaccination campaign” vignettes first! function epidemic_size() can applied nested data column data get final size scenario. example shows implementing interventions reduce transmission can reduce final size epidemic. unnesting output follows procedure , shown .","code":"# set intervention labels labels <- c(   \"No response\", \"Close schools\", \"Close workplaces\", \"Close both\",   \"Mask mandate\", \"Masks + close schools\", \"Masks + close workplaces\",   \"Masks + close both\" )  epidemic_size_estimates <- mutate(   output,   scenario = labels,   size = scales::comma(     map_dbl(data, epidemic_size, by_group = FALSE, include_deaths = FALSE)   ) ) %>%   select(scenario, size)  # view the final epidemic sizes epidemic_size_estimates #>                    scenario       size #>                      <char>     <char> #> 1:              No response 23,084,960 #> 2:            Close schools 21,495,236 #> 3:         Close workplaces 22,423,830 #> 4:               Close both  6,622,568 #> 5:             Mask mandate 22,712,782 #> 6:    Masks + close schools 17,215,645 #> 7: Masks + close workplaces 20,564,673 #> 8:       Masks + close both  2,044,188"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"which-model-components-can-be-passed-as-lists","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Which model components can be passed as lists","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics currently offers ability pass intervention sets vaccination regimes lists. currently possible pass lists populations, seasonality, population changes models. future, may possible pass multiple populations list, rapidly conveniently model epidemic different populations, examine effect assumptions population’s social contacts demographic structure.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"creating-a-list-of-intervention-sets","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Creating a list of intervention sets","title":"Modelling parameter uncertainty and epidemic scenarios","text":"shall create list ‘intervention sets’, set representing scenario epidemic response measures. Note intervention set simply list <intervention> objects; typically, single <contacts_intervention> <rate_interventions> infection parameters. prepared interventions, create intervention sets, pass model function. Note parameter uncertainty included . can visualise effect intervention set form epidemic’s final size, aggregating age groups. output nested <data.table> — can quickly get table final epidemic sizes scenarios — key initial indicator effectiveness interventions. Note example, use model’s default \\(R\\) estimate 1.3. higher values \\(R\\), get counter-intuitive results effects interventions reduce transmission. explored detail later vignette.","code":"# prepare durations as starting at 25% of the way through an epidemic # and ending halfway through time_begin <- max_time / 4 time_end <- max_time / 2  # create three distinct contact interventions # prepare an intervention that models school closures for 180 days close_schools <- intervention(   name = \"School closure\",   type = \"contacts\",   time_begin = time_begin,   time_end = time_end,   reduction = matrix(c(0.3, 0.01, 0.01)) )  # prepare an intervention which mostly affects adults 20 -- 65 close_workplaces <- intervention(   name = \"Workplace closure\",   type = \"contacts\",   time_begin = time_begin,   time_end = time_end,   reduction = matrix(c(0.01, 0.3, 0.01)) )  # prepare a combined intervention combined_intervention <- c(close_schools, close_workplaces) # create a mask-mandate rate intervention # prepare an intervention that models mask mandates for 300 days mask_mandate <- intervention(   name = \"mask mandate\",   type = \"rate\",   time_begin = time_begin,   time_end = time_end,   reduction = 0.1 ) # create intervention sets, which are combinations of contacts and rate # interventions intervention_scenarios <- list(   baseline = NULL,   scenario_01 = list(     contacts = close_schools   ),   scenario_02 = list(     contacts = close_workplaces   ),   scenario_03 = list(     contacts = combined_intervention   ),   scenario_04 = list(     transmission_rate = mask_mandate   ),   scenario_05 = list(     contacts = close_schools,     transmission_rate = mask_mandate   ),   scenario_06 = list(     contacts = close_workplaces,     transmission_rate = mask_mandate   ),   scenario_07 = list(     contacts = combined_intervention,     transmission_rate = mask_mandate   ) ) # pass the list of intervention sets to the model function output <- model_default(   uk_population,   intervention = intervention_scenarios,   time_end = 600 )  # examine the output head(output) #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571      600         1 #> 2:         0.1857143                 0.5     0.1428571      600         1 #> 3:         0.1857143                 0.5     0.1428571      600         1 #> 4:         0.1857143                 0.5     0.1428571      600         1 #> 5:         0.1857143                 0.5     0.1428571      600         1 #> 6:         0.1857143                 0.5     0.1428571      600         1 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>    <list[1]>                   <list[1]>         1        2 #> 3: <population[4]>    <list[1]>                   <list[1]>         1        3 #> 4: <population[4]>    <list[1]>                   <list[1]>         1        4 #> 5: <population[4]>    <list[1]>                   <list[1]>         1        5 #> 6: <population[4]>    <list[2]>                   <list[1]>         1        6 #>                    data #>                  <list> #> 1: <data.table[9015x4]> #> 2: <data.table[9015x4]> #> 3: <data.table[9015x4]> #> 4: <data.table[9015x4]> #> 5: <data.table[9015x4]> #> 6: <data.table[9015x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"output-type-for-list-intervention-inputs","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Output type for list intervention inputs","title":"Modelling parameter uncertainty and epidemic scenarios","text":"output model_*() either intervention vaccination passed list, nested <data.table>. similar output type parameters passed vectors, \"scenario\" column indicating intervention set distinct scenario, helps grouping model outputs \"data\".","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"combinations-of-intervention-and-vaccination-scenarios","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Combinations of intervention and vaccination scenarios","title":"Modelling parameter uncertainty and epidemic scenarios","text":"either intervention vaccination passed lists (intervention sets, vaccination regimes, respectively), model run combination elements. Thus \\(M\\) intervention sets \\(N\\) vaccination regimes, model runs \\(M \\times N\\) times, combination treated unique scenario. Note ‘intervention’ ‘vaccination’ scenarios automatically created, must passed explicitly NULL respective lists. number intervention vaccination combinations expected many, addition parameter uncertainty scenario (next section) may rapidly multiply number times model run. Users advised mindful number scenario combinations create.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"modelling-epidemic-response-scenarios-with-parameter-uncertainty","dir":"Articles","previous_headings":"","what":"Modelling epidemic response scenarios with parameter uncertainty","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics allows parameter uncertainty combined scenario models multiple intervention sets vaccination campaigns. , shall draw 100 samples transmission rate mean 0 low standard deviation 0.005. output nested <data.table> , can handled way.","code":"beta <- with_seed(   seed = 1,   code = {     rnorm(100, 1.3 / 7, 0.005)   } ) # this example includes 100 samples of transmission rates for each intervention # including the baseline output <- model_default(   uk_population,   transmission_rate = beta,   intervention = intervention_scenarios,   time_end = 600 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"output-type-for-intervention-and-parameter-set-combinations","dir":"Articles","previous_headings":"Modelling epidemic response scenarios with parameter uncertainty","what":"Output type for intervention and parameter set combinations","title":"Modelling parameter uncertainty and epidemic scenarios","text":"output model_*() either intervention vaccination passed list, infection parameters passed vector nested <data.table>. \"scenario\" column indicates intervention set distinct scenario, \"param_set\" column indicates parameter set used model run. parameters used scenario, allowing comparability scenarios aggregate level. output \\(M \\times N \\times S\\) rows (nested model outputs), \\(M\\) intervention sets, \\(N\\) vaccination regimes, \\(S\\) infection parameter sets.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"visualising-parameter-uncertainty-in-intervention-scenarios","dir":"Articles","previous_headings":"Modelling epidemic response scenarios with parameter uncertainty","what":"Visualising parameter uncertainty in intervention scenarios","title":"Modelling parameter uncertainty and epidemic scenarios","text":", show one way visualising epidemic size across scenarios, accounting parameter uncertainty. Figure 2: Infections averted relative epidemic response implementing scenario, accounting parameter uncertainty transmission rates.","code":"# select the data, the parameter set, and the scenario epidemic_size_estimates <- select(output, param_set, scenario, data) %>%   mutate(     size = map_dbl(       data, epidemic_size,       by_group = FALSE, include_deaths = FALSE     )   ) %>%   select(-data)  # Extract baseline and alternative scenarios df_scenario1 <- epidemic_size_estimates %>% filter(scenario == 1) df_scenarios_rest <- epidemic_size_estimates %>% filter(scenario != 1)  # Calculate differences as infections averted df_differences <- df_scenarios_rest %>%   left_join(df_scenario1, by = \"param_set\", suffix = c(\"_other\", \"_1\")) %>%   mutate(difference = size_1 - size_other) %>%   select(param_set, scenario = scenario_other, difference) # Plot distribution of differences ggplot(   df_differences,   aes(x = difference, y = factor(scenario), fill = factor(scenario)) ) +   stat_histinterval(     normalize = \"xy\", breaks = 11,     show.legend = FALSE   ) +   labs(     title = \"Scenario comparison\",     x = \"Infections averted\"   ) +   scale_x_continuous(     labels = scales::comma   ) +   scale_y_discrete(     name = NULL,     labels = labels[-1]   ) +   scale_fill_discrete_qualitative(     palette = \"Dynamic\"   ) +   theme_bw()"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"counter-intuitive-effects-of-time-limited-interventions","dir":"Articles","previous_headings":"","what":"Counter-intuitive effects of time-limited interventions","title":"Modelling parameter uncertainty and epidemic scenarios","text":"intervention scenarios modelled suggest : interventions disease transmission rates reduce infections hence epidemic final sizes; multiple interventions reduce epidemic final sizes single interventions. simple example show need always case, counter-intuitively, implementing interventions can lead larger epidemic final size implementing fewer interventions. phenomenon depends baseline transmission rate infection, select relatively low \\(R\\) 1.30 (corresponding pandemic influenza), higher \\(R\\) 1.58 \\(R\\) estimation step start vignette. Figure 3: Counter-intuitive effects time-limited interventions transmission rate high R values. Scenarios multiple interventions implemented may larger final epidemic size scenarios fewer interventions, e.g. ‘Close workplaces schools’ scenario. Plotting epidemic trajectories scenario value \\(R\\) gives fuller picture see unexpected effect. Figure 4: New daily infections intervention scenario two values R. period interventions active shown area shaded grey. interventions active ‘response’ scenario. Implementing interventions disease transmission rate leads ‘flattening curve’ (reduced daily incidence comparison response) interventions active. However, cases deferred rather prevented entirely, scenarios seen shifting incidence curve right (towards end simulation period). \\(R\\) low, incidence curve begins rise later \\(R\\) high (interventions applied epidemics actually miss projected peak epidemic, still shift cases right). Thus low \\(R\\) epidemics run course time simulation ends, making appear though interventions succeeded averting infections. higher \\(R\\), peak projected incidence curve without interventions falls within intervention period, thus interventions reduce new infections. scenarios multiple active interventions, large number susceptibles remain uninfected, compared scenarios fewer interventions. former thus see higher incidence peaks, leading counter-intuitively larger final epidemic sizes.","code":"# run each scenario for two values of R # no parameter uncertainty r_values <- c(1.3, round(r_estimate_mean, 2))  output <- model_default(   uk_population,   transmission_rate = r_values / 7,   intervention = intervention_scenarios,   time_end = 600 )  # obtain epidemic sizes epidemic_size_estimates <- mutate(   output,   size = map_dbl(     data, epidemic_size,     by_group = FALSE, include_deaths = FALSE   ),   r_value = rep(r_values, each = length(intervention_scenarios)),   scenario = rep(factor(labels, labels), 2) ) %>%   select(r_value, scenario, size) # plot the epidemic final size for each scenario for each R ggplot(epidemic_size_estimates) +   geom_col(     aes(scenario, size, fill = scenario),     show.legend = FALSE   ) +   scale_x_discrete(     name = NULL,     guide = guide_axis(n.dodge = 2)   ) +   scale_y_continuous(     labels = scales::comma,     name = \"Epidemic size\"   ) +   scale_fill_discrete_qualitative(     palette = \"Dynamic\"   ) +   facet_grid(     cols = vars(r_value),     labeller = labeller(       r_value = function(x) sprintf(\"R = %s\", x)     )   ) +   theme_bw() # get new infections per day daily_incidence <- mutate(   output,   r_value = rep(r_values, each = length(intervention_scenarios)),   scenario = rep(factor(labels, labels), 2),   incidence_data = map(data, new_infections, by_group = FALSE) ) %>%   select(scenario, r_value, incidence_data) %>%   unnest(incidence_data) ggplot(daily_incidence) +   annotate(     geom = \"rect\",     xmin = time_begin, xmax = time_end,     ymin = -Inf, ymax = Inf,     fill = \"grey90\", colour = \"grey\"   ) +   geom_line(     aes(time, new_infections, col = as.factor(r_value)),     show.legend = TRUE, linewidth = 1   ) +   scale_y_continuous(     labels = scales::label_comma(scale = 1e-3, suffix = \"K\")   ) +   scale_colour_discrete_qualitative(     palette = \"Dynamic\",     name = \"R\"   ) +   facet_wrap(facets = vars(scenario), nrow = 2) +   theme_bw() +   theme(legend.position = \"top\") +   labs(     x = \"Time since epidemic start\",     y = \"New infections\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"setup-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Setup and initial conditions","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"","code":"# set up initial conditions polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE ) contact_matrix <- t(contact_data$matrix) demography_vector <- contact_data$demography$population  # Prepare some initial objects uk_population <- population(   name = \"UK population\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = matrix(     c(1 - 1e-6, 0, 1e-6, 0, 0),     nrow = nrow(contact_matrix), ncol = 5L,     byrow = TRUE   ) )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"defining-a-time-dependent-function","dir":"Articles","previous_headings":"","what":"Defining a time-dependent function","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"Next prepare function affects transmission rate (often denoted \\(\\beta\\)) way two peaks two troughs transmission rate course year. Note example uses arbitrary function, might want choose realistic function model. Nonetheless, figures later show, can still generate realistic looking epidemic curves good starting point understanding feature works. can plot output function time examine effect \\(\\beta\\).","code":"# prepare function, refer to transmissiblity as beta in function name mod_beta <- function(time, x, tmax = 365 / 4) {   x + (x * sinpi(time / tmax)) } # get the function output # calculate beta - this is done automatically inside epidemic_*() output <- mod_beta(seq(0, 365), 1.3 / 7.0)  # plot the effect of time dependence ggplot() +   geom_line(     aes(x = seq(0, 365), y = output)   ) +   labs(x = \"Days\", y = \"Transmission rate (beta)\") +   theme_bw()"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"model-with-time-dependent-transmission","dir":"Articles","previous_headings":"","what":"Model with time-dependent transmission","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"Next run epidemic model including time dependence transmission rate. plot number newly infectious individuals check model dynamics. Note plotting code folded can expanded.  , can see epidemic large first wave, followed smaller second wave later model run (represents one year).","code":"# note transmission_rate is the function/model parameter # the function that affects it may have any name data <- model_default(   population = uk_population,   time_dependence = list(     transmission_rate = mod_beta   ),   time_end = 365, increment = 1 )  # get data on new infections data_infections <- new_infections(data) # plot data on new infections ggplot(data_infections) +   geom_line(     aes(x = time, y = new_infections, col = demography_group)   ) +   scale_y_continuous(     labels = scales::comma,     name = \"New infections\"   ) +   scale_color_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   theme_bw() +   coord_cartesian(     expand = FALSE   ) +   labs(     x = \"Time (days)\",     title = \"Effect of time-dependence of transmission rate\"   ) +   theme(     legend.position = \"top\",     plot.title = element_text(face = \"bold\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"non-pharmaceutical-interventions-and-time-dependence","dir":"Articles","previous_headings":"","what":"Non-pharmaceutical interventions and time-dependence","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"can also model effect imposing non-pharmaceutical interventions reduce social contacts, trajectory epidemic time-dependent changes transmission rate. example, impose intervention three phases: (1) closing schools, primarily affects age group 0 – 19, (2) closing workplaces, affects age groups > 20 years old, (3) partially reopening schools intervention lower effect social contacts age group 0 – 19. First construct intervention, object <contacts_intervention> class. run model specifying time-dependence transmission rate, well intervention social contacts. assign scenario names data, combine , plot comparison.  can observe implementing interventions social contacts can substantially reduce number infections age groups epidemic waves.","code":"# school closures affecting younger age groups close_schools <- intervention(   type = \"contacts\", time_begin = 50, time_end = 120,   reduction = c(0.1, 0.01, 0.01) )  # workplace closures affecting mostly adults close_workplaces <- intervention(   type = \"contacts\", time_begin = 65, time_end = 90,   reduction = c(0.01, 0.2, 0.2) )  # partially reopen schools partial_schools <- intervention(   type = \"contacts\", time_begin = 120, time_end = 180,   reduction = c(0.05, 0.01, 0.01) )  # combine interventions npis <- c(close_schools, close_workplaces, partial_schools)  # print to examine npis #>  #>  Intervention name:  #>  Begins at:  #>      npi_1 npi_2 npi_3 #> [1,]    50    65   120 #>  #>  Ends at:  #>      npi_1 npi_2 npi_3 #> [1,]   120    90   180 #>  #>  Reduction:  #>              Interv. 1 Interv. 2 Interv. 3 #> Demo. grp. 1      0.10      0.01      0.05 #> Demo. grp. 2      0.01      0.20      0.01 #> Demo. grp. 3      0.01      0.20      0.01 # run the model with interventions and time-dependence data_npi <- model_default(   population = uk_population,   intervention = list(contacts = npis),   time_dependence = list(     transmission_rate = mod_beta   ),   time_end = 365, increment = 1 )  # get the infections data_infections_npi <- new_infections(data_npi) data_infections$scenario <- \"baseline\" data_infections_npi$scenario <- \"intervention\"  # combine the data data_npi_compare <- bind_rows(data_infections, data_infections_npi) ggplot(data_npi_compare) +   geom_line(     aes(       x = time, y = new_infections,       col = demography_group, linetype = scenario     )   ) +   scale_y_continuous(     labels = scales::comma,     name = \"New infections\"   ) +   scale_color_brewer(     palette = \"Dark2\",     name = \"Age group\",     labels = c(\"Baseline\", \"Intervention\")   ) +   scale_linetype_manual(     name = \"Scenario\",     values = c(       baseline = \"dashed\",       intervention = \"solid\"     )   ) +   theme_bw() +   coord_cartesian(     expand = FALSE   ) +   labs(     x = \"Time (days)\",     title = \"Effect of multiple interventions on contacts\"   ) +   theme(     legend.position = \"top\",     plot.title = element_text(face = \"bold\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"timing-vaccination-to-prevent-epidemic-peaks","dir":"Articles","previous_headings":"","what":"Timing vaccination to prevent epidemic peaks","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"can model effect timing vaccination doses begin end first wave, 120 days. example include non-pharmaceutical interventions. First define vaccination regime targets adults aged 40 years priority group. age groups vaccinated campaign. also assume single dose vaccine confers immunity (.e., non-leaky vaccination). model effect administering vaccine doses expected peaks epidemic waves, plot outcome.  , can see 2 million individuals vaccinated (immunised; blue line, right-hand Y axis) 100 days end first wave infections, start second wave infections. Vaccination reduces number daily infections among individuals age groups second wave. peak, vaccination scenario sees approximately 5,000 fewer daily infections baseline scenario, may represent substantial benefit public health.","code":"# define vaccination object vax_regime <- vaccination(   nu = matrix(0.001, nrow = 3, ncol = 1),   time_begin = matrix(c(0, 0, 120)),   time_end = matrix(c(0, 0, 220)) )  # view the vaccination object vax_regime #>  #>  Vaccination name:  #>  Begins at:  #>      dose_1 #> [1,]      0 #> [2,]      0 #> [3,]    120 #>  #>  Ends at:  #>      dose_1 #> [1,]      0 #> [2,]      0 #> [3,]    220 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  0.001 #> [2,]  0.001 #> [3,]  0.001 # pass time dependence and vaccination. Note no interventions data_vax <- model_default(   population = uk_population,   vaccination = vax_regime,   time_dependence = list(     transmission_rate = mod_beta   ),   time_end = 365, increment = 1 )  # collect data and add scenario data_vax_infections <- new_infections(   data_vax,   compartments_from_susceptible = c(\"exposed\", \"vaccinated\") ) data_vax_infections$scenario <- \"vaccination\"  # combine data data_vax_compare <- bind_rows(data_infections, data_vax_infections) ggplot(data_vax_compare) +   geom_rect(     aes(       xmin = 120, xmax = 220,       ymin = 0, ymax = 20e3     ),     fill = \"grey\", alpha = 0.1   ) +   geom_line(     data = filter(       data_vax, compartment == \"vaccinated\", demography_group == \"40+\"     ),     aes(time, value / 1e2),     colour = \"darkblue\"   ) +   annotate(     geom = \"text\",     x = 190,     y = 10e3,     label = \"Vaccines administered (100 days)\",     angle = 90,     colour = \"darkblue\"   ) +   geom_line(     aes(       x = time, y = new_infections,       col = demography_group, linetype = scenario     )   ) +   scale_y_continuous(     labels = scales::comma,     name = \"New infections\",     sec.axis = dup_axis(       trans = function(x) x * 1e2,       name = \"Individuals vaccinated\",       labels = function(x) {         scales::comma(x, scale = 1e-6, suffix = \"M\")       }     )   ) +   scale_color_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   scale_linetype_manual(     name = \"Scenario\",     values = c(       baseline = \"dashed\",       vaccination = \"solid\"     )   ) +   theme_bw() +   coord_cartesian(     ylim = c(0, 20e3),     expand = FALSE   ) +   labs(     x = \"Time (days)\",     title = \"Effect of a vaccination regime\"   ) +   theme(     legend.position = \"top\",     plot.title = element_text(face = \"bold\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling the effect of a vaccination campaign","text":"Prepare population contact data. Prepare initial conditions age group. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE ) #> Using POLYMOD social contact data. To cite this in a publication, use the 'get_citation()' function #> Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"prepare-a-vaccination-campaign","dir":"Articles","previous_headings":"","what":"Prepare a vaccination campaign","title":"Modelling the effect of a vaccination campaign","text":"Prepare vaccination campaign targeting individuals aged 65.","code":"# prepare a vaccination object vaccinate_elders <- vaccination(   name = \"vaccinate elders\",   time_begin = matrix(100, nrow(contact_matrix)),   time_end = matrix(250, nrow(contact_matrix)),   nu = matrix(c(0.0001, 0, 0)) )  # view vaccination object vaccinate_elders #> <vaccination> object #>  #>  Vaccination name:  #> \"vaccinate elders\" #>  #>  Begins at:  #>      dose_1 #> [1,]    100 #> [2,]    100 #> [3,]    100 #>  #>  Ends at:  #>      dose_1 #> [1,]    250 #> [2,]    250 #> [3,]    250 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  1e-04 #> [2,]  0e+00 #> [3,]  0e+00"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Modelling the effect of a vaccination campaign","text":"","code":"# run an epidemic model using `epidemic` output <- model_default(   population = uk_population,   vaccination = vaccinate_elders,   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Modelling the effect of a vaccination campaign","text":"Plot epidemic time, showing number individuals exposed, infected, vaccinated compartments.","code":"# plot figure of epidemic curve filter(output, compartment %in% c(\"exposed\", \"infectious\")) %>%   ggplot(     aes(       x = time,       y = value,       col = demography_group,       linetype = compartment     )   ) +   geom_line() +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 500e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Pratik Gupte. Author, maintainer, copyright holder. Rosalind Eggo. Author, copyright holder. Edwin Van Leeuwen. Author, copyright holder. Adam Kucharski. Contributor, reviewer. Tim Taylor. Contributor, reviewer. Hugo Gruson. Reviewer. Joshua W. Lambert. Reviewer.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Gupte P, Eggo R, Van Leeuwen E (2024). epidemics: Library Compartmental Epidemic Scenario Models. R package version 0.2.0.9000,  https://epiverse-trace.github.io/epidemics/, https://github.com/epiverse-trace/epidemics.","code":"@Manual{,   title = {epidemics: A Library of Compartmental Epidemic Scenario Models},   author = {Pratik Gupte and Rosalind Eggo and Edwin {Van Leeuwen}},   year = {2024},   note = {R package version 0.2.0.9000,  https://epiverse-trace.github.io/epidemics/},   url = {https://github.com/epiverse-trace/epidemics}, }"},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"epidemics-a-library-of-compartmental-epidemic-scenario-models-","dir":"","previous_headings":"","what":"A Library of Compartmental Epidemic Scenario Models","title":"A Library of Compartmental Epidemic Scenario Models","text":"epidemics R package provides convenient interface library compartmental models can help model epidemic scenarios directly transmitted respiratory infections influenza Covid-19 well haemorrhagic fevers Ebola virus disease. models epidemics implement methods outlined Bjørnstad et al. (2020a) Bjørnstad et al. (2020b). models epidemics can help provide rough estimates course epidemics, effectiveness pharmaceutical non-pharmaceutical interventions. epidemics relies Eigen via {RcppEigen}, Boost Odeint via {BH}, developed Centre Mathematical Modelling Infectious Diseases London School Hygiene Tropical Medicine part Epiverse-TRACE initiative.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"A Library of Compartmental Epidemic Scenario Models","text":"current development version epidemics can installed GitHub using pak package.","code":"if(!require(\"pak\")) install.packages(\"pak\") pak::pak(\"epiverse-trace/epidemics\")"},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"installation-notes","dir":"","previous_headings":"Installation","what":"Installation Notes","title":"A Library of Compartmental Epidemic Scenario Models","text":"users also using developing packages use Stan might face issues modified toolchain accommodate packages cmdstanr; see resolved issue starting point face similar problems. Users Windows systems need packages RTools family installed system path; see link guidance using RTools version R.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"quick-start","dir":"","previous_headings":"","what":"Quick start","title":"A Library of Compartmental Epidemic Scenario Models","text":"show example using default model epidemics model epidemic U.K. population R0 similar pandemic influenza, heterogeneity social contacts among different age groups, implementation school closures dampen spread infection. Prepare social contact pattern population (, U.K population), divided three age groups: 0 – 19, 20 – 39, 40+. Prepare initial conditions population age group — , one every million individuals infected start epidemic (total 60 infections). Prepare object class <population>, using function population(). Define intervention close schools two months. intervention mostly affects individuals age range 0 – 19, reduces contacts 50%, reducing contacts age groups 1%. object class <contacts_intervention>, created using function intervention(), setting type = \"contacts\". Run default epidemic model, using function model_default(). assume R0 1.5 similar pandemic influenza, infectious period 7 days, pre-infectious period 3 days. values can calculate transmission rate β 1.5 / 7.0, infectiousness_rate α 1.0 / 3.0 recovery_rate γ 1.0 / 7.0. Visualise development individuals “infectious” compartment model time. Note curves represent number individuals infectious, number newly infectious individuals.","code":"# load epidemics library(epidemics) library(ggplot2) library(dplyr) # load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data[[\"matrix\"]])  # prepare the demography vector demography_vector <- contact_data[[\"demography\"]][[\"population\"]] names(demography_vector) <- rownames(contact_matrix) # initial conditions: one in every 1 million is infected initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions ) rownames(initial_conditions) <- rownames(contact_matrix) # prepare the population to model as affected by the epidemic uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions ) # an intervention to close schools close_schools <- intervention(   type = \"contacts\",   time_begin = 200,   time_end = 260,   reduction = matrix(c(0.5, 0.01, 0.01)) )  # view the intervention close_schools #>  #>  Intervention name:  #>  Begins at:  #> [1] 200 #>  #>  Ends at:  #> [1] 260 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.50 #> Demo. grp. 2      0.01 #> Demo. grp. 3      0.01 # run an epidemic model using `epidemic()` output <- model_default(   population = uk_population,   transmission_rate = 1.5 / 7.0,   infectiousness_rate = 1.0 / 3.0,   recovery_rate = 1.0 / 7.0,   intervention = list(contacts = close_schools),   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"package-vignettes","dir":"","previous_headings":"","what":"Package vignettes","title":"A Library of Compartmental Epidemic Scenario Models","text":"details use epidemics can found online documentation package vignettes, “Articles”.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"package-models","dir":"","previous_headings":"","what":"Package models","title":"A Library of Compartmental Epidemic Scenario Models","text":"epidemics currently provides three models: deterministic SEIR-V model susceptible, exposed, infectious, recovered, vaccinated compartments (SEIR-V), allowing heterogeneity social contacts, implementation group-specific non-pharmaceutical intervention reduces social contacts, vaccination regime group-specific start end dates, deterministic Vacamole model developed RIVM, Dutch Public Health Institute Covid-19 pandemic, focus scenario modelling hospitalisation vaccination (Ainslie et al. 2022), stochastic, discrete-time, compartmental SEIR model suitable modelling haemorrhagic fevers Ebola Virus Disease, including hospitalisation hospital funeral transmissions, adapted Li et al. (2019) Getz Dougherty (2018), initial implementation compartmental model diphtheria context internally displaced persons camps, including reporting rate, hospitalisation rate, delays entering leaving hospital, taken Finger et al. (2019). models planned added near future. Please get touch like see model added epidemics model library — happy help translating framework, special focus making model applicable LMIC settings.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"related-projects","dir":"","previous_headings":"","what":"Related projects","title":"A Library of Compartmental Epidemic Scenario Models","text":"epidemics aims library published epidemiological models, following projects may useful building models: R package finalsize also developed Epiverse-TRACE helps calculate final size epidemic heterogeneous population, quicker option estimates total infections temporal dynamics less important; Epirecipes project cookbook-style guide focuses different ways implement epidemic models R languages; R package odin generates systems ordinary differential equations (ODE) integrate , using domain specific language (DSL), widely used translate compartmental models R C code performance gains; Many R packages provide modelling options, can found CRAN Epidemiology Task View section “Infectious disease modelling”.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"help","dir":"","previous_headings":"","what":"Help","title":"A Library of Compartmental Epidemic Scenario Models","text":"report bug please open issue.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"contribute","dir":"","previous_headings":"","what":"Contribute","title":"A Library of Compartmental Epidemic Scenario Models","text":"Contributions epidemics welcomed. Please follow package contributing guide.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of conduct","title":"A Library of Compartmental Epidemic Scenario Models","text":"Please note epidemics project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a list to a intervention object — as.intervention","title":"Convert a list to a intervention object — as.intervention","text":"Convert list intervention object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a list to a intervention object — as.intervention","text":"","code":"as.intervention(x, type = c(\"contacts\", \"rate\"))"},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a list to a intervention object — as.intervention","text":"x list, object inherits list. type string type intervention: \"contacts\" <contact_intervention> \"rate\" <rate_intervention>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a list to a intervention object — as.intervention","text":"intervention class object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a list to a intervention object — as.intervention","text":"","code":"# prepare a list npi <- list(   name = \"npi\",   type = \"contacts\",   time_begin = 30,   time_end = 60,   reduction = rep(0.1, 3) )  as.intervention(npi) #> <contacts_intervention> object #>  #>  Intervention name:  #> \"npi\" #>  #>  Begins at:  #> [1] 30 #>  #>  Ends at:  #> [1] 60 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1       0.1 #> Demo. grp. 2       0.1 #> Demo. grp. 3       0.1"},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a list to a vaccination object — as.vaccination","title":"Convert a list to a vaccination object — as.vaccination","text":"Convert list vaccination object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a list to a vaccination object — as.vaccination","text":"","code":"as.vaccination(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a list to a vaccination object — as.vaccination","text":"x list, object inherits list.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a list to a vaccination object — as.vaccination","text":"vaccination class object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a list to a vaccination object — as.vaccination","text":"","code":"# prepare a list vax <- list(   name = \"vax_regime\",   time_begin = matrix(1),   time_end = matrix(100),   nu = matrix(0.001) )  as.vaccination(vax) #> <vaccination> object #>  #>  Vaccination name:  #> \"vax_regime\" #>  #>  Begins at:  #>      dose_1 #> [1,]      1 #>  #>  Ends at:  #>      dose_1 #> [1,]    100 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  0.001"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert properties of a intervention object — assert_intervention","title":"Assert properties of a intervention object — assert_intervention","text":"Assert objects intervention class properties expected epidemic model. See intervention() specific model functions check intervention properties required model. function internal use argument checking functions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert properties of a intervention object — assert_intervention","text":"","code":"assert_intervention(x, type = c(\"contacts\", \"rate\"), population = NULL)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert properties of a intervention object — assert_intervention","text":"x intervention object. type string type intervention check . May one \"contacts\" \"rate\". population optional argument population object. present, used check whether intervention object x corresponding values reduction demographic group population.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assert properties of a intervention object — assert_intervention","text":"Silently returns <intervention>-superclass object x class x, .e., <rate_intervention> <contacts_intervention>. Primarily called side effects throwing errors x meet certain requirements.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert properties of a population object — assert_population","title":"Assert properties of a population object — assert_population","text":"Assert objects population class parameters expected epidemic model. See population() specific epidemic functions check population parameters required model. function internal use argument checking functions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert properties of a population object — assert_population","text":"","code":"assert_population(x, compartments, demography_vector = NULL)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert properties of a population object — assert_population","text":"x <population> object. compartments character vector giving names model compartments whose length taken reference number columns initial_conditions matrix x. demography_vector optional numeric vector whose length used check length demography vector present x.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assert properties of a population object — assert_population","text":"Silently returns <population> object x. Primarily called side effects throwing errors x meet certain requirements.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert properties of a vaccination object — assert_vaccination","title":"Assert properties of a vaccination object — assert_vaccination","text":"Assert objects vaccination class parameters expected epidemic model. See vaccination() specific epidemic functions check vaccination properties required model. function internal use argument checking functions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert properties of a vaccination object — assert_vaccination","text":"","code":"assert_vaccination(x, doses, population = NULL)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert properties of a vaccination object — assert_vaccination","text":"x vaccination object. doses number doses expected vaccination object. population optional argument <population> object. present, used check whether vaccination object x corresponding values demographic group population.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assert properties of a vaccination object — assert_vaccination","text":"Silently returns <vaccination> object x. Primarily called side effects throwing errors x meet certain requirements.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":null,"dir":"Reference","previous_headings":"","what":"Cross-check model elements — cross_checking_inputs","title":"Cross-check model elements — cross_checking_inputs","text":"Check model elements compatibility population epidemic model, returning compatible dummy values model elements applied, erroring appropriately model elements compatible population characteristics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cross-check model elements — cross_checking_inputs","text":"","code":".cross_check_intervention(x, population, allowed_targets)  .cross_check_vaccination(x, population, doses)  .cross_check_timedep(x, allowed_targets)  .cross_check_popchange(x, population)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cross-check model elements — cross_checking_inputs","text":"x Model input checked. expected value x depends function: .cross_check_intervention(): named list <intervention> objects; .cross_check_vaccination(): <vaccination> object; .cross_check_timedep(): named list functions two arguments, time x, typically returning x function time; .cross_check_popchange(): named list two elements, time values, describing times values number susceptibles changes epidemic model. population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). allowed_targets model components, infection parameters, model input x affects. doses expected number vaccination doses.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cross-check model elements — cross_checking_inputs","text":".cross_check_intervention() returns named list least elements \"contacts\" describing <contacts_intervention> population (among allowed targets), <rate_intervention> transmission rate parameter. present x, returned , substituted missing. interventions also returned. x NULL, dummy contact rate interventions returned list. .cross_check_vaccination() returns x checking suitable population, dummy vaccination regime doses number doses age group. .cross_check_timedep() returns x x NULL, otherwise returns dummy function operating transmission rate parameter default; see .no_time_dependence(); .cross_check_popchange() returns x checks population x NULL, otherwise returns dummy list population change; see .no_population_change().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"Calculate Cumulative Effect Interventions Social Contacts Scale Contact Matrix Active Interventions Social Contacts","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"","code":"cumulative_contacts_intervention(t, time_begin, time_end, reduction)  intervention_on_cm(t, cm, time_begin, time_end, cr)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"t current time. time_begin numeric vector start times interventions modelled. time_end numeric vector end times interventions modelled. Must length time_begin. reduction numeric matrix rows give effect interventions demographic group, columns give proportion reduction contacts. two interventions overlap, proportions added, maximum possible value 1.0 (.e., contacts). cm numeric matrix social contacts demographic groups.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"cumulative_contacts_intervention() returns numeric vector proportion reduction contacts demographic group. intervention_on_cm() returns contact matrix cm scaled cumulative effect active interventions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":"Calculate Cumulative Effect Interventions Rate Parameters","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":"","code":"cumulative_rate_intervention(t, time_begin, time_end, reduction)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":"t current time. time_begin numeric vector start times interventions modelled. time_end numeric vector end times interventions modelled. Must length time_begin. reduction numeric vector element gives effect corresponding intervention model rate parameters. two interventions overlap, proportions added, maximum possible value 1.0 (.e., rate set zero).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":"cumulative_rate_intervention() returns number proportion reduction model rate parameter. intervention_on_cm() returns contact matrix cm scaled cumulative effect active interventions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":null,"dir":"Reference","previous_headings":"","what":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"compartmental model optional non-pharmaceutical intervention optional vaccination regime. function intended called internally model_default_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"","code":".model_default_cpp(   initial_state,   transmission_rate,   infectiousness_rate,   recovery_rate,   contact_matrix,   npi_time_begin,   npi_time_end,   npi_cr,   vax_time_begin,   vax_time_end,   vax_nu,   rate_interventions,   time_dependence,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"initial_state matrix initial state compartments. transmission_rate transmission rate \\(\\beta\\) unvaccinated partially vaccinated individuals infected disease. infectiousness_rate rate transition exposed infectious \\(\\alpha\\). recovery_rate recovery rate \\(\\gamma\\). contact_matrix population contact matrix. npi_time_begin start time non-pharmaceutical interventions . npi_time_end end time non-pharmaceutical interventions. npi_cr reduction contacts non-pharmaceutical interventions. vax_time_begin start time vaccination campaigns. vax_time_end end time vaccination campaigns. vax_nu vaccination rate vaccination campaigns. rate_interventions named list <rate_intervention> objects. time_dependence named list functions parameter time dependence. time_end end time simulation. increment time increment simulation.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"two element list, first element list matrices whose elements correspond numbers individuals compartment specified initial conditions matrix (see population()). second list element vector timesteps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":null,"dir":"Reference","previous_headings":"","what":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"compartmental model diphtheria parameters help account case reporting rate, delays seeking hospitalisation, time spent hospitalised compartment. function intended called internally model_diphtheria_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"","code":".model_diphtheria_cpp(   initial_state,   transmission_rate,   infectiousness_rate,   recovery_rate,   reporting_rate,   prop_hosp,   hosp_entry_rate,   hosp_exit_rate,   rate_interventions,   time_dependence,   pop_change_times,   pop_change_values,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"initial_state matrix initial state compartments. transmission_rate transmission rate \\(\\beta\\). infectiousness_rate rate transition exposed infectious \\(\\alpha\\). recovery_rate recovery rate \\(\\gamma\\). reporting_rate recovery rate \\(\\r\\). prop_hosp proportion individuals hospitalised \\(\\eta\\). hosp_entry_rate rate individuals hospitalised, represented 1 / time hospitalisation \\(\\tau_1\\). hosp_exit_rate rate individuals discharged hospital, represented 1 / time discharge \\(\\tau_2\\). rate_interventions named list <rate_intervention> objects. time_dependence named list functions parameter time dependence. pop_change_times numeric vector times population susceptibles changes. pop_change_values Rcpp List numeric vectors giving value changes demographic group change population. time_end end time simulation. increment time increment simulation.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"two element list, first element list matrices whose elements correspond numbers individuals compartment specified initial conditions matrix. second list element vector timesteps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":null,"dir":"Reference","previous_headings":"","what":"Run the RIVM Vacamole model — .model_vacamole_cpp","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"Vacamole deterministic, compartmental epidemic model built Kylie Ainslie others RIVM, Dutch Public Health Institute Covid-19 pandemic, focus scenario modelling hospitalisation vaccination. Model code: https://github.com/kylieainslie/vacamole Manuscript describing model application: https://doi.org/10.2807/1560-7917.ES.2022.27.44.2101090 function intended called internally model_vacamole_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"","code":".model_vacamole_cpp(   initial_state,   transmission_rate,   transmission_rate_vax,   infectiousness_rate,   mortality_rate,   mortality_rate_vax,   hospitalisation_rate,   hospitalisation_rate_vax,   recovery_rate,   contact_matrix,   npi_time_begin,   npi_time_end,   npi_cr,   vax_time_begin,   vax_time_end,   vax_nu,   rate_interventions,   time_dependence,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"initial_state matrix initial state compartments. transmission_rate transmission rate \\(\\beta\\) unvaccinated partially vaccinated individuals infected disease. transmission_rate_vax transmission rate \\(\\beta_V\\) individuals received two vaccine doses infected disease. infectiousness_rate rate transition exposed infectious \\(\\alpha\\). common fully susceptible, partially vaccinated, fully vaccinated individuals (fully vaccinated represents two doses). mortality_rate mortality rate fully susceptible partially vaccinated unprotected individuals. mortality_rate_vax mortality rate individuals protected vaccination. hospitalisation_rate hospitalisation rate fully susceptible partially vaccinated unprotected individuals. hospitalisation_rate_vax hospitalisation rate individuals protected vaccination. recovery_rate recovery rate \\(\\gamma\\). contact_matrix population contact matrix. npi_time_begin start time non-pharmaceutical interventions . npi_time_end end time non-pharmaceutical interventions. npi_cr reduction contacts non-pharmaceutical interventions. vax_time_begin start time vaccination campaigns. vax_time_end end time vaccination campaigns. vax_nu vaccination rate vaccination campaigns. rate_interventions named list <rate_intervention> objects. time_dependence named list functions parameter time dependence. time_end end time simulation. increment time increment simulation.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"two element list, first element list matrices whose elements correspond numbers individuals compartment specified initial conditions matrix (see population()). second list element vector timesteps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":null,"dir":"Reference","previous_headings":"","what":"Ordinary Differential Equations for the Default Model — .ode_model_default","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"Provides ODEs default SEIR-V model format suitable passing deSolve::lsoda(). See model_default() list required parameters.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"","code":".ode_model_default(t, y, params)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"t single number timestep integrate. y conditions epidemiological compartments. params parameters, passed named list.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"list vector many elements number demographic groups times number epidemiological compartments. value gives change number individuals compartment.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":null,"dir":"Reference","previous_headings":"","what":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"Provides ODEs RIVM Vacamole model format suitable passing deSolve::lsoda(). See model_vacamole() list required parameters.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"","code":".ode_model_vacamole(t, y, params)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"t single number timestep integrate. y conditions epidemiological compartments. params parameters, passed named list.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"list vector many elements number demographic groups times number epidemiological compartments. value gives change number individuals compartment.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-output_to_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Return ODE model output as a data.table — .output_to_df","title":"Return ODE model output as a data.table — .output_to_df","text":"Return ODE model output data.table","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-output_to_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return ODE model output as a data.table — .output_to_df","text":"","code":".output_to_df(output, population, compartments)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-output_to_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return ODE model output as a data.table — .output_to_df","text":"output model output, must two element list (epidemic) models, names \"x\" \"time\", \"x\" represents condition compartment timestep \"time\". population <population> object corresponding population used epidemic model. <population> object used generate names demographic groups, named. compartments vector model compartment names.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-output_to_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return ODE model output as a data.table — .output_to_df","text":"<data.table> columns \"compartment\", \"demography_group\", \"value\", \"time\"; specify epidemiological compartment, name demography group, number individuals group compartment, model timestep, respectively. Names demographic groups generated names provided population object; form \"demo_group_X\".","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare a <population> for an epidemic model — .prepare_population","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"Prepare <population> epidemic model","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"","code":".prepare_population(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"x <population>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"named list \"contact_matrix\", population social contacts matrix scaled largest real eigenvalue demography vector, \"initial_state\", proportional initial state multiplied demography vector.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the epidemic size — epidemic_size","title":"Get the epidemic size — epidemic_size","text":"Get size epidemic stage start end. calculated number individuals recovered infection stage epidemic.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the epidemic size — epidemic_size","text":"","code":"epidemic_size(data, stage = 1, by_group = TRUE, include_deaths = TRUE)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the epidemic size — epidemic_size","text":"data table model output, typically output model_default() similar functions. stage stage epidemic return epidemic size; , 0.0 represents initial conditions epidemic (0% model time ), 1.0 represents end epidemic model (100% model time). values returned stage = 1.0 represent final size epidemic. by_group logical representing whether epidemic size returned demographic group, whether single population-wide value returned. Defaults TRUE. include_deaths logical value indicates whether count dead individuals epidemic size calculation. Defaults TRUE, makes function look \"dead\" compartment data. column, function returns final number recovered removed individuals demographic group.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the epidemic size — epidemic_size","text":"single number by_group = FALSE, vector numbers length number demographic groups by_group = TRUE. Returns absolute sizes proportions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the epidemic size — epidemic_size","text":"function can used calculate final size epidemic, setting stage = 1.0 (100% model time; default). function allows calculation epidemic sizes demographic group well total epidemic size.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the epidemic size — epidemic_size","text":"","code":"# create a population uk_population <- population(   name = \"UK population\",   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0, 0),     nrow = 1, ncol = 5L   ) )  # run epidemic simulation with no vaccination or intervention data <- model_default(   population = uk_population )  # get the final epidemic size epidemic_size(data) #> No 'dead' compartment found in `data`; counting only 'recovered' individuals in the epidemic size. #> demo_group_1  #>     481200.2   # get the epidemic size at the halfway point epidemic_size(data, stage = 0.5) #> No 'dead' compartment found in `data`; counting only 'recovered' individuals in the epidemic size. #> demo_group_1  #>     81921.88"},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemics-package.html","id":null,"dir":"Reference","previous_headings":"","what":"epidemics: A Library of Compartmental Epidemic Scenario Models — epidemics-package","title":"epidemics: A Library of Compartmental Epidemic Scenario Models — epidemics-package","text":"library compartmental epidemic models taken published literature, classes represent populations heterogeneous characteristics, public health response measures including non-pharmaceutical interventions social contacts, non-pharmaceutical pharmaceutical interventions affect disease transmissibility, vaccination regimes, disease seasonality, can combined compose epidemic scenarios.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemics-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"epidemics: A Library of Compartmental Epidemic Scenario Models — epidemics-package","text":"Maintainer: Pratik Gupte pratik.gupte@lshtm.ac.uk (ORCID) [copyright holder] Authors: Rosalind Eggo rosalind.eggo@lshtm.ac.uk (ORCID) [copyright holder] Edwin Van Leeuwen edwin.vanleeuwen@ukhsa.gov.uk (ORCID) [copyright holder] contributors: Adam Kucharski adam.kucharski@lshtm.ac.uk (ORCID) [contributor, reviewer] Tim Taylor tim.taylor@hiddenelephants.co.uk (ORCID) [contributor, reviewer] Hugo Gruson hugo.gruson@data.org (ORCID) [reviewer] Joshua W. Lambert joshua.lambert@lshtm.ac.uk (ORCID) [reviewer]","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an intervention for an epidemic model — intervention","title":"Create an intervention for an epidemic model — intervention","text":"Prepare object <intervention> super-class specifies modification model parameters. <contacts_intervention> used simulate non-pharmaceutical intervention (NPI) regime reduces population's social contacts. <rate_intervention> used simulate reduction model's rate parameters (transmission rate \\(\\beta\\)), can used represent pharmaceutical interventions improved treatment, also NPIs wearing masks. Interventions single start end time applies demographic groups population, can groups-specific effects reduction contacts. Combine <intervention>-inheriting objects create sequential overlapping intervention regimes using c() two <intervention>-inheriting objects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an intervention for an epidemic model — intervention","text":"","code":"intervention(name = NA_character_, type, time_begin, time_end, reduction)  is_intervention(x)  is_contacts_intervention(x)  is_rate_intervention(x)  # S3 method for contacts_intervention c(x, ...)  # S3 method for rate_intervention c(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an intervention for an epidemic model — intervention","text":"name String name intervention. type String type intervention. May one \"contacts\" \"rate\", <contacts_intervention> <rate_intervention> respectively. time_begin Single number start time intervention. time_end Single number end time intervention. reduction <contacts_intervention>s, matrix many rows number demographic groups type population, single column. element gives group-specific proportion reduction contacts. <rate_intervention>s, single number giving proportion reduction model parameter contacts. See details c() can used combine interventions sub-class. x <intervention> object, object checked <intervention> object. ... intervention objects combine x create multi-dose <intervention> object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an intervention for an epidemic model — intervention","text":"object <intervention> S3 super-class, possible sub-classes <contact_intervention> <rate_intervention>. Concatenating two <intervention>-inheriting objects using c() also returns <intervention>-inheriting object sub-class. object holds intervention-specific start end times, reductions specified constituent intervention actions (demographic group intervention contacts). combined effect actions population handled internally epidemic model functions. \"null\" intervention generated using .no_contacts_intervention(population) .no_rate_intervention() returns <intervention> appropriate sub-class start end times, effect set 0.0. is_intervention(), is_contacts_intervention(), is_rate_intervention() return logical value whether object <intervention>, <contacts_intervention>, <rate_intervention> class, respectively.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an intervention for an epidemic model — intervention","text":"Epidemic models can accommodate interventions contacts able accommodate number interventions different start end times different group-specific effects. Epidemic models can accommodate interventions rates also able accommodate number interventions different start end times, uniform effect relevant rate. multiple contact interventions combined using c(), reduction contacts stacked column wise form matrix \\([, j]\\). multiple rate interventions combined using c(), reduction rate concatenated vector length number interventions. Models model_default_cpp() set treat interventions overlapping periods (.e., overlap time active ) additive effect contact rate reductions. contact reductions, group-specific effect \\(J\\) overlapping interventions thus vector \\(\\sum_{j = 1}^J x_{ij}\\), demographic group \\(\\). handled internally epidemic model code. example, contact reduction matrix two perfectly overlapping interventions (\\(J = 2\\)) different effects across three demographic groups (\\(= 3\\)) represented : \\(\\begin{bmatrix}0.1 & 0.05\\\\0.1 & 0.1\\\\0.1 & 0.0\\end{bmatrix}\\) epidemic models, cumulative group-specific effect interventions active \\((0.15, 0.2, 0.1)\\). rate reductions, effect overlapping interventions reduce particular rate also considered additive.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an intervention for an epidemic model — intervention","text":"","code":"# assuming a population with two age groups, 0 -- 18, and 18+ # an example in which schools are closed for 30 days (or other time units) close_schools <- intervention(   name = \"close schools\",   type = \"contacts\",   time_begin = 50,   time_end = 80,   reduction = matrix(c(0.5, 0.01)) # reduces contacts differentially ) close_schools #> <contacts_intervention> object #>  #>  Intervention name:  #> \"close schools\" #>  #>  Begins at:  #> [1] 50 #>  #>  Ends at:  #> [1] 80 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.50 #> Demo. grp. 2      0.01  # Check for intervention class is_contacts_intervention(close_schools) #> [1] TRUE  # Concatenating interventions # create first intervention npi_1 <- intervention(   type = \"contacts\",   time_begin = 30,   time_end = 60,   reduction = matrix(0.1) )  # second intervention npi_2 <- intervention(   type = \"contacts\",   time_begin = 45,   time_end = 75,   reduction = matrix(0.1) )  c(npi_1, npi_2) #> <contacts_intervention> object #>  #>  Intervention name:  #> NA #>  #>  Begins at:  #>      npi_1 npi_2 #> [1,]    30    45 #>  #>  Ends at:  #>      npi_1 npi_2 #> [1,]    60    75 #>  #>  Reduction:  #>              Interv. 1 Interv. 2 #> Demo. grp. 1       0.1       0.1"},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for the  super-class and sub-classes — intervention_constructor","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"Constructor  super-class sub-classes Constructor new <contacts_intervention> Constructor new <rate_intervention>","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"","code":"new_intervention(   name = NA_character_,   time_begin,   time_end,   reduction,   ...,   class )  new_contacts_intervention(name, time_begin, time_end, reduction)  new_rate_intervention(name, time_begin, time_end, reduction)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"name String name intervention. time_begin matrix single element giving start time intervention. time_end matrix single element giving end time intervention. reduction matrix single column many rows demographic groups targeted intervention. See intervention() details types intervention can created requirements type reduction. ... parameters passed constructor. class string giving type intervention; used generate intervention sub-classes.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"new_intervention() returns object inherits <intervention> class. new_contacts_intervention() returns object sub-class <intervention> called <contacts_intervention>. new_rate_intervention() returns object sub-class <intervention> called <rate_intervention>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_on_rates.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply interventions to rate parameters — intervention_on_rates","title":"Apply interventions to rate parameters — intervention_on_rates","text":"Apply interventions rate parameters","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_on_rates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply interventions to rate parameters — intervention_on_rates","text":"","code":"intervention_on_rates(t, interventions, parameters)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_on_rates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply interventions to rate parameters — intervention_on_rates","text":"t single number simulation time. interventions named list list-like objects least three members \"time_begin\", \"time_end\", \"reduction\". used calculate effect named parameters simulation. parameters named list numeric parameters affected interventions. represents model parameters, transmission rate, \\(\\beta\\), recovery rate, \\(\\gamma\\).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_on_rates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Apply interventions to rate parameters — intervention_on_rates","text":"named list length parameters, names. parameters can used timestep ODE model.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":null,"dir":"Reference","previous_headings":"","what":"Model an SEIR-V epidemic with interventions — model_default","title":"Model an SEIR-V epidemic with interventions — model_default","text":"Simulate epidemic using deterministic, compartmental epidemic model compartments \"susceptible\", \"exposed\", \"infectious\", \"recovered\", \"vaccinated\". model can accommodate heterogeneity social contacts among demographic groups, well differences sizes demographic groups. population, transmission_rate, infectiousness_rate, recovery_rate arguments mandatory, passing intervention vaccination optional can used simulate scenarios different epidemic responses different levels type response. See Details information.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model an SEIR-V epidemic with interventions — model_default","text":"","code":"model_default(   population,   transmission_rate = 1.3/7,   infectiousness_rate = 1/2,   recovery_rate = 1/7,   intervention = NULL,   vaccination = NULL,   time_dependence = NULL,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model an SEIR-V epidemic with interventions — model_default","text":"population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). transmission_rate numeric rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. infectiousness_rate numeric rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. recovery_rate numeric rate individuals move infectious recovered compartment. Often denoted \\(\\gamma\\), \\(\\gamma = 1.0 / \\text{infectious period}\\). See Details default values. intervention named list <intervention>s representing optional non-pharmaceutical pharmaceutical interventions applied epidemic. single intervention social contacts class <contacts_intervention> allowed named element \"contacts\". Multiple <rate_interventions> model parameters allowed; see Details model parameters interventions supported. vaccination <vaccination> object representing optional vaccination regime single dose, followed course epidemic, start end time, age-specific vaccination rates. time_dependence named list name model parameter, element function first two arguments current simulation time, x, value dependent time (x represents model parameter). See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). time_end maximum number timesteps run model. Taken days, default value 100 days. May numeric vector. increment size time increment. Taken days, default value 1 day.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model an SEIR-V epidemic with interventions — model_default","text":"<data.table>. model parameters composable elements scalars, single <data.table> columns \"time\", \"compartment\", \"age_group\", \"value\", giving number individuals per demographic group compartment timestep long (\"tidy\") format returned. model parameters composable elements lists list-like, nested <data.table> returned list column \"data\", holds compartmental values described . columns hold parameters composable elements relating model run. Columns \"scenario\" \"param_set\" identify combinations composable elements (population, interventions, vaccination regimes), infection parameters, respectively.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model an SEIR-V epidemic with interventions — model_default","text":"model allows single, population-wide rates transitions compartments per model run. However, model parameters may passed numeric vectors. vectors must follow Tidyverse recycling rules: vectors must length, , vectors length 1 recycled length vector. default values : Transmission rate (\\(\\beta\\), transmission_rate): 0.186, assuming \\(R_0\\) = 1.3 infectious period 7 days. Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.5, assuming pre-infectious period 2 days. Recovery rate (\\(\\gamma\\), recovery_rate): 0.143, assuming infectious period 7 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model an SEIR-V epidemic with interventions — model_default","text":"","code":"# create a population uk_population <- population(   name = \"UK population\",   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0, 0),     nrow = 1, ncol = 5L   ) )  # run epidemic simulation with no vaccination or intervention # and three discrete values of transmission rate data <- model_default(   population = uk_population,   transmission_rate = c(1.3, 1.4, 1.5) / 7.0, # uncertainty in R0 )  # view some data data #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571      100         1 #> 2:         0.2000000                 0.5     0.1428571      100         2 #> 3:         0.2142857                 0.5     0.1428571      100         3 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #>                   data #>                 <list> #> 1: <data.table[505x4]> #> 2: <data.table[505x4]> #> 3: <data.table[505x4]>  # run epidemic simulations with differences in the end time # may be useful when considering different start dates with a fixed end point data <- model_default(   population = uk_population,   time_end = c(50, 100, 150) )  data #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571       50         1 #> 2:         0.1857143                 0.5     0.1428571      100         2 #> 3:         0.1857143                 0.5     0.1428571      150         3 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #>                   data #>                 <list> #> 1: <data.table[255x4]> #> 2: <data.table[505x4]> #> 3: <data.table[755x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":null,"dir":"Reference","previous_headings":"","what":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"Simulate diphtheria outbreak using deterministic, compartmental ordinary differential equation model compartments \"susceptible\", \"exposed\", \"infectious\", \"hospitalised\", \"recovered\". model based Finger et al. (2019) intended used context internally displaced people (IDP) refugee camps. model allows proportion demographic group vaccinated start outbreak, thus contribute outbreak. model also allows changes number susceptibles age group model influxes evacuations camps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"","code":"model_diphtheria(   population,   transmission_rate = 4/4.5,   infectiousness_rate = 1/3,   recovery_rate = 1/3,   reporting_rate = 0.03,   prop_hosp = 0.01,   hosp_entry_rate = 0.2,   hosp_exit_rate = 0.2,   prop_vaccinated = 0 * population[[\"demography_vector\"]],   intervention = NULL,   time_dependence = NULL,   population_change = NULL,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). transmission_rate numeric rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. infectiousness_rate numeric rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. recovery_rate numeric rate individuals move infectious recovered compartment. Often denoted \\(\\gamma\\), \\(\\gamma = 1.0 / \\text{infectious period}\\). See Details default values. reporting_rate numeric proportion infectious cases reported; precursor hospitalisation reported cases hospitalised. prop_hosp numeric proportion reported cases hospitalised. hosp_entry_rate numeric rate reported cases infectious individuals hospitalised. calculated 1 / time hospitalisation, denoted \\(\\tau_1\\). hosp_exit_rate numeric rate individuals discharged hospital enter 'recovered' compartment. calculated 1 / time discharge, denoted \\(\\tau_2\\). prop_vaccinated numeric vector length number demographic groups indicated proportion group vaccinated. individuals included model dynamics. intervention named list <rate_intervention> objects representing optional pharmaceutical non-pharmaceutical interventions applied model parameters listed . time_dependence named list name model parameter, element function first two arguments current simulation time, x, value dependent time (x represents model parameter). See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). population_change two-element list, elements named \"time\" \"values\", giving times population changes, corresponding changes population demographic group times. \"time\" must numeric vector, \"values\" must list length \"time\", element numeric vector length number demographic groups population. time_end maximum number timesteps run model. Taken days, default value 100 days. May numeric vector. increment size time increment. Taken days, default value 1 day.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"data.table columns \"time\", \"compartment\", \"age_group\", \"value\", \"run\", giving number individuals per demographic group compartment timestep long (\"tidy\") format, \"run\" indicating unique parameter combination.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"details-model-an-infection-outbreak-in-a-humanitarian-camp-setting","dir":"Reference","previous_headings":"","what":"Details: Model an infection outbreak in a humanitarian camp setting","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"model developed diphtheria outbreaks settings interventions social contacts difficult implement. suitable application outbreak similar, directly transmitted infectious diseases well.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"model allows single, population-wide rates transitions compartments per model run. However, model parameters may passed numeric vectors. vectors must follow Tidyverse recycling rules: vectors must length, , vectors length 1 recycled length vector. default values taken Finger et al. (2019) possible: Transmission rate (\\(\\beta\\), transmission_rate): 0.8888889, assuming \\(R_0\\) 4.0 total infectious period 4.5 days. Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.333, assuming pre-infectious period 3 days. Reporting rate (\\(r\\), reporting_rate): 0.03, assuming 3% infectious cases detected reported. Proportion hospitalised (\\(\\eta\\), prop_hosp): 0.01, assuming 1% reported cases need hospital treatment. Hospital entry rate (\\(\\tau_1\\), hosp_entry_rate): 0.2, assuming takes 5 days infectious individuals seek hospital treatment. Hospital exit rate (\\(\\tau_2\\), hosp_exit_rate): 0.2, assuming individuals discharged hospital 5 days. Recovery rate (\\(\\gamma\\), recovery_rate): 0.333, assuming infectious period following symptoms, 3 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"modelling-population-changes","dir":"Reference","previous_headings":"","what":"Modelling population changes","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"model allows changes number susceptibles demographic group, represent influxes evacuations camp expected humanitarian relief situations. Users can specify times changes (demographic group) changes using population_changes argument, examine effect outbreak dynamics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"Finger, F., Funk, S., White, K., Siddiqui, M. R., Edmunds, W. J., & Kucharski, . J. (2019). Real-time analysis diphtheria outbreak forcibly displaced Myanmar nationals Bangladesh. BMC Medicine, 17, 58. doi:10.1186/s12916-019-1288-7 .","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"","code":"# create a dummy camp population with three age groups # diphtheria model is SEIHR # assume that most are susceptible, some infectious # values taken from supplementary material in Finger et al. for the # Kutupalong camp, rounded to the nearest 100 n_age_groups <- 3 demography_vector <- c(83000, 108200, 224600) initial_conditions <- matrix(0, nrow = n_age_groups, ncol = 5)  # set susceptibles and infectious initial_conditions[, 1] <- demography_vector - 1 initial_conditions[, 3] <- rep(1, n_age_groups)  camp_pop <- population(   contact_matrix = matrix(1, nrow = n_age_groups, ncol = n_age_groups),   demography_vector = demography_vector,   initial_conditions = initial_conditions / demography_vector )  # assume younger age groups are vaccinated prop_vaccinated <- c(0.2, 0.10, 0.1)  # run model for single, default parameter set data <- model_diphtheria(   camp_pop,   prop_vaccinated = prop_vaccinated ) head(data) #>     time demography_group compartment    value #>    <num>           <char>      <char>    <num> #> 1:     0     demo_group_1 susceptible  66399.2 #> 2:     0     demo_group_2 susceptible  97379.1 #> 3:     0     demo_group_3 susceptible 202139.1 #> 4:     0     demo_group_1     exposed      0.0 #> 5:     0     demo_group_2     exposed      0.0 #> 6:     0     demo_group_3     exposed      0.0 tail(data) #>     time demography_group  compartment        value #>    <num>           <char>       <char>        <num> #> 1:   100     demo_group_1 hospitalised 2.596196e-02 #> 2:   100     demo_group_2 hospitalised 3.807505e-02 #> 3:   100     demo_group_3 hospitalised 7.903602e-02 #> 4:   100     demo_group_1    recovered 6.052999e+04 #> 5:   100     demo_group_2    recovered 8.877102e+04 #> 6:   100     demo_group_3    recovered 1.842694e+05  # run model with increase in population # create population change data p <- list(   time = 70,   values = list(     c(1e4, 2e5, 1e5)   ) )  data <- model_diphtheria(   camp_pop,   prop_vaccinated = prop_vaccinated,   population_change = p ) head(data) #>     time demography_group compartment    value #>    <num>           <char>      <char>    <num> #> 1:     0     demo_group_1 susceptible  66399.2 #> 2:     0     demo_group_2 susceptible  97379.1 #> 3:     0     demo_group_3 susceptible 202139.1 #> 4:     0     demo_group_1     exposed      0.0 #> 5:     0     demo_group_2     exposed      0.0 #> 6:     0     demo_group_3     exposed      0.0 tail(data) #>     time demography_group  compartment        value #>    <num>           <char>       <char>        <num> #> 1:   100     demo_group_1 hospitalised 2.457804e-01 #> 2:   100     demo_group_2 hospitalised 2.881630e+00 #> 3:   100     demo_group_3 hospitalised 1.694441e+00 #> 4:   100     demo_group_1    recovered 6.598005e+04 #> 5:   100     demo_group_2    recovered 1.704198e+05 #> 6:   100     demo_group_3    recovered 2.285045e+05"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":null,"dir":"Reference","previous_headings":"","what":"Model an Ebola virus disease epidemic — model_ebola","title":"Model an Ebola virus disease epidemic — model_ebola","text":"Simulate epidemic using discrete-time, stochastic SEIR compartmental model compartments based Li et al. (2019), Erlang passage times based model developed Getz Dougherty (2017), developed model West African Ebola virus disease (EVD) outbreak 2013 -- 2016. See Details information. model_ebola_cpp() Rcpp implementation model currently lags behind R implementation, likely removed.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model an Ebola virus disease epidemic — model_ebola","text":"","code":"model_ebola(   population,   erlang_subcompartments = 2,   transmission_rate = 1.5/12,   infectiousness_rate = erlang_subcompartments/5,   removal_rate = erlang_subcompartments/12,   prop_community = 0.9,   etu_risk = 0.7,   funeral_risk = 0.5,   intervention = NULL,   time_dependence = NULL,   time_end = 100 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model an Ebola virus disease epidemic — model_ebola","text":"population object <population> class, see population(). model accepts <population> without demographic structure, , demography_vector must single number representing total size affected population. model also account demographic differences social contacts, means contact_matrix ignored. consistency, matrix must square many rows demography groups, one. erlang_subcompartments number Erlang subcompartments assumed exposed, infectious, hospitalised compartments. Defaults 2. transmission_rate single number rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. infectiousness_rate single number rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. removal_rate rate infectious individuals transition infectious hospitalised compartments funeral removed compartments. model distinguish recoveries deaths. Denoted Getz Dougherty \\(\\gamma^\\) (see Details). prop_community proportion infectious individuals remain community hospitalised treatment. Defaults 0.5 etu_risk relative risk onward transmission EVD hospitalised individuals. Must single value 0.0 1.0, 0.0 indicates hospitalisation completely prevents onward transmission, 1.0 indicates hospitalisation prevent onward transmission . etu_risk used scale value transmission_rate transmission_rate \\(\\beta\\). Defaults 0.2. funeral_risk relative risk onward transmission EVD funerals individuals died EVD. Must single value 0.0 1.0, 0.0 indicates onward transmission, 1.0 indicates funeral transmission equivalent transmission community. funeral_risk used scale value transmission_rate transmission_rate \\(\\beta\\). Defaults 0.5. intervention named list <rate_intervention> objects representing optional pharmaceutical non-pharmaceutical interventions applied model parameters listed . time_dependence named list name model parameter, element function first two arguments current simulation time, x, value dependent time (x represents model parameter). See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). time_end maximum number timesteps run model, days. Defaults 100 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model an Ebola virus disease epidemic — model_ebola","text":"<data.table> long format columns \"time\", \"compartment\", \"age_group\", \"value\", gives number individuals model compartment time ( 1 time_end).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"details-discrete-time-ebola-virus-disease-model","dir":"Reference","previous_headings":"","what":"Details: Discrete-time Ebola virus disease model","title":"Model an Ebola virus disease epidemic — model_ebola","text":"model compartments adopted consensus model Ebola virus disease presented Li et al. (2019), transitions epidemiological compartments modelled using Erlang sub-compartments adapted Getz Dougherty (2018); see References. R code model adapted code Ha Minh Lam initially made available Epirecipes (https://github.com/epirecipes/epicookbook) MIT license. shape Erlang distributions passage times exposed infectious compartments (\\(k^E\\) \\(k^\\)) recommended set 2 sensible choice, default value erlang_sbubcompartments argument, can allowed vary (independently). transition rates exposed infectious, infectious funeral compartments (also hospitalised removed), \\(\\gamma^E\\) \\(\\gamma^\\) Getz Dougherty's notation, passed user infectiousness_rate removal_rate respectively. Getz Dougherty's equation (6) gives relationship parameters mean pre-infectious \\(\\rho^E\\) infectious \\(\\rho^\\) periods. $$\\gamma^E = \\dfrac{k^E}{\\rho^E} = \\dfrac{2}{\\rho^E} ~\\text{}~ \\gamma^= \\dfrac{k^}{\\rho^} = \\dfrac{2}{\\rho^}$$ discrete time model, \\(\\gamma^E\\) \\(\\gamma^\\) used determine passage times newly exposed infectious individuals respective compartments (thus allowing variation passage times).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"hospitalisation-funerals-and-removal","dir":"Reference","previous_headings":"","what":"Hospitalisation, funerals, and removal","title":"Model an Ebola virus disease epidemic — model_ebola","text":"proportion, 1.0 - prop_community, infectious individuals transferred hospitalised compartment timestep, compartment represents Ebola Treatment Units (ETUs), individuals hospitalised compartment considered infectious longer community. passage time individuals hospitalised compartment similar individuals infectious compartment (.e., infectious community), means infectious individual \\(N\\) timesteps exiting infectious compartment exit hospitalised compartment time. Hospitalised individuals can contribute transmission Ebola susceptibles depending value etu_risk scales baseline transmission rate \\(\\beta\\) hospitalised individuals. assume deaths hospital lead Ebola-safe funerals, individuals exiting hospitalised compartment move 'removed' compartment, holds recoveries deaths. assume deaths outside hospital lead funerals potentially unsafe burials, funeral_risk argument scales baseline transmission rate \\(\\beta\\) funeral transmission Ebola susceptibles. Individuals assumed spend single timestep funeral transmission compartment, move 'removed' compartment. Individuals 'removed' compartment affect model dynamics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model an Ebola virus disease epidemic — model_ebola","text":"default values : Transmission rate (\\(\\beta\\), transmission_rate): 0.125, resulting \\(R_0\\) = 1.5 infectious period 12 days. Infectiousness rate (\\(\\gamma^E\\), infectiousness_rate): 0.4, assuming pre-infectious period 5 days two Erlang subcompartments. Removal rate (\\(\\gamma^\\), recovery_rate): 0.1667, assuming infectious period 12 days two Erlang subcompartments.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"implementing-vaccination","dir":"Reference","previous_headings":"","what":"Implementing vaccination","title":"Model an Ebola virus disease epidemic — model_ebola","text":"Vaccination currently implemented model \"vaccinated\" epidemiological compartment. prevents use <vaccination> object. Instead, users can use time_dependence argument pass function modifies model parameters --- specifically, transmission rate --- way consistent effect vaccination. example shown vignette model; run code open vignette: vignette(\"ebola_model\", package = \"epidemics\")","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Model an Ebola virus disease epidemic — model_ebola","text":"Li, S.-L., Ferrari, M. J., Bjørnstad, O. N., Runge, M. C., Fonnesbeck, C. J., Tildesley, M. J., Pannell, D., & Shea, K. (2019). Concurrent assessment epidemiological operational uncertainties optimal outbreak control: Ebola case study. Proceedings Royal Society B: Biological Sciences, 286(1905), 20190774. doi:10.1098/rspb.2019.0774 Getz, W. M., & Dougherty, E. R. (2018). Discrete stochastic analogs Erlang epidemic models. Journal Biological Dynamics, 12(1), 16–38. doi:10.1080/17513758.2017.1401677","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model an Ebola virus disease epidemic — model_ebola","text":"","code":"# create a population with 6 compartments population <- population(   contact_matrix = matrix(1),   demography_vector = 14e6,   initial_conditions = matrix(     c(0.999998, 0.000001, 0.000001, 0, 0, 0),     nrow = 1, ncol = 6L   ) )  # run epidemic simulation with no vaccination or intervention data <- model_ebola(   population = population )  # view some data head(data) #>   time demography_group  compartment    value #> 1    1     demo_group_1  susceptible 13999972 #> 2    1     demo_group_1      exposed       14 #> 3    1     demo_group_1   infectious       14 #> 4    1     demo_group_1 hospitalised        0 #> 5    1     demo_group_1      funeral        0 #> 6    1     demo_group_1      removed        0"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":null,"dir":"Reference","previous_headings":"","what":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"Simulate epidemic using Vacamole model Covid-19 developed RIVM, National Institute Public Health Environment Netherlands. model aimed estimating impact 'leaky' vaccination epidemic. See Details References information.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"","code":"model_vacamole(   population,   transmission_rate = 1.3/7,   transmission_rate_vax = 0.8 * transmission_rate,   infectiousness_rate = 1/2,   hospitalisation_rate = 1/1000,   hospitalisation_rate_vax = 0.8 * hospitalisation_rate,   mortality_rate = 1/1000,   mortality_rate_vax = 0.8 * mortality_rate,   recovery_rate = 1/7,   intervention = NULL,   vaccination = NULL,   time_dependence = NULL,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). transmission_rate numeric rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. transmission_rate_vax numeric values 0.0 1.0 giving transmission_rate infection individuals received two doses vaccine. default values 80% transmission_rate infection individuals doubly vaccinated. infectiousness_rate numeric rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. hospitalisation_rate numeric hospitalisation rate infectious individuals. hospitalisation_rate_vax numeric values 0.0 1.0 giving hospitalisation rate infectious individuals received two doses vaccine. default value 80% hospitalisation rate individuals doubly vaccinated. mortality_rate numeric mortality rate infectious hospitalised individuals. mortality_rate_vax numeric values 0.0 1.0 giving mortality infectious hospitalised individuals received two doses vaccine. default value 80% mortality rate individuals doubly vaccinated. recovery_rate numeric rate individuals move infectious recovered compartment. Often denoted \\(\\gamma\\), \\(\\gamma = 1.0 / \\text{infectious period}\\). See Details default values. intervention named list <intervention>s representing optional non-pharmaceutical pharmaceutical interventions applied epidemic. single intervention social contacts class <contacts_intervention> allowed named element \"contacts\". Multiple <rate_interventions> model parameters allowed; see Details model parameters interventions supported. vaccination optional <vaccination> object representing vaccination regime two doses followed course epidemic, start end time, age-specific vaccination rates dose. See vaccination(). time_dependence named list name model parameter, element function first two arguments current simulation time, x, value dependent time (x represents model parameter). See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). time_end maximum number timesteps run model. Taken days, default value 100 days. May numeric vector. increment size time increment. Taken days, default value 1 day.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"<data.table>. model parameters composable elements scalars, single <data.table> columns \"time\", \"compartment\", \"age_group\", \"value\", giving number individuals per demographic group compartment timestep long (\"tidy\") format returned. model parameters composable elements lists list-like, nested <data.table> returned list column \"data\", holds compartmental values described . columns hold parameters composable elements relating model run. Columns \"scenario\" \"param_set\" identify combinations composable elements (population, interventions, vaccination regimes), infection parameters, respectively.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"details-vacamole-covid-model-with-leaky-two-dose-vaccination","dir":"Reference","previous_headings":"","what":"Details: Vacamole Covid-19 model with leaky, two-dose vaccination","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"Vacamole model compartments \"susceptible\", \"vaccinated_one_dose\", \"vaccinated_two_dose\", \"exposed\", \"infectious\" \"infectious_vaccinated\", \"hospitalised\", \"hospitalised_vaccinated\", \"recovered\",  \"dead\". model allows : 'hospitalised' compartment along hospitalisation rate; Two doses vaccination, 'leaky' protection, .e., vaccination prevent infection completely allows reduction infection rate, well reduced rates moving states considered serious, 'hospitalised' 'dead'.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"model allows single, population-wide rates transitions compartments per model run. However, model parameters may passed numeric vectors. vectors must follow Tidyverse recycling rules: vectors must length, , vectors length 1 recycled length vector. Transmission rate (\\(\\beta\\), transmission_rate): 0.186, resulting \\(R_0\\) = 1.3 infectious period 7 days. transmission rate doubly vaccinated individuals (\\(\\beta_v\\)) 80% \\(\\beta\\), 0.1488. Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.5, assuming pre-infectious period 2 days. Hospitalisation rate (\\(\\eta\\), hospitalistion_rate): 1.0 / 1000, assuming one every thousand infectious individuals hospitalised. hospitalisation rate doubly vaccinated individuals (\\(\\eta_v\\)) 80% \\(\\eta\\), 0.8 / 1000. Mortality rate (\\(\\omega\\), mortality_rate): 1.0 / 1000, assuming one every thousand infectious hospitalised individuals dies. mortality rate doubly vaccinated (\\(\\omega_v\\)) 80% \\(\\omega\\), 0.8 / 1000. Recovery rate (\\(\\gamma\\), recovery_rate): 0.143, assuming infectious period 7 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"Ainslie, K. E. C., Backer, J. ., Boer, P. T. de, Hoek, . J. van, Klinkenberg, D., Altes, H. K., Leung, K. Y., Melker, H. de, Miura, F., & Wallinga, J. (2022). scenario modelling analysis anticipate impact COVID-19 vaccination adolescents children disease outcomes Netherlands, summer 2021. Eurosurveillance, 27(44), 2101090. doi:10.2807/1560-7917.ES.2022.27.44.2101090","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"","code":"# create a population, note eleven columns for compartments population <- population(   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0, 0, 0, 0, 0.0001, 0, 0, 0, 0, 0),     nrow = 1, ncol = 11L   ) )  # create a vaccination regime double_vax <- vaccination(   nu = matrix(1e-3, ncol = 2, nrow = 1),   time_begin = matrix(c(10, 30), nrow = 1),   time_end = matrix(c(50, 80), nrow = 1) )  # run epidemic simulation with vaccination but no intervention # with a single set of parameters data <- model_vacamole(   population = population,   vaccination = double_vax )  # view some data head(data) #>     time demography_group         compartment    value #>    <num>           <char>              <char>    <num> #> 1:     0     demo_group_1         susceptible 66993300 #> 2:     0     demo_group_1 vaccinated_one_dose        0 #> 3:     0     demo_group_1 vaccinated_two_dose        0 #> 4:     0     demo_group_1             exposed        0 #> 5:     0     demo_group_1  exposed_vaccinated        0 #> 6:     0     demo_group_1          infectious     6700  # run epidemic simulation with no vaccination or intervention # and three discrete values of transmission_rate data <- model_vacamole(   population = population,   transmission_rate = c(1.3, 1.4, 1.5) / 7.0, # uncertainty in R0 )  # view some data head(data) #>    transmission_rate infectiousness_rate hospitalisation_rate mortality_rate #>                <num>               <num>                <num>          <num> #> 1:         0.1857143                 0.5                0.001          0.001 #> 2:         0.2000000                 0.5                0.001          0.001 #> 3:         0.2142857                 0.5                0.001          0.001 #>    recovery_rate transmission_rate_vax hospitalisation_rate_vax #>            <num>                 <num>                    <num> #> 1:     0.1428571             0.1485714                    8e-04 #> 2:     0.1428571             0.1600000                    8e-04 #> 3:     0.1428571             0.1714286                    8e-04 #>    mortality_rate_vax time_end param_set      population intervention #>                 <num>    <num>     <int>          <list>       <list> #> 1:              8e-04      100         1 <population[4]>              #> 2:              8e-04      100         2 <population[4]>              #> 3:              8e-04      100         3 <population[4]>              #>    vaccination time_dependence increment scenario                 data #>         <list>          <list>     <num>    <int>               <list> #> 1:                   <list[1]>         1        1 <data.table[1111x4]> #> 2:                   <list[1]>         1        1 <data.table[1111x4]> #> 3:                   <list[1]>         1        1 <data.table[1111x4]> tail(data) #>    transmission_rate infectiousness_rate hospitalisation_rate mortality_rate #>                <num>               <num>                <num>          <num> #> 1:         0.1857143                 0.5                0.001          0.001 #> 2:         0.2000000                 0.5                0.001          0.001 #> 3:         0.2142857                 0.5                0.001          0.001 #>    recovery_rate transmission_rate_vax hospitalisation_rate_vax #>            <num>                 <num>                    <num> #> 1:     0.1428571             0.1485714                    8e-04 #> 2:     0.1428571             0.1600000                    8e-04 #> 3:     0.1428571             0.1714286                    8e-04 #>    mortality_rate_vax time_end param_set      population intervention #>                 <num>    <num>     <int>          <list>       <list> #> 1:              8e-04      100         1 <population[4]>              #> 2:              8e-04      100         2 <population[4]>              #> 3:              8e-04      100         3 <population[4]>              #>    vaccination time_dependence increment scenario                 data #>         <list>          <list>     <num>    <int>               <list> #> 1:                   <list[1]>         1        1 <data.table[1111x4]> #> 2:                   <list[1]>         1        1 <data.table[1111x4]> #> 3:                   <list[1]>         1        1 <data.table[1111x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":null,"dir":"Reference","previous_headings":"","what":"Get new infections over model time — new_infections","title":"Get new infections over model time — new_infections","text":"Get new infections model time","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get new infections over model time — new_infections","text":"","code":"new_infections(data, compartments_from_susceptible = NULL, by_group = TRUE)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get new infections over model time — new_infections","text":"data table model output, typically output model_default() similar functions. compartments_from_susceptible optional argument, character vector names model compartments individuals transition \"susceptible\" compartment, related infection. common example compartment \"vaccinated\" individuals longer susceptible, also counted infected. by_group logical representing whether epidemic size returned demographic group, whether single population-wide value returned.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get new infections over model time — new_infections","text":"table columns data, additional variable compartment, \"new_infections\", resulting additional rows.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get new infections over model time — new_infections","text":"","code":"# create a population uk_population <- population(   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0, 0),     nrow = 1, ncol = 5L   ) )   # run epidemic simulation with no vaccination or intervention data <- model_default(   population = uk_population,   time_end = 200,   increment = 1 )  new_infections(data) #> Key: <time, demography_group> #>       time demography_group new_infections #>      <num>           <char>          <num> #>   1:     0     demo_group_1         0.0000 #>   2:     1     demo_group_1       255.6554 #>   3:     2     demo_group_1       597.4504 #>   4:     3     demo_group_1       786.9596 #>   5:     4     demo_group_1       899.2263 #>  ---                                       #> 197:   196     demo_group_1    194151.2197 #> 198:   197     demo_group_1    196154.0970 #> 199:   198     demo_group_1    198089.5442 #> 200:   199     demo_group_1    199954.3897 #> 201:   200     demo_group_1    201745.5414"},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct a new population for an epidemic model — population","title":"Construct a new population for an epidemic model — population","text":"Construct new population epidemic model Check whether object <population>","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct a new population for an epidemic model — population","text":"","code":"population(   name = NA_character_,   contact_matrix,   demography_vector,   initial_conditions )  is_population(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct a new population for an epidemic model — population","text":"name Optional string population name. contact_matrix matrix giving contacts demographic groups population. Must square matrix. demography_vector vector sizes demographic group. Must length dimensions contact matrix. initial_conditions Matrix representing initial proportions demographic group four model compartments: 'susceptible', 'infected/infectious', 'recovered', 'vaccinated'. Must many rows number demographic groups. compartment represented columns matrix, element \\(M_{ij}\\) represents proportion individuals demographic group \\(\\) compartment \\(j\\) . x object checked valid population.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct a new population for an epidemic model — population","text":"object <population> S3 class. is_population() returns logical whether object <population>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct a new population for an epidemic model — population","text":"","code":"uk_pop <- population(   name = \"UK population\",   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0),     nrow = 1, ncol = 4   ) )  # print to check uk_pop #> <population> object #>  #>  Population name:  #> \"UK population\" #>  #>  Demography  #> Dem. grp. 1: 67,000,000 (100%) #>  #>  Contact matrix  #>              Dem. grp. 1: #> Dem. grp. 1:            1  # check for class <population> is_population(uk_pop) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare arguments to default model function — prepare_default_args","title":"Prepare arguments to default model function — prepare_default_args","text":"Prepare arguments model_default() .model_default_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare arguments to default model function — prepare_default_args","text":"","code":".check_prepare_args_default(mod_args)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare arguments to default model function — prepare_default_args","text":"mod_args named list population, epidemic modifiers.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare arguments to default model function — prepare_default_args","text":"list model arguments suitable .model_default_cpp(). named list consisting : initial_state: initial conditions modified represent absolute rather proportional values; transmission_rate, infectiousness_rate, recovery_rate: three numbers representing transmission rate infection, rate transition exposed infectious, recovery rate, respectively; contact_matrix, numeric matrix population contact matrix scaled largest real eigenvalue size groups; npi_time_begin, npi_time_end: two vectors start end times interventions applied; npi_cr: matrix age- intervention-specific effect social contacts; vax_time_begin,vax_time_end, vax_nu: three numeric matrices age- dose-specific start times, end times, rates vaccination doses implemented; time_end, increment: two numbers time end simulation, value simulation time incremented.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Prepare arguments to default model function — prepare_default_args","text":".check_prepare_args_default() prepares arguments .model_default_cpp(), C++ function solves default ODE system using Boost odeint solver, converting arguments collected mod_args simpler structures lists numeric integer vectors can interpreted C++ types Rcpp::List, Rcpp::NumericVector, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"Prepare arguments model_diphtheria() .model_diphtheria_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"","code":".check_prepare_args_diphtheria(mod_args)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"mod_args named list population, epidemic modifiers.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"list model arguments suitable .model_diphtheria_cpp(). named list consisting : initial_state: initial conditions modified represent absolute rather proportional values; transmission_rate, transmission_rate_vax: two numbers representing transmission rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; infectiousness_rate: single number transition rate 'exposed' 'exposed_vaccinated' 'infectious' 'infectious_vaccinated' compartments; recovery_rate: single number recovery rate infection; reporting_rate: single number proportion infectious cases reported; prop_hosp: single number proportion reported cases need hospitalisation; hosp_entry_rate, hosp_exit_rate: two numbers representing rate entry exit 'hospitalised' compartment; rate_interventions: Rcpp List giving interventions model parameters; time_dependence: Rcpp List giving time-dependent effects model parameters form R functions; pop_change_times pop_change_values: times values changes population susceptibles; time_end, increment: two numbers time end simulation, value simulation time incremented.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":".check_prepare_args_diphtheria() prepares arguments .model_diphtheria_cpp(), C++ function solves ODE system using Boost odeint solver, converting arguments collected mod_args simpler structures lists numeric integer vectors can interpreted C++ types Rcpp::List, Rcpp::NumericVector, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":"Prepare arguments model_vacamole() .model_vacamole_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":"","code":".check_prepare_args_vacamole(mod_args)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":"list model arguments suitable .model_vacamole_cpp(). named list consisting : initial_state: initial conditions modified represent absolute rather proportional values; transmission_rate, transmission_rate_vax: two numbers representing transmission rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; infectiousness_rate: single number transition rate 'exposed' 'exposed_vaccinated' 'infectious' 'infectious_vaccinated' compartments; mortality_rate, mortality_rate_vax: two numbers representing mortality rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; hospitalisation_rate, hospitalisation_rate_vax: two numbers representing hospitalisation rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; recovery_rate: single number recovery rate infection; contact_matrix, numeric matrix population contact matrix scaled largest real eigenvalue size groups; npi_time_begin, npi_time_end: two vectors start end times interventions applied; npi_cr: matrix age- intervention-specific effect social contacts; vax_time_begin,vax_time_end, vax_nu: three numeric matrices age- dose-specific start times, end times, rates vaccination doses implemented; time_end, increment: two numbers time end simulation, value simulation time incremented.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":".check_prepare_args_vacamole() prepares arguments .model_vacamole_cpp(), C++ function solves Vacamole ODE system using Boost odeint solver, converting arguments collected mod_args simpler structures lists numeric integer vectors can interpreted C++ types Rcpp::List, Rcpp::NumericVector, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":null,"dir":"Reference","previous_headings":"","what":"Print a <population> object — print.population","title":"Print a <population> object — print.population","text":"Print <population> object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print a <population> object — print.population","text":"","code":"# S3 method for population print(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print a <population> object — print.population","text":"x <population> object. ... parameters passed print().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print a <population> object — print.population","text":"Invisibly returns <population> object x. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Print a <vaccination> object — print.vaccination","title":"Print a <vaccination> object — print.vaccination","text":"Print <vaccination> object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print a <vaccination> object — print.vaccination","text":"","code":"# S3 method for vaccination print(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print a <vaccination> object — print.vaccination","text":"x <vaccination> object. ... parameters passed print().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print a <vaccination> object — print.vaccination","text":"Invisibly returns <vaccination> object x. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Print an object of the <intervention> super-class — print_intervention","title":"Print an object of the <intervention> super-class — print_intervention","text":"Print object <intervention> super-class Print objects <contact_intervention> class Print objects <rate_intervention> class","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print an object of the <intervention> super-class — print_intervention","text":"","code":"# S3 method for intervention print(x, ...)  # S3 method for contact_intervention print(x, ...)  # S3 method for rate_intervention print(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print an object of the <intervention> super-class — print_intervention","text":"x object inherits <intervention> class. print.contacts_intervention(), object <contacts_intervention> class. print.rate_intervention(), object <rate_intervention> class. ... parameters passed print().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print an object of the <intervention> super-class — print_intervention","text":"Invisibly returns object x. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct a new vaccination regime for an epidemic model — vaccination","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"Prepare <vaccination> object specifies vaccination regime use epidemic model. objects can handle different vaccination start end times, well different vaccination rates, demographic group epidemic modelling scenario. Combine <vaccination> objects create multi-dose vaccination regimes using c() two <vaccination> objects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"","code":"vaccination(name = NA_character_, nu, time_begin, time_end)  is_vaccination(x)  # S3 method for vaccination c(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"name String name vaccination regime. nu Matrix group-specific rate vaccination, expressed rate parameter \\(nu\\). element matrix \\(nu_{ij}\\) represents rate delivering vaccine dose \\(j\\) demographic group \\(\\). time_begin Matrix start time delivering vaccination dose \\(j\\) demographic group \\(\\). demographic group \\(\\). time_end Matrix end time delivering vaccination dose \\(j\\) demographic group \\(\\). x <vaccination> object, object checked <vaccination>. ... Vaccination objects combine x create multi-dose <vaccination> object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"object <vaccination> S3 class. vaccination() returns <vaccination> object specified parameters. Concatenating two <vaccination> objects using c() also returns <vaccination> object. object holds group-specific start end times, group-specific vaccination rates specified constituent vaccination regimes. .no_vaccination() returns <vaccination> effect population, start end times set 0.0, rate vaccination \\(nu\\) also set 0.0. is_vaccination() return logical whether object <vaccination> class.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"Multi-dose vaccinations can passed epidemic models, models accommodate multi-dose vaccinations. example, default SEIR-V model provided model_default() single vaccinated compartment, use first parameter set multi-dose regime determine individuals transition vaccinated compartment. contrast, Vacamole model considers two doses, make use first two parameter sets multi-dose regime. doses can specified, disregarded model.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"","code":"# Assuming a population with two age groups, children 0 -- 5, and others 5+ # an example for childhood vaccination only childhood_vaccination <- vaccination(   name = \"childhood_vaccination\",   time_begin = matrix(c(0, 100)), # assuming a simulation over 100 days   time_end = matrix(c(100, 100)),   nu = matrix(c(0.0001, 0.0)) # over 5s never vaccinated ) #> Vaccination: some `time_end`s are not greater than `time_begin`s #> Vaccination: some `time_end`s are not greater than `time_begin`s childhood_vaccination #> Vaccination: some `time_end`s are not greater than `time_begin`s #> <vaccination> object #>  #>  Vaccination name:  #> \"childhood_vaccination\" #>  #>  Begins at:  #>      dose_1 #> [1,]      0 #> [2,]    100 #>  #>  Ends at:  #>      dose_1 #> [1,]    100 #> [2,]    100 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  1e-04 #> [2,]  0e+00  # check whether the object is a <vaccination> is_vaccination(childhood_vaccination) #> [1] TRUE  # Concatenating vaccinations # create first dose regime vax_1 <- vaccination(   name = \"vax_regime\",   time_begin = matrix(1),   time_end = matrix(100),   nu = matrix(0.001) )  # second dose regime vax_2 <- vaccination(   name = \"vax_regime\",   time_begin = matrix(101),   time_end = matrix(200),   nu = matrix(0.001) )  c(vax_1, vax_2) #> <vaccination> object #>  #>  Vaccination name:  #> \"vax_regime\" #>  #>  Begins at:  #>      dose_1 dose_2 #> [1,]      1    101 #>  #>  Ends at:  #>      dose_1 dose_2 #> [1,]    100    200 #>  #>  Vaccination rate:  #>      dose_1 dose_2 #> [1,]  0.001  0.001"},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Validate objects that inherit from the  class — validate_intervention","title":"Validate objects that inherit from the  class — validate_intervention","text":"Validate objects inherit  class Validate objects inherit  class","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validate objects that inherit from the  class — validate_intervention","text":"","code":"validate_contacts_intervention(x)  validate_rate_intervention(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validate objects that inherit from the  class — validate_intervention","text":"x validate_contacts_intervention(), object validated <contacts_intervention>. validate_rate_intervention(), object validated <rate_intervention>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validate objects that inherit from the  class — validate_intervention","text":"Invisibly returns input x. Called primarily input checking validator objects <intervention> superclass.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":null,"dir":"Reference","previous_headings":"","what":"Vector recyclability checks and vector recycling — vector_recycling","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"Internal functions check whether vectors can recycled recycle vectors.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"","code":".test_recyclable(x)  .recycle_vectors(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"x list vectors checked compliance Tidyverse recycling rules, recycled. x list recycled, two cases envisaged: elements x expected length, , one element x scalars.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vector recyclability checks and vector recycling — vector_recycling","text":".test_recyclable returns single logical value. .recycle_vectors returns list vectors recycled length following Tidyverse recycling rules.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"Note .test_recyclable() return vectors unequal lengths x comply length rules. compliance enforced function expected used internally, call .test_recyclable() (e.g. stopifnot()).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"Tim Taylor","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"epidemics-020","dir":"Changelog","previous_headings":"","what":"epidemics 0.2.0","title":"epidemics 0.2.0","text":"second GitHub release epidemics makes substantial additions functionality v0.1.0, introduces significant breaking changes (#176). release end point project ship vectorised ODE models. release focuses ODE models epidemics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"breaking-changes-0-2-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"epidemics 0.2.0","text":"model functions renamed model_<NAME>(), removing language suffix (#176). wrappers around R-implementations ‘default’ ‘Vacamole’ models removed, ODE system functions retained potential future use (#176). “Vacamole” model refactored arguments *_reduction_vax effect double vaccination compartmental transition rates renamed *_vax, * may one “susceptibility”, “hospitalisation”, “mortality”. Previously, parameters implemented internal C++ code, presented inverse values users (.e., susceptibility_vax = susceptibility * (1 - (susceptibility_reduction_vax)))). change brings user-facing representation line internal implementation, allows parameters targeted rate interventions time-dependence, possible earlier (#176, #203, overriding #144). function get_parameter() removed (#176). infection parameter “transmissibility” renamed “transmission rate” corresponding function argument transmission_rate (#196).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"model-functions-0-2-0","dir":"Changelog","previous_headings":"","what":"Model functions","title":"epidemics 0.2.0","text":"ODE model functions can now passed numeric vectors infection parameters, lists intervention sets (list <intervention>s), lists <vaccination> intervention vaccination argument respectively. main change minor version. (#176) ODE model functions take {data.table} make combinations interventions vaccinations (together called ‘scenario’), infection parameter sets run scenario parameter set (#176). ODE model functions return <data.table>s - may nested model arguments identity columns vectors parameters multiple scenarios passed. simple, unnested <data.table> passed model function called scalar arguments (#176).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"model-structures-0-2-0","dir":"Changelog","previous_headings":"","what":"Model structures","title":"epidemics 0.2.0","text":"fix vaccination implemented default Vacamole models: group-specific vaccination rates passed <vaccination> internally converted count multiplication group-specific population size, value subtracted susceptibles, vaccination active. previous implementation made number vaccinations dependent number susceptibles, line public health understanding vaccination (details: #198, fix: #202). C++ ODE model implementation now access values std::unordered_map model parameters using operator keys (model_params.(\"parameter_name\")) rather using [ (model_params[\"parameter_name\"]); latter method introduce key-value pair parameter_name : 0 numeric value types key missing map. led issues Vacamole model *_vax parameters correctly transferred C++ substituted 0s without throwing error (#203).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"classes-0-2-0","dir":"Changelog","previous_headings":"","what":"Classes","title":"epidemics 0.2.0","text":"substantial changes classes; small additions input checking <population> class.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"helper-functions-0-2-0","dir":"Changelog","previous_headings":"","what":"Helper functions","title":"epidemics 0.2.0","text":"Internal helper functions .check_args_model_*() .prepare_args_model_*() combined single functions .check_prepare_args_*() called output input checking side effects. new internal functions .prepare_population(), .cross_check_intervention(), .cross_check_vaccination(), .cross_check_timedep(), .cross_check_popchange() check prepare model population check inputs compatibility . used .check_prepare_args_*(). New internal functions added check recycle lists vectors; original implementations @TimTaylor. output_to_df() renamed .output_to_df().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"documentation-0-2-0","dir":"Changelog","previous_headings":"","what":"Documentation","title":"epidemics 0.2.0","text":"benchmarking vignette removed R-model implementations longer provided users (#176). vignette parameter uncertainty rewritten show pass vectors infection parameters model composable elements model functions, renamed “Modelling parameter uncertainty epidemic scenarios” (#176). design decisions vignette added help developers contributors understand package architecture design choices made epidemics development; includes conceptual design diagram well architecture diagram (#188). function documentation updated reflect name changes minor improvements (#176). README reorganised shift model list end, make installation instructions easier find (#176). Corrected website URL _pkgdown.yml; allows search functionality package website (#195). Updated WORDLIST.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"package-0-2-0","dir":"Changelog","previous_headings":"","what":"Package","title":"epidemics 0.2.0","text":"ODE model functions received extensive standardised (much possible) test suite. Filenames standardised show files related, e.g. R/model_default.R, src/model_default.cpp, inst/include/model_default.h; references filenames package header updated. Removed {deSolve} dependencies. Added {ggdist}, {withr}, {purr} {tidyr} Suggests; CITATION.cff updated match. Added basic infrastructure continuous relative benchmarking (#206).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"epidemics-010","dir":"Changelog","previous_headings":"","what":"epidemics 0.1.0","title":"epidemics 0.1.0","text":"initial GitHub release epidemics, R package ships library compartmental epidemic model structures can used, along supplied classes help define population characteristics epidemic response interventions including vaccinations, compose model epidemic scenarios. epidemics still actively developed, major changes planned near future. release aimed supporting reproducibility projects used epidemics subject breaking changes due planned package development. sections describe contents release.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"model-structures-0-1-0","dir":"Changelog","previous_headings":"","what":"Model structures","title":"epidemics 0.1.0","text":"release epidemics includes four model structures supporting range composable elements modify epidemic trajectories. “Default” model: deterministic SEIR-V model allowing heterogeneity social contacts demographic groups, optional, single-dose non-leaky vaccination; “Vacamole” model: deterministic SEI-HRD-V2 implementation model allowing heterogeneity social contacts demographic groups, two-dose leaky vaccination, supporting different infection trajectories infectious hospitalised (H) compartments doubly vaccinated individuals, tracks deaths (D), initially developed Dutch public health agency RIVM vaccine impact modelling Covid-19 pandemic, published Ainslie et al. 2022 https://doi.org/10.2807/1560-7917.ES.2022.27.44.2101090; “Diphtheria” model: deterministic SEIHR model tracking outcomes different demographic groups, including heterogeneity social contacts, adapted Finger et al. 2019 https://doi.org/10.1186/s12916-019-1288-7 intended application disease outbreaks humanitarian camp setting; “Ebola” model: discrete time stochastic SEIHFR model suitable modelling Ebola virus disease haemorrhagic fevers, allows varying efficacy isolation hospital setting (H), allows modelling transmission funeral context (F), adapted consensus Ebola virus disease model Li et al. 2019 https://doi.org/10.1098/rspb.2019.0774 using simulation methods Getz Dougherty 2018 https://doi.org/10.1080/17513758.2017.1401677.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"solving-ode-systems-using-boost-odeint-0-1-0","dir":"Changelog","previous_headings":"","what":"Solving ODE systems using Boost odeint","title":"epidemics 0.1.0","text":"epidemics uses Boost’s odeint https://www.boost.org/doc/libs/1_84_0/libs/numeric/odeint/doc/html/boost_numeric_odeint/getting_started/overview.html treat deterministic models’ ordinary differential equations (ODEs) initial value problems solve . Model ODEs defined structs operators package headers, exposed R internal Rcpp functions. ‘default’, ‘Vacamole’, ‘diphtheria’ models ODE models defined way. intended help reduce overheads associated passing ODE systems written R back forth solver (provided {deSolve}), easier way define feature-rich models writing C code solvers provided {deSolve} accept compiled code. epidemics headers include tools handling C++ representations R objects used package (see ), can imported Rcpp packages. ‘default’ ‘Vacamole’ models equivalent R-implementations well use {deSolve} package; intended made unavailable future releases.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"composable-elements-as-classes-0-1-0","dir":"Changelog","previous_headings":"","what":"Composable elements as classes","title":"epidemics 0.1.0","text":"epidemics provides classes help organise components epidemic scenario model. <population>: S3 class store population characteristics including size demographic groups, social contacts matrix, initial conditions model; <intervention>: S3 abstract class super-class allows definition events modify epidemic trajectory: <rate_intervention>: sub-class <intervention> allows reduction transition rates model compartments simulate effect policy interventions specific period; <contacts_intervention>: sub-class <intervention> allows reduction social contacts simulate effect policy interventions specific period; <vaccination>: S3 class holds intervals group-specific rates individuals transition ‘vaccinated’ compartment(s) model, available;","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"other-composable-elements-0-1-0","dir":"Changelog","previous_headings":"","what":"Other composable elements","title":"epidemics 0.1.0","text":"epidemics allows models include elements affect epidemic trajectory, custom classes. Time-dependence: models can passed list functions two arguments, time x expected return x function time, may used model effect seasonality model parameters; Population changes: Applicable diphtheria model, two element list time values, allow definition changes number susceptible individuals model, may used model influxes evacuations individuals humanitarian camps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"output-processing-functions-0-1-0","dir":"Changelog","previous_headings":"","what":"Output processing functions","title":"epidemics 0.1.0","text":"epidemics provides functions help process output epidemic model run, calculate size epidemic demographic group stage (epidemic_size()), calculate number new infections demographic group timepoint model (new_infections()).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"usage-vignettes-0-1-0","dir":"Changelog","previous_headings":"","what":"Usage vignettes","title":"epidemics 0.1.0","text":"epidemics includes range usage vignettes demonstrate : Get started package; Get started modelling interventions social contacts control outbreaks; Model overlapping sequential interventions social contacts; Model interventions modify transition rates model compartments; Get started modelling vaccination campaign; Model time-dependence seasonality disease transmission dynamics; Generate model uncertainty model parameters; Reduce number parameters required final size estimation; Use ‘Vacamole’ model scenarios leaky vaccination vaccine impact hospitalisation; Use ‘Ebola’ model scenarios responses Ebola virus disease outbreak; Use ‘diphtheria’ model scenarios outbreaks humanitarian camp setting.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"miscellaneous-0-1-0","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"epidemics 0.1.0","text":"Workflows render vignettes README website; Test code coverage 93%.","code":""}]
+[{"path":"https://epiverse-trace.github.io/epidemics/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 epidemics authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"scope","dir":"Articles","previous_headings":"","what":"Scope","title":"Design Principles for epidemics","text":"epidemics aims help public health practitioners - rather research-focussed modellers - rapidly simulate disease outbreak scenarios, aims balance flexibility, performance, user-friendliness, maintainability. epidemics trades away flexibility defining model structures gain ease defining epidemic scenario components affected populations model events. epidemics attempts balance performance maintainability minimum sufficient use C++, attempting write domain-specific language (odin). broadly applicable, epidemics provides ‘library’ compartmental models adapted published literature. models focus broad types diseases settings, rather specific diseases scenarios. Thus models intended applicable range diseases.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"output","dir":"Articles","previous_headings":"","what":"Output","title":"Design Principles for epidemics","text":"function outputs expected return structure inherits <data.frame>, make processing easier users. exact structure output - whether list <data.frame>s, <data.table> <tibble>, nested version tabular data classes - yet fixed. eventual stable output type must allow users conveniently access epidemic trajectory data, identify filter intervention scenarios comparisons among , allow interoperability data science tools Tidyverse.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"package-architecture","dir":"Articles","previous_headings":"","what":"Package architecture","title":"Design Principles for epidemics","text":"Fig. 1: epidemics designed allow easy combination composable elements model structure taken library published models, sensible default parameters, allow public health practitioners conveniently model epidemic scenarios efficacy response strategies.  Fig. 2: epidemics package architecture, ODE model stack. epidemics includes multiple internal functions R C++ check inputs suitable model, cross-check inputs compatible . Function names indicate behaviour (e.g. assert_*()), similarly named functions called similar places model function bodies. Partly, reflects privileged positions model components (population, components checked), also composable elements (time-dependence) may vectorised.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"epidemic-modelling","dir":"Articles","previous_headings":"Design decisions","what":"Epidemic modelling","title":"Design Principles for epidemics","text":"notes refer broad decisions individual models – see individual model vignettes published sources modelling decisions. two broad types models: Deterministic models implemented solutions systems ordinary different equations (ODEs), Stochastic models discrete timesteps individuals move compartments probabilistically. epidemics models’ compartmental transitions fixed. Users create new links compartments, although links compartments can disallowed modifying model parameters. models’ epidemiological parameter sets unique, although parameters shared among models. can changed users although reasonable default values provided. model components - population affected epidemic, policy responses form interventions - called composable elements. Composable elements can expected modified users match situation. model components except population optional. model allows unique sets composable elements considered suitable expected use case. E.g. Ebola model allow modelling vaccination regime, considered unlikely Ebola outbreaks. allowed set composable elements subject change, open user requests. effect interventions modelled additive, multiplicative. intervention X% reduction contacts overlaps intervention Y% reduction, cumulative effect contacts \\(C\\) \\(C \\times 1 - (X + Y)\\), rather \\(C \\times (1 - X)(1 - Y)\\). Additive effects considered easier users understand multiplicative effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"ode-systems-and-models","dir":"Articles","previous_headings":"Design decisions","what":"ODE systems and models","title":"Design Principles for epidemics","text":"common method defining solving ODEs R write ODE system R pass solvers deSolve::lsoda() deSolve package. opted approach (referred ‘R-deSolve’). possible write ODE compartmental transitions C++, expose C++ code R, eventually passing ODE system deSolve solvers (referred ‘Rcpp-deSolve’). also opted approach, involves substantial interconversion complex objects structured lists (model composable elements) R C++ solver timestep, reducing performance. ODE systems written C++, solved using Boost odeint solvers fixed step sizes. means within call model_*(), R objects converted use C++ (scalar arguments case), passed back forth multiple times. odeint provided package BH (Boost Headers), making convenient use Rcpp packages. r2sundials package provides Rcpp-friendly interface SUNDIALS ODE solvers, documentation less clear overall, seems recommend use RcppArmadillo RcppXPtrUtils; evaluated use. odeint imposes certain constraints ODE systems. functionality easily define ‘events’ (also called ‘callbacks’) combine ODE system. means ODE systems encapsulate information timing events (interventions) effect. Equations describing right-hand side model ODE systems \\(x' = f(x)\\) thus written structs overloaded function call operator makes FunctionObject types. struct thus holds epidemiological parameters composable elements, passed reference operations, reducing copying. See simple example Boost documentation. can passed function solver, epidemiological parameters calculated solver timestep function time composable elements (applicable). epidemics relies Eigen C++ library provided RcppEigen represent matrices initial conditions. Eigen matrices among types accepted initial states odeint solvers. Alternatives include Boost Basic Linear Algebra Library (uBLAS) standard library arrays vectors; partial list - include Eigen - provided Boost, Armadillo matrices may also supported. use Eigen matrices Eigen offers broad well documented support matrix operations, easy conversion Rcpp types, also conforms previous use Eigen finalsize. models’ C++ code two levels underlie R source code - C++ source code C++ headers. make header code (model ODEs helper functions) shareable can re-used Rcpp packages explored blog post. epidemics defines C++ namespaces package headers clearly indicate certain functionalities sit. model structures namespace epidemics, namespaces vaccination, intervention, time_dependence contain C++ code handle composable elements (calculating effect cumulative interventions). namespace odetools defines initial state type, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"stochastic-models","dir":"Articles","previous_headings":"Design decisions","what":"Stochastic models","title":"Design Principles for epidemics","text":"epidemics currently includes single discrete-time stochastic model implements sub-compartment system taken @getz2018, initially adapted Epirecipes. modelling decisions explained , recognising adding models different implementations see revisited. Stochastic models currently target, expected target, diseases outbreak sizes initially small thus stochasticity matters ; typical example Ebola virus disease (simply, Ebola), reflected model name. Ebola model also expected suitable diseases high fatality risk detected outbreak sizes small, isolation treatment response comparable Ebola, e.g. Marburg virus disease. Note different alternative implementations stochastic models exist. current implementation chosen due use Erlang sub-compartments felt better represent long-tailed distributions infection times seen haemorrhagic fevers like Ebola. model implements two-level structure similar ODE models, .model_ebola_internal() function implementing simulation, model_ebola() user-facing wrapper input checks parameter scenario combination handling. model allows vectors infection parameters duration (called time_end); however number replicates parameter-scenario combination allowed vary. default 100 chosen reasonable middle ground efficiency realism. model allows lists intervention sets time-dependence functions passed. interventions model parameters allowed, interventions social contacts allowed, model include age-stratification transmission (otherwise). parameters infectiousness_rate (often denoted \\(\\sigma\\)) removal_rate (recovery death safe burial, \\(\\gamma\\)) targeted rate interventions time-dependence values determine number sub-compartments exposed infectious (hospitalised) compartments, respectively. fixed start simulation, changing partway challenging support involve redistributing individuals currently sub-compartment fewer sub-compartments. model supports defaults multiple replicates runs parameter-scenario combination. \\(N\\) runs single parameter set single intervention set, runs differ due stochasticity (essentially, different random numbers drawn run). \\(N\\) runs multiple parameter sets single intervention set, runs differ due stochasticity within parameter sets, differences runs across parameter sets (e.g. two different transmission rates) due differences parameter values alone. multiple runs multiple parameter-scenario combinations, differences among runs due differences parameters composable elements (interventions) alone. withr package used ensure seeds preserved across parameter sets interventions. input output types correspond ODE model types. model written R although may change future. main reason keeping implementation R stats::rmultinom() function efficient way drawing categorical distribution (often called discrete distribution) heterogeneous probabilities. StackOverflow question 2014 details including benchmarks implementations using Rcpp; though old, benchmarked minimal example using Boost found information still valid. One possible reason switch least part Ebola model implementation C++ make use efficient random number generation GNU Scientific Library via RcppGSL, although may issues users trying compile source Windows.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"classes","dir":"Articles","previous_headings":"Design decisions","what":"Classes","title":"Design Principles for epidemics","text":"major composable elements bundled custom S3 classes inherit lists, expected understandable elements epidemic response: <population>, <intervention> superclass, <vaccination>. composable elements take form named, structured lists. defined classes expected less used, used advanced modellers comfortable working lists directly. key element composable elements inheriting lists can easily handled within C++ code interpreted Rcpp lists. matrix objects referring demography-group coefficients follow ‘demography--rows’ pattern finalsize, rows represent demography groups, columns represent coefficients. includes initial conditions matrix <population>s, columns epidemiological compartments, also vaccination rates <vaccination>, contacts reductions <contacts_intervention>s. Interventions may <contacts_intervention> <rate_intervention> class, inherit abstract super-class <intervention>. inheritance structure chosen maintain coherence intervention types, keep option open unifying classes single concrete type future. composable elements except population optional. Model functions internally generate dummy values composable elements allowed model, required C++ code. <intervention> <vaccination> objects may combined objects (sub)-class using c() method (sub)-class, resulting object (sub)-class. interpretation class however slightly different: <intervention>: Combining two interventions sub-class understood represent combined application multiple epidemic response strategies, e.g. closing schools also closing workplaces, introducing mask mandates different intervals. <vaccination>: Combining two vaccination objects results two-dose vaccination regime, rather two separate vaccination campaigns (delivering single dose). epidemics focuses initial pandemic response phase vaccination expected available scale, rather long-term vaccination campaigns endemic infections.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"function-vectorisation","dir":"Articles","previous_headings":"Design decisions","what":"Function vectorisation","title":"Design Principles for epidemics","text":"epidemics moving towards allowing vectors lists passed model function arguments, easily allow incorporation parameter uncertainty comparisons multiple scenarios (maintaining comparability across scenarios function call). Consequently, function call may consist many 1000s model runs (see PR #176 vignette scenario modelling). model epidemiological parameters allowed passed numeric vectors (currently ODE models). includes time_end, allows runs different durations within single function call. use case taken report aimed calculate epidemic size given period uncertainty start time (hence duration). epidemics follows Tidyverse rules vector recycling epidemiological parameters. Arguments intervention vaccination accepting composable elements allowed passed lists inputs. case intervention, list lists, element list <intervention> objects (typically one <contacts_intervention> variable number <rate_intervention>s): referred intervention set. composable elements may currently scalar values, may change future (see issue #181 passing lists populations). Model functions internally create combinations composable elements, combination referred scenario, also combine scenario set epidemiological parameters. ensure comparability across scenarios.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"miscellaneous-decisions","dir":"Articles","previous_headings":"","what":"Miscellaneous decisions","title":"Design Principles for epidemics","text":"epidemics follows finalsize example following Google’s C++ code style, using Cpplint Cppcheck static code analysis options Clang-tidy work well Rcpp code; see blog post . Function naming: Function names aim contain verbs indicate function behaviour. Internal input checking functions follow checkmate naming style (e.g. assert_*()). Function naming: Internal functions aim begin . (e.g. .model_default_cpp()) clearly indicate direct use.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"dependencies","dir":"Articles","previous_headings":"","what":"Dependencies","title":"Design Principles for epidemics","text":"aim restrict number hard dependencies maintaining user-friendliness. checkmate: useful input-checking package used across Epiverse packages; cli glue: convenience packages pretty printing methods; reconsidered lighten package dependencies; data.table: lightweight dependency handle data model outputs, especially used nested list column functionality. Rcpp: provides linking C++ R; RcppEigen: provides matrix classes suitable use Boost odeint; BH: provides Boost odeint ODE solvers; withr: seed management; stats utils: already installed R, used Ebola model, hence liable removed future. wider range packages taken soft dependencies make vignettes user-friendly. bench: benchmark epidemics finalsize; bookdown, knitr, rmarkdown: packages generate vignettes format ; dplyr, tibble, tidyr: show processing model outputs; EpiEstim: show links upstream packages estimate R vignette; finalsize: comparison epidemics vignette; ggplot2, scales, colorspace: packages plotting; socialmixr: obtain social contacts matrices; spelling: spell-checking; testthat (>= 3.0.0): unit tests.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/design-principles.html","id":"contribute","dir":"Articles","previous_headings":"","what":"Contribute","title":"Design Principles for epidemics","text":"special requirements contributing epidemics, contributions new models clearly motivated, fall within scope package, target disease type situation already covered existing models, ideally already peer-reviewed. general, please follow package contributing guide.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/epidemics.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Getting started with epidemic scenario modelling components","text":"Prepare population contact data. Prepare initial conditions age group. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE ) #> Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix)  # view contact matrix and demography contact_matrix #>                   #> contact.age.group     [,1]     [,2]     [,3] #>           [0,20)  7.883663 2.794154 1.565665 #>           [20,40) 3.120220 4.854839 2.624868 #>           40+     3.063895 4.599893 5.005571  demography_vector #>   [0,20)  [20,40)      40+  #> 14799290 16526302 28961159 # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix)  # view initial conditions initial_conditions #>                S E     I R V #> [0,20)  0.999999 0 1e-06 0 0 #> [20,40) 0.999999 0 1e-06 0 0 #> 40+     0.999999 0 1e-06 0 0 uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )  uk_population #> <population> object #>  #>  Population name:  #> \"UK\" #>  #>  Demography  #> [0,20): 14,799,290 (20%) #> [20,40): 16,526,302 (30%) #> 40+: 28,961,159 (50%) #>  #>  Contact matrix  #>                   #> contact.age.group   [0,20)  [20,40)      40+ #>           [0,20)  7.883663 2.794154 1.565665 #>           [20,40) 3.120220 4.854839 2.624868 #>           40+     3.063895 4.599893 5.005571"},{"path":"https://epiverse-trace.github.io/epidemics/articles/epidemics.html","id":"note-on-social-contacts-data","dir":"Articles","previous_headings":"Prepare population and initial conditions","what":"Note on social contacts data","title":"Getting started with epidemic scenario modelling components","text":"Note social contacts matrices provided socialmixr[https://CRAN.R-project.org/package=socialmixr] package follow format wherein matrix \\(M_{ij}\\) represents contacts group \\(\\) group \\(j\\). However, epidemic models traditionally adopt notation \\(M_{ij}\\) defines contacts \\(\\) \\(j\\) (Wallinga, Teunis, Kretzschmar 2006). \\(q M_{ij} / n_i\\) defines probability infection, \\(q\\) scaling factor dependent \\(R_0\\) (another measure infection transmissibility), \\(n_i\\) population proportion group \\(\\). ODEs epidemics also follow convention. consistency notation, social contact matrices socialmixr need transposed (using t()) used epidemics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/epidemics.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Getting started with epidemic scenario modelling components","text":"","code":"# run an epidemic model using `epidemic` output <- model_default(   population = uk_population,   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/epidemics.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Getting started with epidemic scenario modelling components","text":"Plot epidemic time, showing number individuals exposed infected compartments.","code":"# plot figure of epidemic curve filter(output, compartment %in% c(\"exposed\", \"infectious\")) %>%   ggplot(     aes(       x = time,       y = value,       col = demography_group,       linetype = compartment     )   ) +   geom_line() +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 500e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )"},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"different-use-cases-of-finalsize-and-epidemics","dir":"Articles","previous_headings":"","what":"Different use cases of finalsize and epidemics","title":"Reducing parameters required for final size estimation","text":"finalsize epidemics can used calculate epidemic final size, aimed different use cases. finalsize assumes infection population characteristics fixed initial conditions. infection, includes properties transmission rate, population, includes social contacts demographic groups, proportion demographic groups specific levels susceptibility infection. advantage finalsize requires define initial transmission rate infection susceptibility population, rather time-dependent processes drive epidemic shape, duration infectiousness latent period infection. questions relating epidemic shape, rather shape, results much simpler set inputs. However, also means finalsize used model temporal dynamics epidemic response, used answer policy questions temporal component, implement interventions. epidemics includes number scenario models, assumptions. models allow modification initial characteristics outbreak due range events. infection, includes interventions (masking treatments) reduce number forward transmissions deaths, also seasonal effects may increase decrease transmission rate. population, initial conditions social contacts can influenced interventions well. makes much easier model temporal dynamics public-health policy decisions taken epidemic response epidemics many features allow modelling. However, requires inputs defined, including time-dependent infections processes. can also difficult model scenarios complicated susceptibility structure required, demographic groups underlying immunity infection due past exposure vaccination. Thus epidemics likely especially useful outbreaks novel pathogens (Covid-19 pandemic) little population immunity infection. easier configure finalsize ---box scenarios complex demographic patterns underlying susceptibility (immunity ) infection, potentially due history previous outbreaks policy responses (vaccination). Thus, model temporal dynamics, can quickly provide useful initial estimates final size outbreaks, without write compartmental models implement multiple policy decisions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"converting-scenarios-between-finalsize-and-epidemics","dir":"Articles","previous_headings":"","what":"Converting scenarios between finalsize and epidemics","title":"Reducing parameters required for final size estimation","text":", show example show model similar scenario using finalsize epidemics. example, might want study full epidemic dynamics future, start simpler final size estimate meantime. show build equivalent models, allowing extensions model epidemic temporal dynamics (using epidemics) later. illustration, use epidemics model effect vaccination trajectory epidemic. finalsize allow implementation dynamic vaccination calendar, can model reduced susceptibility infection population, due prior vaccination. two methods comparable model vaccination epidemics occurring main wave epidemic, sets underlying susceptibility.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"prepare-population-and-model-parameters","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Prepare population and model parameters","title":"Reducing parameters required for final size estimation","text":"first prepare population (modelled U.K.), initial conditions, model parameters, passing epidemics::model_default(). example include interventions vaccination regimes. Code prepare model inputs folded brevity. See “Get started” vignette explanation prepare inputs. model spread influenza pandemic potential, assuming $R_0 = $ 1.5, pre-infectious period 3 days, infectious period 7 days. leads following model parameters transmission rate \\(\\beta\\), rate transition exposed infectious \\(\\sigma\\), recovery rate \\(\\gamma\\).","code":"# load contact and population data from socialmixr::polymod polymod <- polymod contact_data <- contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix)  # initial conditions: one in every 1 million is infected initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions ) rownames(initial_conditions) <- rownames(contact_matrix) # prepare the population to model as affected by the epidemic # the contact_matrix, demography_vector, and initial_conditions # have been prepared in the folded code above uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )  # view the population uk_population #>  #>  Population name:  #>  Demography  #> [0,20): 14,799,290 (20%) #> [20,40): 16,526,302 (30%) #> 40+: 28,961,159 (50%) #>  #>  Contact matrix  #>                   #> contact.age.group   [0,20)  [20,40)      40+ #>           [0,20)  7.883663 2.794154 1.565665 #>           [20,40) 3.120220 4.854839 2.624868 #>           40+     3.063895 4.599893 5.005571 # simulate pandemic parameters transmission_rate <- 1.5 / 7 infectiousness_rate <- 1 / 3 recovery_rate <- 1 / 7"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"implementing-vaccination-in-epidemics","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Implementing vaccination in epidemics","title":"Reducing parameters required for final size estimation","text":"simplicity, implement vaccination regime vaccines delivered individuals age 40 course roughly six months (150 days) main epidemic peak. assume 1 every 1000 individuals age group vaccinated every day; translates approximately 28,900 individuals per day. assume vaccination non-leaky, protecting vaccinated individuals infection, due model structure ‘default’ SEIR-V model epidemics use . New modelling vaccination using epidemics? may help read “Modelling vaccination campaign” vignette first. first create <vaccination> object represent vaccination regime. pass vaccination regime epidemic function optional vaccination argument, model 600 days epidemic. obtain ‘final’ epidemic size using epidemics::epidemic_size().","code":"# prepare a vaccination object vaccinate_elders <- vaccination(   name = \"vaccinate elders\",   time_begin = matrix(1, nrow(contact_matrix)),   time_end = matrix(150, nrow(contact_matrix)),   nu = matrix(c(0.0, 0.0, 0.001)) ) # model epidemic with vaccination prior to the main epidemic wave output <- model_default(   population = uk_population,   transmission_rate = transmission_rate,   infectiousness_rate = infectiousness_rate,   recovery_rate = recovery_rate,   vaccination = vaccinate_elders,   time_end = 600, increment = 1.0 )  # Calculate the epidemic size using the helper function finalsize_dat <- tibble(   demography_group = names(demography_vector),   value = epidemic_size(output) / demography_vector )  # View the data finalsize_dat #> # A tibble: 3 × 2 #>   demography_group value #>   <chr>            <dbl> #> 1 [0,20)           0.617 #> 2 [20,40)          0.525 #> 3 40+              0.343"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"calculating-individuals-vaccinated-in-epidemic-model","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Calculating individuals vaccinated in epidemic model","title":"Reducing parameters required for final size estimation","text":"compare results ODE model analytical method, necessary set population’s susceptibility demography--susceptibility matrices reflect proportion individuals age group vaccinated outbreak. , need calculate total proportion individuals age group vaccinated end epidemic model run.","code":"# Proportion of the individuals vaccinated p_vacc <- filter(output, compartment == \"vaccinated\", time == max(time)) p_vacc <- p_vacc$value / demography_vector"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"implementing-vaccination-in-finalsize","dir":"Articles","previous_headings":"Converting scenarios between finalsize and epidemics","what":"Implementing vaccination in finalsize","title":"Reducing parameters required for final size estimation","text":"use proportion individuals vaccinated age group set matrices pass susceptibility p_susceptibility arguments finalsize::final_size(). New final size estimation heterogeneity susceptibility infection? may help read “Modelling heterogeneous susceptibility” vignette, “Guide constructing susceptibility matrices” finalsize first. create susceptibility matrix two groups, ‘unvaccinated’, full susceptibility, ‘vaccinated’, immune infection. create demography--susceptibility matrix reflect individuals >40 age group vaccinated. Since vaccination implemented age groups, assume individuals groups fully susceptible. calculate expected final size using modified susceptibility matrices, combine data output ODE model previous example. need scale contact matrix appropriately. can print data compare values, similar. However, note epidemics::epidemic_size() can used time point epidemic, finalsize::final_size() returns size end epidemic, showing epidemics suitable examine temporal dynamics.","code":"# create the susceptibility matrix susceptibility <- matrix(   data = 1,   nrow = length(demography_vector),   ncol = 2,   dimnames = list(     names(demography_vector),     c(\"unvaccinated\", \"vaccinated\")   ) ) # Second column holds the vaccinated (who are protected fully) susceptibility[, \"vaccinated\"] <- 0  # Assume susceptibility varies within age groups p_susceptibility <- matrix(   data = 1.0,   nrow = length(demography_vector),   ncol = 2,   dimnames = list(     names(demography_vector),     c(\"unvaccinated\", \"vaccinated\")   ) ) p_susceptibility[, \"vaccinated\"] <- p_vacc p_susceptibility[, \"unvaccinated\"] <- 1 - p_vacc # Define population in each age group scalar <- max(eigen(contact_data$matrix)$values) contact_matrix <- (contact_data$matrix / demography_vector) / scalar # Calculate the proportion of individuals infected in each age group dat1 <- final_size(   r0 = 1.5,   contact_matrix = contact_matrix,   demography_vector = demography_vector,   susceptibility = susceptibility,   p_susceptibility = p_susceptibility )  # Final size returns the proportion infected in each susceptibility group # (i.e. non vaccinated and vaccinated) # here we calculate the proportion of infected for the age group as a whole dat3 <- dat1 %>%   select(     -susceptibility,     final_size = p_infected   ) %>%   filter(susc_grp == \"unvaccinated\") %>%   select(-susc_grp)  fs <- dat3$unvaccinated * p_susceptibility[, \"unvaccinated\"]  finalsize_dat <- finalsize_dat %>%   select(demo_grp = demography_group, seir_v = value) %>%   left_join(dat3) finalsize_dat #> # A tibble: 3 × 3 #>   demo_grp seir_v final_size #>   <chr>     <dbl>      <dbl> #> 1 [0,20)    0.617      0.660 #> 2 [20,40)   0.525      0.542 #> 3 40+       0.343      0.272 # note that epidemic_size() returns the absolute values # epidemic size after 10% of the epidemic model run epidemic_size(data = output, stage = 0.1) #> [1] 574.4348 488.3563 585.5760  # epidemic size at 50% epidemic_size(data = output, stage = 0.5) #> [1] 5565772 4890178 5254726"},{"path":"https://epiverse-trace.github.io/epidemics/articles/finalsize_comparison.html","id":"consideration-of-computational-speed","dir":"Articles","previous_headings":"","what":"Consideration of computational speed","title":"Reducing parameters required for final size estimation","text":"important reason use finalsize final size calculations may speed — finalsize::final_size() much faster epidemics::epidemic_size() applied epidemics::model_default(). makes much suitable high-performance applications fitting data. benchmarking shows total time taken 1,000 runs using methods low, methods used scan across multiple values input parameters, dealing parameter uncertainty. Note model runs using epidemics implement complex compartmental structure, multiple interventions vaccination regimes likely slower example shown . However, users choose finalsize assumptions underlying final size calculation met. example, cases vaccinations concurrent large number infections, interventions applied reduce transmission, final size assumptions met. cases, users advised use dynamical model epidemics instead.","code":"# run benchmarks using {bench} benchmark <- mark(   analytical_method = final_size(     r0 = 1.5,     contact_matrix = contact_matrix,     demography_vector = demography_vector,     susceptibility = susceptibility,     p_susceptibility = p_susceptibility   ),   ode_model = epidemic_size(     model_default(       population = uk_population,       transmission_rate = transmission_rate,       infectiousness_rate = infectiousness_rate,       recovery_rate = recovery_rate,       vaccination = vaccinate_elders,       time_end = 600, increment = 1.0     )   ),   iterations = 1000,   time_unit = \"s\",   check = FALSE )  # view the total time for 1000 runs in seconds select(as_tibble(benchmark), expression, total_time) #> # A tibble: 2 × 2 #>   expression        total_time #>   <bch:expr>             <dbl> #> 1 analytical_method      0.467 #> 2 ode_model             10.9"},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_diphtheria.html","id":"modelling-an-outbreak-with-pre-existing-immunity","dir":"Articles","previous_headings":"","what":"Modelling an outbreak with pre-existing immunity","title":"Modelling a diphtheria outbreak in a humanitarian camp setting","text":"create population object corresponding Kutupalong camp Cox’s Bazar, Bangladesh 2017-18, rounded nearest 100, described Additional file 1 provided Finger et al. (2019). population three age groups, < 5 years, 5 – 14 years, \\(\\geq\\) 15 years. assume one individual infectious age group. assume, following Finger et al. (2019), 20% 5 – 14 year-olds vaccinated (immune ) diphtheria prior start outbreak, coverage much lower among age groups. run model default parameters, assuming : diphtheria \\(R_0\\) 4.0 mean infectious period 4.5 days, giving transmission rate (\\(\\beta\\)) 0.889; diphtheria pre-infectious incubation period 3 days, giving infectiousness rate (\\(\\sigma\\)) 0.33; recovery rate diphtheria 0.33. also make several assumptions regarding clinical progression reporting. Specifically: case reporting (3% infections reported cases), proportion reported cases needing hospitalisation (1%), time taken cases needing hospitalisation seek admitted hospital (5 days, giving daily hospitalisation rate 0.2 among cases), time spent hospital (5 days, giving daily hospitalisation recovery rate 0.2). Finally, assume interventions seasonal effects affect dynamics transmission outbreak. run model plot outcomes. Figure 1: Model results single run showing number individuals infectious diphtheria 100 days outbreak.","code":"# three age groups with five compartments SEIHR n_age_groups <- 3 demography_vector <- c(83000, 108200, 224600) initial_conditions <- matrix(0, nrow = n_age_groups, ncol = 5)  # 1 individual in each group is infectious initial_conditions[, 1] <- demography_vector - 1 initial_conditions[, 3] <- rep(1, n_age_groups)  # camp social contact rates are assumed to be uniform within and between # age groups camp_pop <- population(   contact_matrix = matrix(1, nrow = n_age_groups, ncol = n_age_groups),   demography_vector = demography_vector,   initial_conditions = initial_conditions / demography_vector )  camp_pop #>  #>  Population name:  #>  Demography  #> Dem. grp. 1: 83,000 (20%) #> Dem. grp. 2: 108,200 (30%) #> Dem. grp. 3: 224,600 (50%) #>  #>  Contact matrix  #>              Dem. grp. 1: Dem. grp. 2: Dem. grp. 3: #> Dem. grp. 1:            1            1            1 #> Dem. grp. 2:            1            1            1 #> Dem. grp. 3:            1            1            1 # 20% of 5-14 year-olds are vaccinated prop_vaccinated <- c(0.05, 0.2, 0.05) data <- model_diphtheria(   population = camp_pop,   prop_vaccinated = prop_vaccinated ) filter(data, compartment == \"infectious\") %>%   ggplot() +   geom_line(     aes(time, value, colour = demography_group)   ) +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\",     labels = c(\"<5\", \"5-15\", \">15\")   ) +   expand_limits(     x = c(0, 101)   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     y = \"Individuals infectious\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_diphtheria.html","id":"modelling-an-outbreak-with-changing-population-sizes","dir":"Articles","previous_headings":"","what":"Modelling an outbreak with changing population sizes","title":"Modelling a diphtheria outbreak in a humanitarian camp setting","text":"now model outbreak, increase susceptible individuals towards end outbreak, illustrate effect influx non-immune individuals outbreak dynamics. example, assume prior immunity among new arrivals population. prepare population change schedule named list giving times change, corresponding changes demographic group. Note model assumes changes apply susceptible compartment, assume wider population entering camp yet affected diphtheria (.e. infected recovered arrival), already infected hospitalised individuals leave camp. , population size camp increases 75% overall, similar reported values Kutupalong camp scenario (Finger et al. 2019). Figure 2: Model results single run showing number individuals infectious diphtheria 100 days outbreak, increase camp population size. Shaded blue region shows number individuals susceptible infection (right-hand side Y axis). example shows increase number susceptibles population can lead rise transmission potential infection therefore extend duration outbreak.","code":"# susceptibles increase by about 12%, 92%, and 89% of initial sizes pop_change <- list(   time = 70,   values = list(     c(1e4, 1e5, 2e5)   ) ) data <- model_diphtheria(   population = camp_pop,   population_change = pop_change )  # summarise population change in susceptibles data_pop_size <- filter(data, compartment == \"susceptible\") %>%   group_by(time) %>%   summarise(     total_susceptibles = sum(value)   ) ggplot() +   geom_area(     data = data_pop_size,     aes(time, total_susceptibles / 10),     fill = \"steelblue\", alpha = 0.5   ) +   geom_line(     data = filter(data, compartment == \"infectious\"),     aes(time, value, colour = demography_group)   ) +   geom_vline(     xintercept = pop_change$time,     colour = \"red\",     linetype = \"dashed\",     linewidth = 0.2   ) +   annotate(     geom = \"text\",     x = pop_change$time,     y = 20e3,     label = \"Population increase\",     angle = 90,     vjust = \"inward\",     colour = \"red\"   ) +   scale_y_continuous(     labels = scales::comma,     sec.axis = dup_axis(       trans = function(x) x * 10,       name = \"Individuals susceptible\"     )   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group (individuals infectious)\",     labels = c(\"<5\", \"5-15\", \">15\")   ) +   expand_limits(     x = c(0, 101)   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     y = \"Individuals infectious\"   )"},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Prepare population data — model, need total population size initial conditions. can create <population> object dummy values contact matrix, assign total size demography vector. prepare population total size 14 million, corresponding population Guinea, West African country 2014 Ebola virus epidemic originated. assume 1 person initially infected infectious, 10 people exposed yet become infectious.","code":"population_size <- 14e6  # prepare initial conditions as proportions initial_conditions <- c(   S = population_size - 11, E = 10, I = 1, H = 0, F = 0, R = 0 ) / population_size # prepare a <population> object guinea_population <- population(   name = \"Guinea\",   contact_matrix = matrix(1), # note dummy value   demography_vector = 14e6, # 14 million, no age groups   initial_conditions = matrix(     initial_conditions,     nrow = 1   ) )  guinea_population #>  #>  Population name:  #>  Demography  #> Dem. grp. 1: 14,000,000 (100%) #>  #>  Contact matrix  #>              Dem. grp. 1: #> Dem. grp. 1:            1"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"prepare-model-parameters","dir":"Articles","previous_headings":"","what":"Prepare model parameters","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"use default model parameters, beginning \\(R_0\\) taken value estimated ebola Guinea (Althaus 2014). assume ebola mean infectious period 12 days, time exposure symptom onset — pre-infectious period — 5 days. Together, give following values: Transmission rate (\\(\\beta\\)): 0.125, Infectiousness rate (\\(\\gamma^E\\) Getz Dougherty (2018)): 0.4, Removal rate (\\(\\gamma^\\) Getz Dougherty (2018)): 0.1667 model yet explicit “deaths” compartment, rather, “removed” compartment holds individuals recovered died buried safely. Functionally, similar part model dynamics. assume 10% infectious individuals hospitalised, hospitalisation achieves modest 30% reduction transmission hospitalised individuals still susceptible. assume also deaths hospital lead ebola-safe funerals, infections result . assume infectious individuals hospitalised die community, funerals potentially ebola-safe. assume transmission rate ebola funerals 50% baseline transmission rate. can also interpreted proportion funerals ebola-safe.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"run model using function model_ebola(). model run 100 days (default), data reported day. appropriate period obtain initial predictions outbreak, response efforts non-pharmaceutical interventions vaccination campaigns likely launched bring outbreak control. function automatically runs 100 replicates (stochastic realisations) default, can changed using replicates argument.","code":"# run with a pre-set seed for consisten results # run the epidemic model using `epidemic` # we call the model \"ebola\" from the library data <- withr::with_seed(   1,   model_ebola(     population = guinea_population   ) )  # view the head of the output head(data) #>     time demography_group  compartment    value replicate #>    <int>           <char>       <char>    <num>     <int> #> 1:     0     demo_group_1  susceptible 13999989         1 #> 2:     0     demo_group_1      exposed       10         1 #> 3:     0     demo_group_1   infectious        1         1 #> 4:     0     demo_group_1 hospitalised        0         1 #> 5:     0     demo_group_1      funeral        0         1 #> 6:     0     demo_group_1      removed        0         1"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"plot size ebola epidemic time; epidemic size taken number individuals considered ‘removed’. Figure 1: Model results single run showing epidemic size 100 days outbreak. model assumes 1 initially infectious person exposed 10 others. Grey lines show 100 stochastic realisations model replicates. observe model stochasticity leads wide variation model outcomes within first 100 days: outbreaks may much severe mean outbreak. Note nearly replicates, epidemic size increasing near exponential rates. can find size replicate using epidemic_size() function original simulation data. Note final size refers final size 100 days, duration simulation. Looking model parameter uncertainty? vignette modelling parameter uncertainty helpful information also applicable Ebola model.","code":"# plot figure of epidemic curve filter(data, compartment == \"removed\") %>%   ggplot(     aes(       x = time, y = value     )   ) +   geom_line(aes(group = replicate), linewidth = 0.2, colour = \"grey\") +   stat_summary(     fun.min = function(x) quantile(x, 0.025),     fun.max = function(x) quantile(x, 0.975),     geom = \"ribbon\", fill = \"red\", alpha = 0.2   ) +   stat_summary(geom = \"line\") +   scale_y_continuous(     labels = scales::comma   ) +   expand_limits(     x = c(0, 101),     y = c(-10, NA)   ) +   coord_cartesian(expand = FALSE) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     y = \"Outbreak size\"   ) # apply the function over each replicate data_final_size <- nest(data, .by = \"replicate\") %>%   mutate(     final_size = map_dbl(data, epidemic_size)   )  # get range of final sizes range(data_final_size$final_size) #> [1]  97 686"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"applying-interventions-that-reduce-transmission","dir":"Articles","previous_headings":"","what":"Applying interventions that reduce transmission","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Interventions affect model parameters (called rate interventions) can simulated Ebola outbreak way models; creating passing rate interventions covered vignette modelling rate interventions. Note model include demographic variation contacts, EVD spreads primarily among contacts caring infected individuals, making age demographic structure less important. Thus model allows interventions model rates (demographic groups contacts interventions). , compare effect intervention begins 15 days outbreak, reduces transmission 20%, counterfactual, baseline scenario specific outbreak response. simulate 100 days previous examples. Figure 2: Effect implementing intervention reduces transmission 20% ebola outbreak. intervention begins 15th day (dotted vertical line), active remainder model duration. Applying intervention leads many fewer individuals infectious ebola outbreak. see applying intervention reduces transmission may effective reducing outbreak sizes.","code":"# create an intervention on the transmission rate reduce_transmission <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.2 )  # create a list of intervention scenarios intervention_scenarios <- list(   baseline = NULL,   response = list(     transmission_rate = reduce_transmission   ) ) # run the epidemic model and save data as the baseline, using a fixed seed data_scenarios <- withr::with_seed(   1,   model_ebola(     population = guinea_population,     intervention = intervention_scenarios   ) )  # assign scenario names data_scenarios$scenario <- c(\"baseline\", \"response\")  # unnest the data, preserving scenario identifiers data_scenarios <- select(data_scenarios, data, scenario) %>%   unnest(data) filter(data_scenarios, compartment == \"removed\") %>%   ggplot(aes(time, value, colour = scenario)) +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(group = interaction(scenario, replicate)),     linewidth = 0.2, alpha = 0.5   ) +   stat_summary(     geom = \"ribbon\",     fun.min = function(x) quantile(x, 0.025),     fun.max = function(x) quantile(x, 0.975),     alpha = 0.3, colour = NA,     aes(fill = scenario)   ) +   stat_summary(     geom = \"line\", linewidth = 1   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Intervention\")   ) +   scale_fill_brewer(     palette = \"Dark2\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Intervention\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"modelling-the-roll-out-of-vaccination","dir":"Articles","previous_headings":"","what":"Modelling the roll-out of vaccination","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"can also model rollout vaccination EVD, model structured differently models epidemics, vaccination must modelled differently . model_ebola() accept vaccination regime <vaccination> object, can still model effect vaccination gradual decrease transmission rate \\(\\beta\\) time. done using time dependence functionality epidemics. New implementing parameter time dependence epidemics? may help read vignette time dependence functionality first! Note time-dependence composable element passed set scenarios. first define function suitable time_dependence argument. function assumes baseline transmission rate ebola decreases time, 0.5% reduction day due vaccination. Figure 3: Effect implementing vaccination regime gradually reduces ebola transmission time, using time dependence functionality. Similar functionality can used model parameters flexibly allowed <rate_intervention> class.","code":"# we assume a 0.5% daily reduction # we assume that this vaccination begins on the 15th day time_dep_vax <- function(     time, x, time_start = 15, reduction = 0.005) {   if (time < time_start) {     x   } else {     x * (1.0 - reduction)^time   } } data_baseline <- with_seed(   1,   model_ebola(     population = guinea_population   ) ) data_vax_scenario <- with_seed(   1,   model_ebola(     population = guinea_population,     time_dependence = list(       transmission_rate = time_dep_vax     )   ) )  data_baseline$scenario <- \"baseline\" data_vax_scenario$scenario <- \"scenario\"  # bind the data together data_scenarios <- bind_rows(data_baseline, data_vax_scenario) filter(data_scenarios, compartment == \"removed\") %>%   ggplot(aes(time, value, colour = scenario)) +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(group = interaction(scenario, replicate)),     linewidth = 0.2, alpha = 0.5   ) +   stat_summary(     geom = \"ribbon\",     fun.min = function(x) quantile(x, 0.025),     fun.max = function(x) quantile(x, 0.975),     alpha = 0.3, colour = NA,     aes(fill = scenario)   ) +   stat_summary(     geom = \"line\", linewidth = 1   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Vaccination campaign\")   ) +   scale_fill_brewer(     palette = \"Dark2\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Vaccination campaign\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"modelling-a-multi-pronged-ebola-response","dir":"Articles","previous_headings":"","what":"Modelling a multi-pronged ebola response","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Since EVD severe disease high case fatality risk, responses outbreak may require simultaneous implementation number measures reduce transmission end outbreak quickly. can use EVD model existing functionality epidemics model implementation multi-pronged response ebola aims improve: detection treatment cases, safety hospitals risk community transmission, safety funeral practices reduce risk transmission dead bodies. , show combined effects interventions separately. can pass interventions model function’s intervention argument named list, names indicating model parameters target. Figure 4: Effect implementing multiple simultaneous interventions reduce transmission ebola outbreak, beginning 15th day (dotted vertical line), remaining active remainder model duration. Applying interventions substantially reduces final size outbreak, potential plateau outbreak size reached 100 days. Individual scenario replicates shown background, shaded region shows 95% interval, heavy central line shows mean scenario.","code":"# create an intervention on the transmission rate improve_hospitalisation <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.3 )  # create an intervention on ETU risk improve_etu_safety <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.7 )  # create an intervention on the transmission rate reduce_funeral_risk <- intervention(   type = \"rate\",   time_begin = 15, time_end = 100, reduction = 0.5 ) # create a list of single and combined interventions intervention_scenarios <- list(   baseline = NULL,   combined = list(     transmission_rate = reduce_transmission,     prop_community = improve_hospitalisation,     etu_risk = improve_etu_safety,     funeral_risk = reduce_funeral_risk   ) ) # run the epidemic model and save data as the baseline, using a fixed seed data_scenarios <- withr::with_seed(   1,   model_ebola(     population = guinea_population,     intervention = intervention_scenarios   ) ) # name the scenarios and unnest the data data_scenarios <- mutate(   data_scenarios,   scenario = names(intervention_scenarios) )  data_scenarios <- select(data_scenarios, scenario, data) %>%   unnest(data) filter(data_scenarios, compartment == \"removed\") %>%   ggplot(aes(time, value, colour = scenario)) +   geom_vline(     xintercept = 15,     linetype = \"dotted\"   ) +   geom_line(     aes(group = interaction(scenario, replicate)),     linewidth = 0.2, alpha = 0.5   ) +   stat_summary(     geom = \"ribbon\",     fun.min = function(x) quantile(x, 0.025),     fun.max = function(x) quantile(x, 0.975),     alpha = 0.3, colour = NA,     aes(fill = scenario)   ) +   stat_summary(     geom = \"line\", linewidth = 1   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Combined interventions\")   ) +   scale_fill_brewer(     palette = \"Dark2\",     name = \"Scenario\",     labels = c(\"Baseline\", \"Combined interventions\")   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Days\",     y = \"Outbreak size\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"details-discrete-time-ebola-virus-disease-model","dir":"Articles","previous_headings":"","what":"Details: Discrete-time Ebola virus disease model","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"model compartments adopted consensus model Ebola virus disease presented Li et al. (2019), transitions epidemiological compartments modelled using Erlang sub-compartments adapted Getz Dougherty (2018); see References. R code model adapted code Ha Minh Lam initially made available Epirecipes MIT license. transition rates exposed infectious, infectious funeral compartments (also hospitalised removed), \\(\\gamma^E\\) \\(\\gamma^\\) Getz Dougherty’s notation, passed user infectiousness_rate removal_rate respectively. shape Erlang distributions passage times exposed infectious compartments (\\(k^E\\) \\(k^\\)) recommended set 2 sensible choice, default value erlang_sbubcompartments argument, can allowed vary (independently). Getz Dougherty’s equation (6) gives relationship parameters mean pre-infectious \\(\\rho^E\\) infectious \\(\\rho^\\) periods. \\[\\gamma^E = \\dfrac{k^E}{\\rho^E} = \\dfrac{2}{\\rho^E} ~\\text{}~ \\gamma^= \\dfrac{k^}{\\rho^} = \\dfrac{2}{\\rho^}\\] discrete time model, \\(\\gamma^E\\) \\(\\gamma^\\) used determine passage times newly exposed infectious individuals respective compartments (thus allowing variation passage times).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_ebola.html","id":"hospitalisation-funerals-and-removal","dir":"Articles","previous_headings":"Details: Discrete-time Ebola virus disease model","what":"Hospitalisation, funerals, and removal","title":"Modelling responses to a stochastic Ebola virus epidemic","text":"Li et al. (2019) present consensus model EVD individuals can follow multiple pathways infectious compartment — hospitalisation, funeral transmission, safe burial recovery (removed), possibility skipping compartments sequence (e.g. directly infectious removed, infectious hospitalisation removed etc.). model simplifies transitions two pathways: Infectious → funeral → removed (safe burial) Infectious → hospitalised → removed (recovery safe burial) proportion, 1.0 - prop_community, infectious individuals transferred hospitalised compartment timestep, compartment represents Ebola Treatment Units (ETUs), individuals hospitalised compartment considered infectious longer community. passage time individuals hospitalised compartment similar individuals infectious compartment (.e., infectious community), means infectious individual \\(N\\) timesteps exiting infectious compartment exit hospitalised compartment time. Hospitalised individuals can contribute transmission Ebola susceptibles depending value \\(p_\\text{ETU}\\), probability (proportion) hospitalised cases contributing infection susceptibles. interpreted relative risk Ebola virus treatment units (ETUs), range 0.0 – 1.0, 0.0 indicates hospitalisation prevents onward transmission entirely, 1.0 indicates hospitalisation reduce transmission . passed argument etu_risk. assume deaths hospital lead Ebola-safe funerals, individuals exiting hospitalised compartment move ‘removed’ compartment, holds recoveries deaths. assume infectious individuals hospitalised die, deaths outside hospital lead funerals potentially Ebola-safe, contribution funerals Ebola transmission determined \\(p_\\text{funeral}\\), can interpreted relative risk funerals, passed funeral_risk argument. Values closer 0.0 indicate low risk Ebola transmission funerals, values closer 1.0 indicate risk similar transmission community. Individuals assumed spend single timestep funeral transmission compartment, move ‘removed’ compartment. Individuals ‘removed’ compartment affect model dynamics.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"modifications-for-epidemics","dir":"Articles","previous_headings":"","what":"Modifications for epidemics","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"made modifications ODE model Vacamole order make general thus potentially applicable wider range settings. Specifically, dropped ICU ICU2H compartment potentially less relevant context intensive care capacity low. added transitions infectious () hospitalised (H) compartments death (D), may general assumption hospital capacity low (relatively → D) treatments poor (relatively H → D). assume, first pass implementation vaccination primarily reduces adverse outcomes, modification transition rates (\\(\\beta_V,\\eta_{V},\\omega_V\\)): \\(\\beta_V\\): transmission rate \\(\\beta\\) individuals fully vaccinated compartment \\(V_2\\); \\(\\eta_{V}\\): hospitalisation rate \\(\\eta\\) fully vaccinated, infected individuals (\\(I_V\\) → \\(H_V\\)); \\(\\omega_V\\): mortality rate fully vaccinated individuals stage post infection (, H). details ODE system version Vacamole included epidemics can found end page.","code":"library(epidemics) library(dplyr) library(tidyr) library(ggplot2) library(colorspace) library(scales)"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"Prepare population contact data. Prepare initial conditions age group. Vacamole model 11 compartments therefore requires matrix 11 columns. Prepare time days model epidemic, outbreak beginning day zero. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-6  # // 0| 1| 2|3| 4|5| 6|7| 8|9|10 # // S|V1|V2|E|EV|I|IV|H|HV|D|R  # make initial conditions - order is important initial_conditions <- c(   S = 1 - initial_i,   V1 = 0, V2 = 0,   E = 0, EV = 0,   I = initial_i, IV = 0,   H = 0, HV = 0, D = 0, R = 0 ) initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) epidemic_days <- 300 uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"prepare-a-two-dose-vaccination-campaign","dir":"Articles","previous_headings":"","what":"Prepare a two dose vaccination campaign","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"prepare two-dose vaccination campaign concatenating two single dose vaccination regimes, .e., applying function c() two vaccination objects. possible combine multiple vaccination objects together using c() — limitation vaccination regimes combined way must number demographic groups. possible add single dose two-vaccination regime using c() two vaccination objects two one dose, respectively.","code":"# prepare a two dose vaccination regime for a single age group # prepare the first dose dose_1 <- vaccination(   name = \"two-dose vaccination\", # name given to first dose   nu = matrix(1e-2, nrow = 3),   time_begin = matrix(30, nrow = 3),   time_end = matrix(epidemic_days, nrow = 3) )  # prepare the second dose with a 30 day interval in start date dose_2 <- vaccination(   name = \"two-dose vaccination\", # name given to first dose   nu = matrix(1e-2, nrow = 3),   time_begin = matrix(60, nrow = 3),   time_end = matrix(epidemic_days, nrow = 3) )  # use `c()` to combine the two doses double_vaccination <- c(dose_1, dose_2)  # print to visualise double_vaccination #>  #>  Vaccination name:  #>  Begins at:  #>      dose_1 dose_2 #> [1,]     30     60 #> [2,]     30     60 #> [3,]     30     60 #>  #>  Ends at:  #>      dose_1 dose_2 #> [1,]    300    300 #> [2,]    300    300 #> [3,]    300    300 #>  #>  Vaccination rate:  #>      dose_1 dose_2 #> [1,]   0.01   0.01 #> [2,]   0.01   0.01 #> [3,]   0.01   0.01"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"model-epidemic-using-vacamole","dir":"Articles","previous_headings":"","what":"Model epidemic using Vacamole","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"First, run model vaccination. default behaviour, vaccination regime need specified included. model’s default parameters : Transmission rate (\\(\\beta\\), transmission_rate): 0.186, resulting \\(R_0\\) = 1.3 infectious period 7 days, given \\(\\beta = R_0 / \\text{infectious period}\\). Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.5, assuming pre-infectious period 2 days, given \\(\\sigma = 1 / \\text{pre-infectious period}\\). Hospitalisation rate (\\(\\eta\\), hospitalistion_rate): 1.0 / 1000, assuming one every thousand infectious individuals hospitalised. Mortality rate (\\(\\omega\\), mortality_rate): 1.0 / 1000, assuming one every thousand infectious hospitalised individuals dies. Recovery rate (\\(\\gamma\\), recovery_rate): 0.143, assuming infectious period 7 days, given \\(\\gamma = 1 / \\text{infectious period}\\). Susceptibility reduction vaccination (susc_reduction_vax): 0.2, assuming 20% reduction susceptibility individuals doubly vaccinated. Hospitalisation reduction vaccination (hosp_reduction_vax): 0.2, assuming 20% reduction hospitalisation individuals doubly vaccinated. Mortality reduction vaccination (mort_reduction_vax): 0.2, assuming 20% reduction mortality individuals doubly vaccinated. Next run model two dose vaccination regime.","code":"# note model will automatically account for no vaccination data <- model_vacamole(   population = uk_population,   time_end = epidemic_days ) data_vaccination <- model_vacamole(   population = uk_population,   vaccination = double_vaccination, # note vaccination object for two doses   time_end = epidemic_days )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"visualise-model-outcomes","dir":"Articles","previous_headings":"","what":"Visualise model outcomes","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"First, calculate total number infections resulting recoveries deaths course simulation; epidemic’s final size.  Finally, can compare peak hospital bed occupancy scenario — can rough indication much hospital capacity required pandemic characteristics occur, well another way examine effect vaccination reducing requirement. example demonstrates implementing vaccination can substantially reduce peak hospital occupancy (100%) compared scenario vaccines deployed.","code":"# collect data from the two scenarios data_scenarios <- list(data, data_vaccination)  # get deaths and recoveries from infection data_scenarios <- Map(   data_scenarios, c(\"no_vax\", \"vax\"),   f = function(df, sc) {     df_ <- distinct(df, demography_group)      # get total deaths per group     df_$total_deaths <- filter(       df, time == max(time), compartment == \"dead\"     ) %>% pull(value)      # get total recoveries per group using helper function `epidemic_size()`     # do not count dead     df_$total_recovered <- epidemic_size(df, include_deaths = FALSE)      # add scenario information     df_$scenario <- sc      # return data     df_   } )  # collect data data_scenarios <- bind_rows(data_scenarios)  # transform to long format data_scenarios <- pivot_longer(   data_scenarios,   cols = c(\"total_deaths\", \"total_recovered\"),   names_to = \"measure\" ) ggplot(data_scenarios) +   geom_col(     aes(demography_group, value, fill = scenario),     position = \"dodge\",     colour = \"black\"   ) +   facet_wrap(     facets = vars(measure),     scales = \"free_y\",     labeller = labeller(       measure = c(         total_deaths = \"Total deaths\",         total_recovered = \"Epidemic size (infections without deaths)\"       )     )   ) +   scale_fill_discrete_qualitative(     palette = \"Dynamic\",     labels = c(\"No vaccination\", \"Vaccination\"),     name = \"Scenario\",     na.value = \"lightgrey\"   ) +   scale_y_continuous(     labels = label_comma(       scale = 1e-6, suffix = \"M\"     )   ) +   theme_bw() +   theme(     legend.position = \"bottom\",     legend.key.height = unit(2, \"mm\"),     strip.background = element_blank(),     strip.text = element_text(       face = \"bold\",       size = 11     )   ) +   expand_limits(     x = c(0.5, length(unique(data_scenarios$demography_group)) + 0.5)   ) +   coord_cartesian(     expand = FALSE   ) +   labs(     x = \"Age group\",     y = \"No. of individuals\",     title = \"Effect of vaccination on deaths and total infections\"   ) # collect data from the two scenarios data_scenarios <- list(data, data_vaccination)  peak_hospital_occupancy <- vapply(data_scenarios, function(df) {   # get highest hospital occupancy   # first get total hospitalisations among vaccinated and un- or part-vacc.   df <- filter(     df,     grepl(       pattern = \"hospitalised\", x = compartment,       fixed = TRUE     )   ) %>%     # summarise all hospitalised over time, aggregating away age groups     summarise(       total_hosp = sum(value), .by = \"time\"     ) %>%     # filter for the time point with highest hospital occupancy     filter(total_hosp == max(total_hosp)) %>%     # get the value     pull(total_hosp) }, FUN.VALUE = numeric(1))  # set names for comprehensibility names(peak_hospital_occupancy) <- c(\"No vaccination\", \"Vaccination\")  # show peak hospital occupancy in a readable format format(peak_hospital_occupancy, big.mark = \",\", digits = 1) #> No vaccination    Vaccination  #>        \"1,813\"        \"    8\""},{"path":"https://epiverse-trace.github.io/epidemics/articles/model_vacamole.html","id":"vacamole-ode-system-for-epidemics","dir":"Articles","previous_headings":"","what":"Vacamole ODE system for {epidemics}","title":"Modelling leaky vaccination and hospitalisation outcomes with Vacamole","text":"Vacamole ODE system adapted {epidemics} : Susceptibles vaccinated, partially vaccinated (considered unprotected) can transition exposed vaccinated: \\[dS = -\\beta S(+I_V) - \\nu_1 S\\] Two sequential vaccination compartments, lower conversion rate two-dose vaccinated individuals (considered protected) exposed: \\[dV_1 = \\nu_1S - \\beta V_1(+I_V) - \\nu_2V_1\\] \\[dV_2 = \\nu_2V_1 - \\beta_VV_2(+I_V)\\] Two parallel exposed compartments, similar conversion infectious: \\[dE = \\beta (S+V_1)(+I_V) - \\sigma E\\] \\[dE_V = \\beta_VV_2(+I_V) - \\sigma E_V\\] Two parallel infectious compartments, lower hospitalisation mortality rate vaccinated: \\[dI = \\sigma E - \\gamma - \\eta - \\omega \\] \\[dI_V = \\sigma E_V - \\gamma I_V - \\eta_{V} I_V - \\omega_V I_V\\] Two parallel hospitalisation compartments, lower mortality rate vaccinated: \\[dH = \\eta - \\gamma H - \\eta_2 H - \\omega H\\] \\[dH_V = \\eta_{V} - \\gamma H_V - \\omega_V H_V\\] Single recovered compartment: \\[dR = \\gamma(+ H + I_V + H_V)\\] Single mortality compartment: \\[dD = \\omega(+ H) + \\omega_V(I_V + H_V)\\]","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Getting started with modelling interventions targeting social contacts","text":"Prepare population contact data. Prepare initial conditions age group. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE ) #> Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"note-on-social-contacts-data","dir":"Articles","previous_headings":"Prepare population and initial conditions","what":"Note on social contacts data","title":"Getting started with modelling interventions targeting social contacts","text":"epidemics expects social contacts matrices \\(M_{ij}\\) represent contacts \\(\\) \\(j\\) (Wallinga, Teunis, Kretzschmar 2006), \\(q M_{ij} / n_i\\) probability infection, \\(q\\) scaling factor dependent infection transmissibility, \\(n_i\\) population proportion group \\(\\). Social contacts matrices provided socialmixr[https://CRAN.R-project.org/package=socialmixr] package follow opposite convention, \\(M_{ij}\\) represents contacts group \\(\\) group \\(j\\). Thus social contact matrices socialmixr need transposed (using t()) used epidemics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"prepare-an-intervention","dir":"Articles","previous_headings":"","what":"Prepare an intervention","title":"Getting started with modelling interventions targeting social contacts","text":"Prepare intervention simulate school closures.","code":"# prepare an intervention with a differential effect on age groups close_schools <- intervention(   name = \"School closure\",   type = \"contacts\",   time_begin = 200,   time_end = 300,   reduction = matrix(c(0.5, 0.001, 0.001)) )  # examine the intervention object close_schools #> <contacts_intervention> object #>  #>  Intervention name:  #> \"School closure\" #>  #>  Begins at:  #> [1] 200 #>  #>  Ends at:  #> [1] 300 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1     0.500 #> Demo. grp. 2     0.001 #> Demo. grp. 3     0.001"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Getting started with modelling interventions targeting social contacts","text":"","code":"# run an epidemic model using `epidemic` output <- model_default(   population = uk_population,   intervention = list(contacts = close_schools),   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_interventions.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Getting started with modelling interventions targeting social contacts","text":"Plot epidemic time, showing number individuals exposed infected compartments.","code":"# plot figure of epidemic curve filter(output, compartment %in% c(\"exposed\", \"infectious\")) %>%   ggplot(     aes(       x = time,       y = value,       col = demography_group,       linetype = compartment     )   ) +   geom_line() +   annotate(     geom = \"rect\",     xmin = close_schools$time_begin,     xmax = close_schools$time_end,     ymin = 0, ymax = 500e3,     fill = alpha(\"red\", alpha = 0.2),     lty = \"dashed\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 400e3,     angle = 90,     label = \"School closure\"   ) +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 500e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )"},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"prepare population contact data U.K., epidemiological compartments matching default epidemic model (SEIR-V). assume one every million people infected infectious, translating 67 total infections U.K. population 67 million. code steps similar “Getting started vignette” hidden , although can expanded reference.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-4 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"examine-the-baseline","dir":"Articles","previous_headings":"","what":"Examine the baseline","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"first examine baseline scenario — interventions implemented slow spread epidemic — visualise outcomes terms daily new infections. simulate epidemic using model_default(), calling default model outlined “Get started vignette”. show one instance plotting code using ggplot2 package , instances hidden keep vignette short. Figure 1: model infectious disease epidemic, assuming directly transmitted infection influenza, \\(R_0\\) 1.3, infectious period 5 days, pre-infectious period 1.5 days. baseline scenario, epidemic continue approximately 400 days, one year, peak new infections 150th 180th day different age groups. scenario, epidemic expected final size around 23 million individuals infected overall. following sections shall iteratively model effects applying non-pharmaceutical interventions reduce contacts examine whether epidemic’s final size reduced, whether peak infections can spread time.","code":"# no intervention baseline scenario data_baseline <- model_default(   population = uk_population,   time_end = 400, increment = 1.0 )  # get new infections data_baseline_infections <- new_infections(data_baseline, by_group = TRUE) # visualise the spread of the epidemic in terms of new infections # plot figure of epidemic curve plot_baseline <- ggplot() +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_baseline"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"modelling-overlapping-interventions","dir":"Articles","previous_headings":"","what":"Modelling overlapping interventions","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"shall prepare multiple interventions plausibly implemented course epidemic. can use c() function combine two intervention objects single intervention accommodates effect interventions. multiple intervention can passed — single intervention object — epidemic model model_default(). can combine number intervention objects single intervention object passed model_default(). cumulative effect interventions handled automatically C++ code underlying epidemics. Remember two multiple interventions can also combined using c(). important careful make sure interventions intend combine concatenated together. example, c(combined_interventions, combined_interventions) valid, effectively double effect school workplace closures example. simulate epidemic using model_default() function, calling default model outlined “Get started vignette”. simulate epidemic 600 days. Figure 3: Epidemic model two overlapping interventions early phase outbreak: school closures target infections among younger people, workplace closures target infections among working-age adults. scenario school closures 6 months well workplace closures 2 months, epidemic still continue approximately 600 days, one half years, number days 10,000 daily cases reduced, typically occur intervention workplaces lifted. scenario, epidemic expected final size around 22 million individuals infected overall — similar school closures intervention. distinct peak new infections schools simulated re-open, nearly 100,000 new infections days.","code":"# combine interventions using `c()` combined_interventions <- c(   close_schools, close_workplaces )  # visualise the combined intervention object combined_interventions #>  #>  Intervention name:  #>  Begins at:  #>      npi_1 npi_2 #> [1,]    60    80 #>  #>  Ends at:  #>      npi_1 npi_2 #> [1,]   240   140 #>  #>  Reduction:  #>              Interv. 1 Interv. 2 #> Demo. grp. 1      0.30      0.01 #> Demo. grp. 2      0.01      0.30 #> Demo. grp. 3      0.01      0.01 # get data from an epidemic model with both interventions data_combined <- model_default(   population = uk_population,   intervention = list(contacts = combined_interventions),   time_end = 600, increment = 1.0 )  # get data on new infections data_infections <- new_infections(data_combined, by_group = TRUE) plot_intervention_cases <-   ggplot() +   geom_vline(     xintercept = c(       close_schools$time_begin,       close_schools$time_end     ),     linetype = \"dotted\"   ) +   geom_vline(     xintercept = c(       close_workplaces$time_begin,       close_workplaces$time_end     ),     colour = \"red\",     linetype = \"dotted\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 50000,     label = \"Schools closed\"   ) +   annotate(     geom = \"text\",     x = mean(c(       close_workplaces$time_begin,       close_workplaces$time_end     )),     y = 30000,     colour = \"red\",     label = \"Workplaces\\nclosed\"   ) +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   geom_line(     data = data_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"solid\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_intervention_cases"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"school-closures","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"School closures","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"first example, shall model school closures, primarily aimed reducing infections among younger individuals transmit families. first prepare intervention simulates effect closing schools reduce contacts younger people. assume reduces contacts age group 0 – 19 30%, contacts age groups 1% (adults meet individuals age). intervention assumed last 6 months approximately 180 days, beginning 100th day outbreak — similar duration initial school closures Covid-19 pandemic 2020 U.K. simulate epidemic 600 days expect intervention spread disease incidence longer period. Figure 2: Epidemic model intervention targets infections among children closing schools six months, thus reducing children’s social contacts. school closures scenario, epidemic continue approximately 600 days, one half years, 10,000 daily new infections one year. scenario, epidemic expected final size around 22 million individuals infected overall.","code":"# prepare an intervention that models school closures for ~3 months (100 days) close_schools <- intervention(   name = \"School closure\",   type = \"contacts\",   time_begin = 60,   time_end = 60 + 180,   reduction = matrix(c(0.3, 0.01, 0.01)) )  # examine the intervention object close_schools #>  #>  Intervention name:  #>  Begins at:  #> [1] 60 #>  #>  Ends at:  #> [1] 240 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.30 #> Demo. grp. 2      0.01 #> Demo. grp. 3      0.01 # no intervention baseline scenario data_schools_closed <- model_default(   population = uk_population,   intervention = list(contacts = close_schools),   time_end = 600, increment = 1.0 )  # get new infections data_noschool_infections <- new_infections(data_schools_closed, by_group = TRUE) # visualise the spread of the epidemic in terms of new infections when # schools are closed plot_noschool <-   ggplot() +   geom_vline(     xintercept = c(       close_schools$time_begin,       close_schools$time_end     ),     linetype = \"dotted\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 1000,     label = \"Schools closed\"   ) +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   geom_line(     data = data_noschool_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"solid\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_noschool"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"workplace-closures","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"Workplace closures","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"General workplace closures broad-based measure aimed reducing infections among working age adults. shall prepare intervention simulates effect closing workplaces addition closing schools, assume reduces contacts age group 20 – 65 30%, contacts age groups 1% (assume individuals age groups meeting many individuals workplaces). intervention assumed last 60 days, beginning 80th day outbreak — simulates situation policymakers decide close workplaces three weeks deciding close schools, choose keep workplaces closed long (2 months 60 days vs. 6 months 180 days school closures).","code":"# prepare an intervention which mostly affects adults 20 -- 65 intervention_duration <- 60 close_workplaces <- intervention(   name = \"Workplace closure\",   type = \"contacts\",   time_begin = 80,   time_end = 80 + intervention_duration,   reduction = matrix(c(0.01, 0.3, 0.01)) )  # examine the intervention object close_workplaces #>  #>  Intervention name:  #>  Begins at:  #> [1] 80 #>  #>  Ends at:  #> [1] 140 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.01 #> Demo. grp. 2      0.30 #> Demo. grp. 3      0.01"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"combining-interventions","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"Combining interventions","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"can use c() function combine two intervention objects single intervention accommodates effect interventions. multiple intervention can passed — single intervention object — epidemic model model_default(). intervention object made multiple interventions first intervention specified treated baseline intervention, age-specific effect reducing contacts duration effect. interventions assumed additional percentage point increases effect active interventions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_multiple_interventions.html","id":"re-applying-workplace-closures","dir":"Articles","previous_headings":"Modelling overlapping interventions","what":"Re-applying workplace closures","title":"Modelling overlapping and sequential interventions targeting social contacts","text":"scenario combined interventions, daily new infections forecast exceed 50,000 397th day epidemic. final example, simulate re-implementing two months workplace closures, school closures, reduce infections. Combine multiple interventions object two interventions third intervention. simulate epidemic using model_default() function 600 days . Figure 4: Epidemic model two initial, overlapping interventions schools workplaces, followed later intervention workplaces. scenario school closures 6 months well two phases workplace closures 2 months , epidemic continue 600 days, one half years, number days 10,000 daily cases reduced, typically occur interventions workplaces lifted — similar previous example. scenario, epidemic expected final size around 15 million individuals infected overall — lower previous examples.","code":"# log the date that cases exceed 50000 daily start_date <- min(   which(     new_infections(data_combined, by_group = FALSE)[, new_infections > 50000]   ) )  # create a new workplace closures object workplace_closures_2 <- intervention(   type = \"contacts\",   time_begin = start_date,   time_end = start_date + 60,   reduction = matrix(c(0.01, 0.3, 0.01)) ) combined_interventions <- c(combined_interventions, workplace_closures_2) # get data from an epidemic model with both interventions data_combined <- model_default(   population = uk_population,   intervention = list(contacts = combined_interventions),   time_end = 600, increment = 1.0 )  # get data on new infections data_infections <- new_infections(data_combined, by_group = TRUE) plot_three_interventions <-   ggplot() +   geom_vline(     xintercept = c(       close_schools$time_begin,       close_schools$time_end     ),     linetype = \"dotted\"   ) +   geom_vline(     xintercept = c(       close_workplaces$time_begin,       close_workplaces$time_end,       workplace_closures_2$time_begin,       workplace_closures_2$time_end     ),     colour = \"red\",     linetype = \"dotted\"   ) +   annotate(     geom = \"text\",     x = mean(c(close_schools$time_begin, close_schools$time_end)),     y = 50000,     label = \"Schools closed\"   ) +   annotate(     geom = \"text\",     x = c(       mean(         c(close_workplaces$time_begin, close_workplaces$time_end)       ),       mean(c(workplace_closures_2$time_begin, workplace_closures_2$time_end))     ),     y = 30000,     colour = \"red\",     label = c(\"Workplaces\\nclosed\", \"Workplaces\\nclosed\")   ) +   geom_line(     data = data_baseline_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"dashed\"   ) +   geom_line(     data = data_infections,     aes(time, new_infections, colour = demography_group),     linetype = \"solid\"   ) +   scale_y_sqrt(     labels = scales::comma,     breaks = c(10^seq(3, 5), 5e4)   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )  plot_three_interventions"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_rate_interventions.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling other interventions that change transmission rates","text":"prepare population contact data U.K., epidemiological compartments matching default epidemic model (SEIR-V). assume one every million people infected infectious, translating 67 total infections U.K. population 67 million. code steps similar “Getting started vignette” hidden , although can expanded reference.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-4 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_rate_interventions.html","id":"modelling-an-intervention-on-the-transmission-rate","dir":"Articles","previous_headings":"","what":"Modelling an intervention on the transmission rate","title":"Modelling other interventions that change transmission rates","text":"model intervention transmission rate \\(\\beta\\) reduces 10%. represent interventions requiring people wear masks reduce transmission. first run baseline scenario — interventions implemented slow spread epidemic — visualise outcomes terms daily new infections. simulate epidemic using model_default(), calling default model outlined “Get started vignette”. examine effect mask mandate, simulate epidemic 200 days expect intervention spread disease incidence longer period. plot data examine effect implementing mask mandate daily number new infections.","code":"# prepare an intervention that models mask mandates for ~3 months (100 days) mask_mandate <- intervention(   name = \"mask mandate\",   type = \"rate\",   time_begin = 60,   time_end = 60 + 100,   reduction = 0.1 )  # examine the intervention object mask_mandate #>  #>  Intervention name:  #>  Begins at:  #>      [,1] #> [1,]   60 #>  #>  Ends at:  #>      [,1] #> [1,]  160 #>  #>  Reduction:  #> Interv. 1  #>       0.1  # check the object is_intervention(mask_mandate) #> [1] TRUE  is_contacts_intervention(mask_mandate) #> [1] FALSE  is_rate_intervention(mask_mandate) #> [1] TRUE # no intervention baseline scenario data <- model_default(   population = uk_population,   time_end = 200, increment = 1.0 )  # with a mask mandate data_masks <- model_default(   population = uk_population,   intervention = list(transmission_rate = mask_mandate),   time_end = 200, increment = 1.0 ) # get new infections in each scenario data <- new_infections(data, by_group = TRUE) data_masks <- new_infections(data_masks, by_group = TRUE)  # assign a scenario name to each scenario data$scenario <- \"baseline\" data_masks$scenario <- \"masks\"  # bind data together data_combined <- bind_rows(data, data_masks) ggplot(data_combined) +   geom_line(     aes(time, new_infections, col = demography_group, linetype = scenario)   ) +   coord_cartesian(     expand = FALSE   ) +   annotate(     geom = \"rect\",     xmin = mask_mandate[[\"time_begin\"]],     xmax = mask_mandate[[\"time_end\"]],     ymin = 0, ymax = 150e3,     fill = alpha(\"red\", alpha = 0.2),     lty = \"dashed\"   ) +   scale_y_continuous(     labels = scales::comma   ) +   scale_linetype_manual(     name = \"Scenario\",     values = c(       baseline = \"dashed\",       masks = \"solid\"     )   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 100e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"New infections\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"modelling-parameter-uncertainty","dir":"Articles","previous_headings":"","what":"Modelling parameter uncertainty","title":"Modelling parameter uncertainty and epidemic scenarios","text":"Uncertainty characteristics epidemic key element roadblock epidemic response (Shea et al. 2020). Epidemic dynamics can influenced two main sources uncertainty: intrinsic randomness transmission process, uncertain knowledge parameters underlying transmission process. focus latter, .e. uncertainty input parameters epidemic model. epidemics model functions can accept numeric vectors infection parameters; model run parameter combination using population model components (interventions, vaccinations) etc. allows users quickly obtain results range parameter values without repeatedly call model_*() loop similar; iteration performed internally. benefits vectorising inputs: Inputs checked , rather \\(N\\) times element parameter vector — improves performance manual iteration; Model output organised make filtering parameter values scenarios easier (). Note always possible pass single value infection parameter. Single values may referred “scalar” values “scalars”. Passing scalar infection parameters yield simple table model “time”, “demography group”, “compartment”, “value”, number individuals demographic group compartment model time point. Click “Code” see hidden code used set population vignette. details define populations initial model conditions please see “Getting started epidemic scenario modelling components” vignette. brief, model U.K. population three age groups, 0 – 19, 20 – 39, > 40, social contacts stratified age. unnest output’s “data” column order plot incidence curves transmission rate value. Figure 1: Incidence curves number new infections day epidemic given uncertainty R estimate; colours indicate \\(R\\) bins. Larger \\(R\\) values lead shorter epidemics higher peaks, lower R values lead spread epidemics lower peaks. Epidemics \\(R\\) < 1.0 ‘take ’ clearly visible. Linking incidence curves \\(R\\) values plot allows quick visual assessment potential outcomes epidemic whose \\(R\\) uncertain.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix)  # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions ) # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) # UK population created from hidden code uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions ) # select the parameter set and data columns with dplyr::select() # add the R value for visualisation # calculate new infections, and use tidyr to unnest the data column data <- select(output, param_set, transmission_rate, data) %>%   mutate(     r_value = r_samples,     new_infections = map(data, new_infections)   ) %>%   select(-data) %>%   unnest(new_infections) # plot the data filter(data) %>%   ggplot() +   geom_line(     aes(time, new_infections, col = r_value, group = param_set),     alpha = 0.3   ) +   # use qualitative scale to emphasize differences   scale_colour_fermenter(     palette = \"Dark2\",     name = \"R\",     breaks = c(0, 1, 1.5, 2.0, 3.0),     limits = c(0, 3)   ) +   scale_y_continuous(     name = \"New infections\",     labels = scales::label_comma(scale = 1e-3, suffix = \"K\")   ) +   labs(     x = \"Time (days since start of epidemic)\"   ) +   facet_grid(     cols = vars(demography_group)   ) +   theme_bw() +   theme(     legend.position = \"top\",     legend.key.height = unit(2, \"mm\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"obtaining-estimates-of-disease-transmission-rate","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Obtaining estimates of disease transmission rate","title":"Modelling parameter uncertainty and epidemic scenarios","text":"example, consider influenza pandemic potential (Ghani et al. 2010), prepare multiple samples estimated \\(R\\). reflects pandemic response scenarios \\(R\\) estimates always come uncertainty (due limitations data estimation methods). Sampling distribution \\(R\\) expected follow allows us better understand extent variance possible epidemic outcomes. obtain probability distribution function (PDF) distribution serial intervals; Gamma distribution shape \\(k\\) = 2.622 scale \\(\\theta\\) = 0.957 (Ghani et al. 2010). forthcoming Epiverse package epiparameter expected make substantially easier access use epidemiological parameters, serial interval, reported literature, making easier model scenarios differing intrinsic characteristics pathogen causing outbreak. use PDF estimate \\(R\\) 2009 influenza pandemic U.K., using EpiEstim package. use \\(R\\) estimate (mean standard deviation) EpiEstim generate 100 samples \\(R\\), assuming normally distributed. Users drawing parameters greater variance may wish draw larger number samples.","code":"# Get 2009 influenza data for school in Pennsylvania data(Flu2009) flu_early_data <- filter(Flu2009$incidence, dates < \"2009-05-10\")  # get the PDF of the distribution of serial intervals serial_pdf <- dgamma(seq(0, 25), shape = 2.622, scale = 0.957) # ensure probabilities add up to 1 by normalising them by the sum serial_pdf <- serial_pdf / sum(serial_pdf)  # Use EpiEstim to estimate R with uncertainty # Uses Gamma distribution by default output_R <- estimate_R(   incid = flu_early_data,   method = \"non_parametric_si\",   config = make_config(list(si_distr = serial_pdf)) )  # Plot output to visualise plot(output_R, \"R\")"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"passing-a-vector-of-transmission-rates","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Passing a vector of transmission rates","title":"Modelling parameter uncertainty and epidemic scenarios","text":", generate 100 samples \\(R\\), convert transmission rate (often denoted \\(\\beta\\)) dividing infectious period 7 days. Since EpiEstim estimates \\(Rt\\), instantaneous \\(R\\), shall use mean estimates time period, mean standard deviation, parameters distribution draw \\(R\\) samples model. output nested <data.table>, output run model unique transmission_rate contained <data.frame> list column \"data\".","code":"# get mean mean and sd over time r_estimate_mean <- mean(output_R$R$`Mean(R)`) r_estimate_sd <- mean(output_R$R$`Std(R)`)  # Generate 100 R samples r_samples <- with_seed(   seed = 1,   rnorm(     n = 100, mean = r_estimate_mean, sd = r_estimate_sd   ) )  infectious_period <- 7 beta <- r_samples / infectious_period # pass the vector of transmissibilities to the argument `transmission_rate` output <- model_default(   population = uk_population,   transmission_rate = beta,   time_end = 600 )  # view the output head(output) #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1977482                 0.5     0.1428571      600         1 #> 2:         0.2333557                 0.5     0.1428571      600         2 #> 3:         0.1885540                 0.5     0.1428571      600         3 #> 4:         0.2954036                 0.5     0.1428571      600         4 #> 5:         0.2397671                 0.5     0.1428571      600         5 #> 6:         0.1892204                 0.5     0.1428571      600         6 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #> 4: <population[4]>                                <list[1]>         1        1 #> 5: <population[4]>                                <list[1]>         1        1 #> 6: <population[4]>                                <list[1]>         1        1 #>                    data #>                  <list> #> 1: <data.table[9015x4]> #> 2: <data.table[9015x4]> #> 3: <data.table[9015x4]> #> 4: <data.table[9015x4]> #> 5: <data.table[9015x4]> #> 6: <data.table[9015x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"output-type-for-vector-parameter-inputs","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Output type for vector parameter inputs","title":"Modelling parameter uncertainty and epidemic scenarios","text":"output model_*() infection parameter passed vector nested <data.table>. similar nested <tibble>, can handled popular data science packages, Tidyverse. handling nested data can found section list-columns R Data Science documentation nested data tidyr package. Equivalent operations possible <data.table>s directly; see R Bloggers post unnesting data.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"passing-parameter-sets","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Passing parameter sets","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics model functions can accept multiple infection parameters vectors, long vectors length, length 1 (scalar values) shown .","code":"beta <- rnorm(n = 100, mean, sd) gamma <- rnorm(n = 100, mean, sd) # the recovery rate  model_default(   population,   transmission_rate = beta, # same length as gamma   infectiousness_rate = 0.5, # length 1   recovery_rate = gamma )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"passing-vectors-of-epidemic-duration","dir":"Articles","previous_headings":"Modelling parameter uncertainty","what":"Passing vectors of epidemic duration","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics allows duration model run varied, may useful examining variation start time epidemic affects outcomes fixed end point. example shows estimate potential variation final epidemic size range epidemic start times (hence durations, assuming fixed end).  NOTE: duration model runs varied, model output potentially distinct number rows.","code":"# draw samples of time_end max_time <- 600 duration <- max_time - with_seed(seed = 1, {   rnbinom(100, 1, 0.02) }) # view durations ggplot() +   geom_histogram(aes(duration)) +   theme_bw() +   labs(     x = \"Epidemic duration\",     y = \"Count\"   ) # pass the vector of durations to `time_end` output <- model_default(   population = uk_population,   time_end = duration )  # view the output head(output) #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571      589         1 #> 2:         0.1857143                 0.5     0.1428571      595         2 #> 3:         0.1857143                 0.5     0.1428571      568         3 #> 4:         0.1857143                 0.5     0.1428571      583         4 #> 5:         0.1857143                 0.5     0.1428571      589         5 #> 6:         0.1857143                 0.5     0.1428571      593         6 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #> 4: <population[4]>                                <list[1]>         1        1 #> 5: <population[4]>                                <list[1]>         1        1 #> 6: <population[4]>                                <list[1]>         1        1 #>                    data #>                  <list> #> 1: <data.table[8850x4]> #> 2: <data.table[8940x4]> #> 3: <data.table[8535x4]> #> 4: <data.table[8760x4]> #> 5: <data.table[8850x4]> #> 6: <data.table[8910x4]> # calculate the epidemic size to view the mean and SD of sizes epidemic_size_estimates <- select(output, param_set, data) %>%   mutate(     size = map(data, function(x) {       tibble(         demography_group = unique(x$demography_group),         size = epidemic_size(x)       )     })   ) %>%   select(size) %>%   unnest(size) %>%   summarise(     across(size, .fns = c(mean = mean, sd = sd)),     .by = \"demography_group\"   ) # view the range of epidemic sizes range(epidemic_size_estimates$size) #> [1]  Inf -Inf"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"modelling-scenarios-of-epidemic-response","dir":"Articles","previous_headings":"","what":"Modelling scenarios of epidemic response","title":"Modelling parameter uncertainty and epidemic scenarios","text":"Users may wish model epidemic trajectories outcomes multiple scenarios response measures. epidemics model functions can accept lists intervention sets vaccination regimes, allowing multiple intervention, vaccination, combined intervention--vaccination sets modelled population. benefits passing lists composable elements: Combinations intervention vaccination scenarios can conveniently created, model functions automatically create possible combinations arguments intervention vaccination; Input-checking cross-checking reduced checking element intervention vaccination list independently combination created (population, cross-checking); hence \\(N\\) intervention sets \\(M\\) vaccination regimes \\(N+M\\) cross-checks, rather \\(N \\time M\\) cross-checks; Model output organised provide scenario identifier, making subsetting easier (). may help read “Modelling non-pharmaceutical intervention targeting social contacts” “Modelling effect vaccination campaign” vignettes first! function epidemic_size() can applied nested data column data get final size scenario. example shows implementing interventions reduce transmission can reduce final size epidemic. unnesting output follows procedure , shown .","code":"# set intervention labels labels <- c(   \"No response\", \"Close schools\", \"Close workplaces\", \"Close both\",   \"Mask mandate\", \"Masks + close schools\", \"Masks + close workplaces\",   \"Masks + close both\" )  epidemic_size_estimates <- mutate(   output,   scenario = labels,   size = scales::comma(     map_dbl(data, epidemic_size, by_group = FALSE, include_deaths = FALSE)   ) ) %>%   select(scenario, size)  # view the final epidemic sizes epidemic_size_estimates #>                    scenario       size #>                      <char>     <char> #> 1:              No response 23,084,960 #> 2:            Close schools 21,495,236 #> 3:         Close workplaces 22,423,830 #> 4:               Close both  6,622,568 #> 5:             Mask mandate 22,712,782 #> 6:    Masks + close schools 17,215,645 #> 7: Masks + close workplaces 20,564,673 #> 8:       Masks + close both  2,044,188"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"which-model-components-can-be-passed-as-lists","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Which model components can be passed as lists","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics currently offers ability pass intervention sets vaccination regimes lists. currently possible pass lists populations, seasonality, population changes models. future, may possible pass multiple populations list, rapidly conveniently model epidemic different populations, examine effect assumptions population’s social contacts demographic structure.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"creating-a-list-of-intervention-sets","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Creating a list of intervention sets","title":"Modelling parameter uncertainty and epidemic scenarios","text":"shall create list ‘intervention sets’, set representing scenario epidemic response measures. Note intervention set simply list <intervention> objects; typically, single <contacts_intervention> <rate_interventions> infection parameters. prepared interventions, create intervention sets, pass model function. Note parameter uncertainty included . can visualise effect intervention set form epidemic’s final size, aggregating age groups. output nested <data.table> — can quickly get table final epidemic sizes scenarios — key initial indicator effectiveness interventions. Note example, use model’s default \\(R\\) estimate 1.3. higher values \\(R\\), get counter-intuitive results effects interventions reduce transmission. explored detail later vignette.","code":"# prepare durations as starting at 25% of the way through an epidemic # and ending halfway through time_begin <- max_time / 4 time_end <- max_time / 2  # create three distinct contact interventions # prepare an intervention that models school closures for 180 days close_schools <- intervention(   name = \"School closure\",   type = \"contacts\",   time_begin = time_begin,   time_end = time_end,   reduction = matrix(c(0.3, 0.01, 0.01)) )  # prepare an intervention which mostly affects adults 20 -- 65 close_workplaces <- intervention(   name = \"Workplace closure\",   type = \"contacts\",   time_begin = time_begin,   time_end = time_end,   reduction = matrix(c(0.01, 0.3, 0.01)) )  # prepare a combined intervention combined_intervention <- c(close_schools, close_workplaces) # create a mask-mandate rate intervention # prepare an intervention that models mask mandates for 300 days mask_mandate <- intervention(   name = \"mask mandate\",   type = \"rate\",   time_begin = time_begin,   time_end = time_end,   reduction = 0.1 ) # create intervention sets, which are combinations of contacts and rate # interventions intervention_scenarios <- list(   baseline = NULL,   scenario_01 = list(     contacts = close_schools   ),   scenario_02 = list(     contacts = close_workplaces   ),   scenario_03 = list(     contacts = combined_intervention   ),   scenario_04 = list(     transmission_rate = mask_mandate   ),   scenario_05 = list(     contacts = close_schools,     transmission_rate = mask_mandate   ),   scenario_06 = list(     contacts = close_workplaces,     transmission_rate = mask_mandate   ),   scenario_07 = list(     contacts = combined_intervention,     transmission_rate = mask_mandate   ) ) # pass the list of intervention sets to the model function output <- model_default(   uk_population,   intervention = intervention_scenarios,   time_end = 600 )  # examine the output head(output) #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571      600         1 #> 2:         0.1857143                 0.5     0.1428571      600         1 #> 3:         0.1857143                 0.5     0.1428571      600         1 #> 4:         0.1857143                 0.5     0.1428571      600         1 #> 5:         0.1857143                 0.5     0.1428571      600         1 #> 6:         0.1857143                 0.5     0.1428571      600         1 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>    <list[1]>                   <list[1]>         1        2 #> 3: <population[4]>    <list[1]>                   <list[1]>         1        3 #> 4: <population[4]>    <list[1]>                   <list[1]>         1        4 #> 5: <population[4]>    <list[1]>                   <list[1]>         1        5 #> 6: <population[4]>    <list[2]>                   <list[1]>         1        6 #>                    data #>                  <list> #> 1: <data.table[9015x4]> #> 2: <data.table[9015x4]> #> 3: <data.table[9015x4]> #> 4: <data.table[9015x4]> #> 5: <data.table[9015x4]> #> 6: <data.table[9015x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"output-type-for-list-intervention-inputs","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Output type for list intervention inputs","title":"Modelling parameter uncertainty and epidemic scenarios","text":"output model_*() either intervention vaccination passed list, nested <data.table>. similar output type parameters passed vectors, \"scenario\" column indicating intervention set distinct scenario, helps grouping model outputs \"data\".","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"combinations-of-intervention-and-vaccination-scenarios","dir":"Articles","previous_headings":"Modelling scenarios of epidemic response","what":"Combinations of intervention and vaccination scenarios","title":"Modelling parameter uncertainty and epidemic scenarios","text":"either intervention vaccination passed lists (intervention sets, vaccination regimes, respectively), model run combination elements. Thus \\(M\\) intervention sets \\(N\\) vaccination regimes, model runs \\(M \\times N\\) times, combination treated unique scenario. Note ‘intervention’ ‘vaccination’ scenarios automatically created, must passed explicitly NULL respective lists. number intervention vaccination combinations expected many, addition parameter uncertainty scenario (next section) may rapidly multiply number times model run. Users advised mindful number scenario combinations create.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"modelling-epidemic-response-scenarios-with-parameter-uncertainty","dir":"Articles","previous_headings":"","what":"Modelling epidemic response scenarios with parameter uncertainty","title":"Modelling parameter uncertainty and epidemic scenarios","text":"epidemics allows parameter uncertainty combined scenario models multiple intervention sets vaccination campaigns. , shall draw 100 samples transmission rate mean 0 low standard deviation 0.005. output nested <data.table> , can handled way.","code":"beta <- with_seed(   seed = 1,   code = {     rnorm(100, 1.3 / 7, 0.005)   } ) # this example includes 100 samples of transmission rates for each intervention # including the baseline output <- model_default(   uk_population,   transmission_rate = beta,   intervention = intervention_scenarios,   time_end = 600 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"output-type-for-intervention-and-parameter-set-combinations","dir":"Articles","previous_headings":"Modelling epidemic response scenarios with parameter uncertainty","what":"Output type for intervention and parameter set combinations","title":"Modelling parameter uncertainty and epidemic scenarios","text":"output model_*() either intervention vaccination passed list, infection parameters passed vector nested <data.table>. \"scenario\" column indicates intervention set distinct scenario, \"param_set\" column indicates parameter set used model run. parameters used scenario, allowing comparability scenarios aggregate level. output \\(M \\times N \\times S\\) rows (nested model outputs), \\(M\\) intervention sets, \\(N\\) vaccination regimes, \\(S\\) infection parameter sets.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"visualising-parameter-uncertainty-in-intervention-scenarios","dir":"Articles","previous_headings":"Modelling epidemic response scenarios with parameter uncertainty","what":"Visualising parameter uncertainty in intervention scenarios","title":"Modelling parameter uncertainty and epidemic scenarios","text":", show one way visualising epidemic size across scenarios, accounting parameter uncertainty. Figure 2: Infections averted relative epidemic response implementing scenario, accounting parameter uncertainty transmission rates.","code":"# select the data, the parameter set, and the scenario epidemic_size_estimates <- select(output, param_set, scenario, data) %>%   mutate(     size = map_dbl(       data, epidemic_size,       by_group = FALSE, include_deaths = FALSE     )   ) %>%   select(-data)  # Extract baseline and alternative scenarios df_scenario1 <- epidemic_size_estimates %>% filter(scenario == 1) df_scenarios_rest <- epidemic_size_estimates %>% filter(scenario != 1)  # Calculate differences as infections averted df_differences <- df_scenarios_rest %>%   left_join(df_scenario1, by = \"param_set\", suffix = c(\"_other\", \"_1\")) %>%   mutate(difference = size_1 - size_other) %>%   select(param_set, scenario = scenario_other, difference) # Plot distribution of differences ggplot(   df_differences,   aes(x = difference, y = factor(scenario), fill = factor(scenario)) ) +   stat_histinterval(     normalize = \"xy\", breaks = 11,     show.legend = FALSE   ) +   labs(     title = \"Scenario comparison\",     x = \"Infections averted\"   ) +   scale_x_continuous(     labels = scales::comma   ) +   scale_y_discrete(     name = NULL,     labels = labels[-1]   ) +   scale_fill_discrete_qualitative(     palette = \"Dynamic\"   ) +   theme_bw()"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_scenarios.html","id":"counter-intuitive-effects-of-time-limited-interventions","dir":"Articles","previous_headings":"","what":"Counter-intuitive effects of time-limited interventions","title":"Modelling parameter uncertainty and epidemic scenarios","text":"intervention scenarios modelled suggest : interventions disease transmission rates reduce infections hence epidemic final sizes; multiple interventions reduce epidemic final sizes single interventions. simple example show need always case, counter-intuitively, implementing interventions can lead larger epidemic final size implementing fewer interventions. phenomenon depends baseline transmission rate infection, select relatively low \\(R\\) 1.30 (corresponding pandemic influenza), higher \\(R\\) 1.58 \\(R\\) estimation step start vignette. Figure 3: Counter-intuitive effects time-limited interventions transmission rate high R values. Scenarios multiple interventions implemented may larger final epidemic size scenarios fewer interventions, e.g. ‘Close workplaces schools’ scenario. Plotting epidemic trajectories scenario value \\(R\\) gives fuller picture see unexpected effect. Figure 4: New daily infections intervention scenario two values R. period interventions active shown area shaded grey. interventions active ‘response’ scenario. Implementing interventions disease transmission rate leads ‘flattening curve’ (reduced daily incidence comparison response) interventions active. However, cases deferred rather prevented entirely, scenarios seen shifting incidence curve right (towards end simulation period). \\(R\\) low, incidence curve begins rise later \\(R\\) high (interventions applied epidemics actually miss projected peak epidemic, still shift cases right). Thus low \\(R\\) epidemics run course time simulation ends, making appear though interventions succeeded averting infections. higher \\(R\\), peak projected incidence curve without interventions falls within intervention period, thus interventions reduce new infections. scenarios multiple active interventions, large number susceptibles remain uninfected, compared scenarios fewer interventions. former thus see higher incidence peaks, leading counter-intuitively larger final epidemic sizes.","code":"# run each scenario for two values of R # no parameter uncertainty r_values <- c(1.3, round(r_estimate_mean, 2))  output <- model_default(   uk_population,   transmission_rate = r_values / 7,   intervention = intervention_scenarios,   time_end = 600 )  # obtain epidemic sizes epidemic_size_estimates <- mutate(   output,   size = map_dbl(     data, epidemic_size,     by_group = FALSE, include_deaths = FALSE   ),   r_value = rep(r_values, each = length(intervention_scenarios)),   scenario = rep(factor(labels, labels), 2) ) %>%   select(r_value, scenario, size) # plot the epidemic final size for each scenario for each R ggplot(epidemic_size_estimates) +   geom_col(     aes(scenario, size, fill = scenario),     show.legend = FALSE   ) +   scale_x_discrete(     name = NULL,     guide = guide_axis(n.dodge = 2)   ) +   scale_y_continuous(     labels = scales::comma,     name = \"Epidemic size\"   ) +   scale_fill_discrete_qualitative(     palette = \"Dynamic\"   ) +   facet_grid(     cols = vars(r_value),     labeller = labeller(       r_value = function(x) sprintf(\"R = %s\", x)     )   ) +   theme_bw() # get new infections per day daily_incidence <- mutate(   output,   r_value = rep(r_values, each = length(intervention_scenarios)),   scenario = rep(factor(labels, labels), 2),   incidence_data = map(data, new_infections, by_group = FALSE) ) %>%   select(scenario, r_value, incidence_data) %>%   unnest(incidence_data) ggplot(daily_incidence) +   annotate(     geom = \"rect\",     xmin = time_begin, xmax = time_end,     ymin = -Inf, ymax = Inf,     fill = \"grey90\", colour = \"grey\"   ) +   geom_line(     aes(time, new_infections, col = as.factor(r_value)),     show.legend = TRUE, linewidth = 1   ) +   scale_y_continuous(     labels = scales::label_comma(scale = 1e-3, suffix = \"K\")   ) +   scale_colour_discrete_qualitative(     palette = \"Dynamic\",     name = \"R\"   ) +   facet_wrap(facets = vars(scenario), nrow = 2) +   theme_bw() +   theme(legend.position = \"top\") +   labs(     x = \"Time since epidemic start\",     y = \"New infections\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"setup-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Setup and initial conditions","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"","code":"# set up initial conditions polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE ) contact_matrix <- t(contact_data$matrix) demography_vector <- contact_data$demography$population  # Prepare some initial objects uk_population <- population(   name = \"UK population\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = matrix(     c(1 - 1e-6, 0, 1e-6, 0, 0),     nrow = nrow(contact_matrix), ncol = 5L,     byrow = TRUE   ) )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"defining-a-time-dependent-function","dir":"Articles","previous_headings":"","what":"Defining a time-dependent function","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"Next prepare function affects transmission rate (often denoted \\(\\beta\\)) way two peaks two troughs transmission rate course year. Note example uses arbitrary function, might want choose realistic function model. Nonetheless, figures later show, can still generate realistic looking epidemic curves good starting point understanding feature works. can plot output function time examine effect \\(\\beta\\).","code":"# prepare function, refer to transmissiblity as beta in function name mod_beta <- function(time, x, tmax = 365 / 4) {   x + (x * sinpi(time / tmax)) } # get the function output # calculate beta - this is done automatically inside epidemic_*() output <- mod_beta(seq(0, 365), 1.3 / 7.0)  # plot the effect of time dependence ggplot() +   geom_line(     aes(x = seq(0, 365), y = output)   ) +   labs(x = \"Days\", y = \"Transmission rate (beta)\") +   theme_bw()"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"model-with-time-dependent-transmission","dir":"Articles","previous_headings":"","what":"Model with time-dependent transmission","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"Next run epidemic model including time dependence transmission rate. plot number newly infectious individuals check model dynamics. Note plotting code folded can expanded.  , can see epidemic large first wave, followed smaller second wave later model run (represents one year).","code":"# note transmission_rate is the function/model parameter # the function that affects it may have any name data <- model_default(   population = uk_population,   time_dependence = list(     transmission_rate = mod_beta   ),   time_end = 365, increment = 1 )  # get data on new infections data_infections <- new_infections(data) # plot data on new infections ggplot(data_infections) +   geom_line(     aes(x = time, y = new_infections, col = demography_group)   ) +   scale_y_continuous(     labels = scales::comma,     name = \"New infections\"   ) +   scale_color_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   theme_bw() +   coord_cartesian(     expand = FALSE   ) +   labs(     x = \"Time (days)\",     title = \"Effect of time-dependence of transmission rate\"   ) +   theme(     legend.position = \"top\",     plot.title = element_text(face = \"bold\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"non-pharmaceutical-interventions-and-time-dependence","dir":"Articles","previous_headings":"","what":"Non-pharmaceutical interventions and time-dependence","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"can also model effect imposing non-pharmaceutical interventions reduce social contacts, trajectory epidemic time-dependent changes transmission rate. example, impose intervention three phases: (1) closing schools, primarily affects age group 0 – 19, (2) closing workplaces, affects age groups > 20 years old, (3) partially reopening schools intervention lower effect social contacts age group 0 – 19. First construct intervention, object <contacts_intervention> class. run model specifying time-dependence transmission rate, well intervention social contacts. assign scenario names data, combine , plot comparison.  can observe implementing interventions social contacts can substantially reduce number infections age groups epidemic waves.","code":"# school closures affecting younger age groups close_schools <- intervention(   type = \"contacts\", time_begin = 50, time_end = 120,   reduction = c(0.1, 0.01, 0.01) )  # workplace closures affecting mostly adults close_workplaces <- intervention(   type = \"contacts\", time_begin = 65, time_end = 90,   reduction = c(0.01, 0.2, 0.2) )  # partially reopen schools partial_schools <- intervention(   type = \"contacts\", time_begin = 120, time_end = 180,   reduction = c(0.05, 0.01, 0.01) )  # combine interventions npis <- c(close_schools, close_workplaces, partial_schools)  # print to examine npis #>  #>  Intervention name:  #>  Begins at:  #>      npi_1 npi_2 npi_3 #> [1,]    50    65   120 #>  #>  Ends at:  #>      npi_1 npi_2 npi_3 #> [1,]   120    90   180 #>  #>  Reduction:  #>              Interv. 1 Interv. 2 Interv. 3 #> Demo. grp. 1      0.10      0.01      0.05 #> Demo. grp. 2      0.01      0.20      0.01 #> Demo. grp. 3      0.01      0.20      0.01 # run the model with interventions and time-dependence data_npi <- model_default(   population = uk_population,   intervention = list(contacts = npis),   time_dependence = list(     transmission_rate = mod_beta   ),   time_end = 365, increment = 1 )  # get the infections data_infections_npi <- new_infections(data_npi) data_infections$scenario <- \"baseline\" data_infections_npi$scenario <- \"intervention\"  # combine the data data_npi_compare <- bind_rows(data_infections, data_infections_npi) ggplot(data_npi_compare) +   geom_line(     aes(       x = time, y = new_infections,       col = demography_group, linetype = scenario     )   ) +   scale_y_continuous(     labels = scales::comma,     name = \"New infections\"   ) +   scale_color_brewer(     palette = \"Dark2\",     name = \"Age group\",     labels = c(\"Baseline\", \"Intervention\")   ) +   scale_linetype_manual(     name = \"Scenario\",     values = c(       baseline = \"dashed\",       intervention = \"solid\"     )   ) +   theme_bw() +   coord_cartesian(     expand = FALSE   ) +   labs(     x = \"Time (days)\",     title = \"Effect of multiple interventions on contacts\"   ) +   theme(     legend.position = \"top\",     plot.title = element_text(face = \"bold\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_time_dependence.html","id":"timing-vaccination-to-prevent-epidemic-peaks","dir":"Articles","previous_headings":"","what":"Timing vaccination to prevent epidemic peaks","title":"Modelling time-dependence and seasonality in transmission dynamics","text":"can model effect timing vaccination doses begin end first wave, 120 days. example include non-pharmaceutical interventions. First define vaccination regime targets adults aged 40 years priority group. age groups vaccinated campaign. also assume single dose vaccine confers immunity (.e., non-leaky vaccination). model effect administering vaccine doses expected peaks epidemic waves, plot outcome.  , can see 2 million individuals vaccinated (immunised; blue line, right-hand Y axis) 100 days end first wave infections, start second wave infections. Vaccination reduces number daily infections among individuals age groups second wave. peak, vaccination scenario sees approximately 5,000 fewer daily infections baseline scenario, may represent substantial benefit public health.","code":"# define vaccination object vax_regime <- vaccination(   nu = matrix(0.001, nrow = 3, ncol = 1),   time_begin = matrix(c(0, 0, 120)),   time_end = matrix(c(0, 0, 220)) )  # view the vaccination object vax_regime #>  #>  Vaccination name:  #>  Begins at:  #>      dose_1 #> [1,]      0 #> [2,]      0 #> [3,]    120 #>  #>  Ends at:  #>      dose_1 #> [1,]      0 #> [2,]      0 #> [3,]    220 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  0.001 #> [2,]  0.001 #> [3,]  0.001 # pass time dependence and vaccination. Note no interventions data_vax <- model_default(   population = uk_population,   vaccination = vax_regime,   time_dependence = list(     transmission_rate = mod_beta   ),   time_end = 365, increment = 1 )  # collect data and add scenario data_vax_infections <- new_infections(   data_vax,   compartments_from_susceptible = c(\"exposed\", \"vaccinated\") ) data_vax_infections$scenario <- \"vaccination\"  # combine data data_vax_compare <- bind_rows(data_infections, data_vax_infections) ggplot(data_vax_compare) +   geom_rect(     aes(       xmin = 120, xmax = 220,       ymin = 0, ymax = 20e3     ),     fill = \"grey\", alpha = 0.1   ) +   geom_line(     data = filter(       data_vax, compartment == \"vaccinated\", demography_group == \"40+\"     ),     aes(time, value / 1e2),     colour = \"darkblue\"   ) +   annotate(     geom = \"text\",     x = 190,     y = 10e3,     label = \"Vaccines administered (100 days)\",     angle = 90,     colour = \"darkblue\"   ) +   geom_line(     aes(       x = time, y = new_infections,       col = demography_group, linetype = scenario     )   ) +   scale_y_continuous(     labels = scales::comma,     name = \"New infections\",     sec.axis = dup_axis(       trans = function(x) x * 1e2,       name = \"Individuals vaccinated\",       labels = function(x) {         scales::comma(x, scale = 1e-6, suffix = \"M\")       }     )   ) +   scale_color_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   scale_linetype_manual(     name = \"Scenario\",     values = c(       baseline = \"dashed\",       vaccination = \"solid\"     )   ) +   theme_bw() +   coord_cartesian(     ylim = c(0, 20e3),     expand = FALSE   ) +   labs(     x = \"Time (days)\",     title = \"Effect of a vaccination regime\"   ) +   theme(     legend.position = \"top\",     plot.title = element_text(face = \"bold\")   )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"prepare-population-and-initial-conditions","dir":"Articles","previous_headings":"","what":"Prepare population and initial conditions","title":"Modelling the effect of a vaccination campaign","text":"Prepare population contact data. Prepare initial conditions age group. Prepare population population class object.","code":"# load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 65),   symmetric = TRUE ) #> Removing participants that have contacts without age information. To change this behaviour, set the 'missing.contact.age' option  # prepare contact matrix contact_matrix <- t(contact_data$matrix)  # prepare the demography vector demography_vector <- contact_data$demography$population names(demography_vector) <- rownames(contact_matrix) # initial conditions initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions )  # assign rownames for clarity rownames(initial_conditions) <- rownames(contact_matrix) uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"prepare-a-vaccination-campaign","dir":"Articles","previous_headings":"","what":"Prepare a vaccination campaign","title":"Modelling the effect of a vaccination campaign","text":"Prepare vaccination campaign targeting individuals aged 65.","code":"# prepare a vaccination object vaccinate_elders <- vaccination(   name = \"vaccinate elders\",   time_begin = matrix(100, nrow(contact_matrix)),   time_end = matrix(250, nrow(contact_matrix)),   nu = matrix(c(0.0001, 0, 0)) )  # view vaccination object vaccinate_elders #> <vaccination> object #>  #>  Vaccination name:  #> \"vaccinate elders\" #>  #>  Begins at:  #>      dose_1 #> [1,]    100 #> [2,]    100 #> [3,]    100 #>  #>  Ends at:  #>      dose_1 #> [1,]    250 #> [2,]    250 #> [3,]    250 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  1e-04 #> [2,]  0e+00 #> [3,]  0e+00"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"run-epidemic-model","dir":"Articles","previous_headings":"","what":"Run epidemic model","title":"Modelling the effect of a vaccination campaign","text":"","code":"# run an epidemic model using `epidemic` output <- model_default(   population = uk_population,   vaccination = vaccinate_elders,   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/articles/modelling_vaccination.html","id":"prepare-data-and-visualise-infections","dir":"Articles","previous_headings":"","what":"Prepare data and visualise infections","title":"Modelling the effect of a vaccination campaign","text":"Plot epidemic time, showing number individuals exposed, infected, vaccinated compartments.","code":"# plot figure of epidemic curve filter(output, compartment %in% c(\"exposed\", \"infectious\")) %>%   ggplot(     aes(       x = time,       y = value,       col = demography_group,       linetype = compartment     )   ) +   geom_line() +   scale_y_continuous(     labels = scales::comma   ) +   scale_colour_brewer(     palette = \"Dark2\",     name = \"Age group\"   ) +   expand_limits(     y = c(0, 500e3)   ) +   coord_cartesian(     expand = FALSE   ) +   theme_bw() +   theme(     legend.position = \"top\"   ) +   labs(     x = \"Simulation time (days)\",     linetype = \"Compartment\",     y = \"Individuals\"   )"},{"path":"https://epiverse-trace.github.io/epidemics/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Pratik Gupte. Author, maintainer, copyright holder. Rosalind Eggo. Author, copyright holder. Edwin Van Leeuwen. Author, copyright holder. Adam Kucharski. Contributor, reviewer. Tim Taylor. Contributor, reviewer. Banky Ahadzie. Contributor. Hugo Gruson. Reviewer. Joshua W. Lambert. Reviewer. James M. Azam. Reviewer.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Gupte P, Eggo R, Van Leeuwen E (2024). epidemics: Composable Epidemic Scenario Modelling. R package version 0.3.0,  https://epiverse-trace.github.io/epidemics/, https://github.com/epiverse-trace/epidemics.","code":"@Manual{,   title = {epidemics: Composable Epidemic Scenario Modelling},   author = {Pratik Gupte and Rosalind Eggo and Edwin {Van Leeuwen}},   year = {2024},   note = {R package version 0.3.0,  https://epiverse-trace.github.io/epidemics/},   url = {https://github.com/epiverse-trace/epidemics}, }"},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"epidemics-composable-epidemic-scenario-modelling-","dir":"","previous_headings":"","what":"Composable Epidemic Scenario Modelling","title":"Composable Epidemic Scenario Modelling","text":"epidemics R package provides modular representations populations public health response measures, allowing combined epidemiological model structures curated published literature, conveniently compose compare epidemic scenario models. models epidemics focus directly transmitted infections, implement methods outlined Bjørnstad et al. (2020a) Bjørnstad et al. (2020b). models epidemics can help provide rough estimates course epidemics, effectiveness pharmaceutical non-pharmaceutical interventions. epidemics relies Eigen via {RcppEigen}, Boost Odeint via {BH}, developed Centre Mathematical Modelling Infectious Diseases London School Hygiene Tropical Medicine part Epiverse-TRACE initiative.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Composable Epidemic Scenario Modelling","text":"current development version epidemics can installed GitHub using pak package.","code":"if(!require(\"pak\")) install.packages(\"pak\") pak::pkg_install(\"epiverse-trace/epidemics\")"},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"installation-notes","dir":"","previous_headings":"Installation","what":"Installation Notes","title":"Composable Epidemic Scenario Modelling","text":"users also using developing packages use Stan might face issues modified toolchain accommodate packages cmdstanr; see resolved issue starting point face similar problems. Users Windows systems need packages RTools family installed system path; see link guidance using RTools version R.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"quick-start","dir":"","previous_headings":"","what":"Quick start","title":"Composable Epidemic Scenario Modelling","text":"show example using default model epidemics model epidemic U.K. population R0 similar pandemic influenza, heterogeneity social contacts among different age groups, implementation school closures dampen spread infection. Prepare social contact pattern population (, U.K population), divided three age groups: 0 – 19, 20 – 39, 40+. Prepare initial conditions population age group — , one every million individuals infected start epidemic (total 60 infections). Prepare object class <population>, using function population(). Define intervention close schools two months. intervention mostly affects individuals age range 0 – 19, reduces contacts 50%, reducing contacts age groups 1%. object class <contacts_intervention>, created using function intervention(), setting type = \"contacts\". Run default epidemic model, using function model_default(). assume R0 1.5 similar pandemic influenza, infectious period 7 days, pre-infectious period 3 days. values can calculate transmission rate β 1.5 / 7.0, infectiousness_rate α 1.0 / 3.0 recovery_rate γ 1.0 / 7.0. Visualise development individuals “infectious” compartment model time. Note curves represent number individuals infectious, number newly infectious individuals.","code":"# load epidemics library(epidemics) library(ggplot2) library(dplyr) # load contact and population data from socialmixr::polymod polymod <- socialmixr::polymod contact_data <- socialmixr::contact_matrix(   polymod,   countries = \"United Kingdom\",   age.limits = c(0, 20, 40),   symmetric = TRUE )  # prepare contact matrix contact_matrix <- t(contact_data[[\"matrix\"]])  # prepare the demography vector demography_vector <- contact_data[[\"demography\"]][[\"population\"]] names(demography_vector) <- rownames(contact_matrix) # initial conditions: one in every 1 million is infected initial_i <- 1e-6 initial_conditions <- c(   S = 1 - initial_i, E = 0, I = initial_i, R = 0, V = 0 )  # build for all age groups initial_conditions <- rbind(   initial_conditions,   initial_conditions,   initial_conditions ) rownames(initial_conditions) <- rownames(contact_matrix) # prepare the population to model as affected by the epidemic uk_population <- population(   name = \"UK\",   contact_matrix = contact_matrix,   demography_vector = demography_vector,   initial_conditions = initial_conditions ) # an intervention to close schools close_schools <- intervention(   type = \"contacts\",   time_begin = 200,   time_end = 260,   reduction = matrix(c(0.5, 0.01, 0.01)) )  # view the intervention close_schools #>  #>  Intervention name:  #>  Begins at:  #> [1] 200 #>  #>  Ends at:  #> [1] 260 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.50 #> Demo. grp. 2      0.01 #> Demo. grp. 3      0.01 # run an epidemic model using `epidemic()` output <- model_default(   population = uk_population,   transmission_rate = 1.5 / 7.0,   infectiousness_rate = 1.0 / 3.0,   recovery_rate = 1.0 / 7.0,   intervention = list(contacts = close_schools),   time_end = 600, increment = 1.0 )"},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"package-vignettes","dir":"","previous_headings":"","what":"Package vignettes","title":"Composable Epidemic Scenario Modelling","text":"details use epidemics can found online documentation package vignettes, “Articles”.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"package-models","dir":"","previous_headings":"","what":"Package models","title":"Composable Epidemic Scenario Modelling","text":"epidemics provides convenient interface library compartmental models can help model epidemic scenarios directly transmitted respiratory infections influenza Covid-19 well haemorrhagic fevers Ebola virus disease: deterministic SEIR-V model susceptible, exposed, infectious, recovered, vaccinated compartments (SEIR-V), allowing heterogeneity social contacts, implementation group-specific non-pharmaceutical intervention reduces social contacts, vaccination regime group-specific start end dates; deterministic Vacamole model developed RIVM, Dutch Public Health Institute Covid-19 pandemic, focus scenario modelling hospitalisation vaccination (Ainslie et al. 2022); stochastic, discrete-time, compartmental SEIR model suitable modelling haemorrhagic fevers Ebola Virus Disease, including hospitalisation hospital funeral transmissions, adapted Li et al. (2019) Getz Dougherty (2018); initial implementation compartmental model diphtheria context internally displaced persons camps, including reporting rate, hospitalisation rate, delays entering leaving hospital, taken Finger et al. (2019). models planned added near future. Please get touch like see model added epidemics model library — happy help translating framework, special focus making model applicable LMIC settings.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"related-projects","dir":"","previous_headings":"","what":"Related projects","title":"Composable Epidemic Scenario Modelling","text":"epidemics aims library published epidemiological models, following projects may useful building models: R package finalsize also developed Epiverse-TRACE helps calculate final size epidemic heterogeneous population, quicker option estimates total infections temporal dynamics less important; Epirecipes project cookbook-style guide focuses different ways implement epidemic models R languages; R package odin generates systems ordinary differential equations (ODE) integrate , using domain specific language (DSL), widely used translate compartmental models R C code performance gains; Many R packages provide modelling options, can found CRAN Epidemiology Task View section “Infectious disease modelling”.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"help","dir":"","previous_headings":"","what":"Help","title":"Composable Epidemic Scenario Modelling","text":"report bug please open issue.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"contribute","dir":"","previous_headings":"","what":"Contribute","title":"Composable Epidemic Scenario Modelling","text":"Contributions epidemics welcomed via pull requests.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of conduct","title":"Composable Epidemic Scenario Modelling","text":"Please note epidemics project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a list to a intervention object — as.intervention","title":"Convert a list to a intervention object — as.intervention","text":"Convert list intervention object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a list to a intervention object — as.intervention","text":"","code":"as.intervention(x, type = c(\"contacts\", \"rate\"))"},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a list to a intervention object — as.intervention","text":"x list, object inherits list. type string type intervention: \"contacts\" <contact_intervention> \"rate\" <rate_intervention>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a list to a intervention object — as.intervention","text":"intervention class object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.intervention.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a list to a intervention object — as.intervention","text":"","code":"# prepare a list npi <- list(   name = \"npi\",   type = \"contacts\",   time_begin = 30,   time_end = 60,   reduction = rep(0.1, 3) )  as.intervention(npi) #> <contacts_intervention> object #>  #>  Intervention name:  #> \"npi\" #>  #>  Begins at:  #> [1] 30 #>  #>  Ends at:  #> [1] 60 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1       0.1 #> Demo. grp. 2       0.1 #> Demo. grp. 3       0.1"},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a list to a vaccination object — as.vaccination","title":"Convert a list to a vaccination object — as.vaccination","text":"Convert list vaccination object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a list to a vaccination object — as.vaccination","text":"","code":"as.vaccination(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a list to a vaccination object — as.vaccination","text":"x list, object inherits list.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a list to a vaccination object — as.vaccination","text":"vaccination class object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/as.vaccination.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a list to a vaccination object — as.vaccination","text":"","code":"# prepare a list vax <- list(   name = \"vax_regime\",   time_begin = matrix(1),   time_end = matrix(100),   nu = matrix(0.001) )  as.vaccination(vax) #> <vaccination> object #>  #>  Vaccination name:  #> \"vax_regime\" #>  #>  Begins at:  #>      dose_1 #> [1,]      1 #>  #>  Ends at:  #>      dose_1 #> [1,]    100 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  0.001"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert properties of a intervention object — assert_intervention","title":"Assert properties of a intervention object — assert_intervention","text":"Assert objects intervention class properties expected epidemic model. See intervention() specific model functions check intervention properties required model. function internal use argument checking functions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert properties of a intervention object — assert_intervention","text":"","code":"assert_intervention(x, type = c(\"contacts\", \"rate\"), population = NULL)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert properties of a intervention object — assert_intervention","text":"x intervention object. type string type intervention check . May one \"contacts\" \"rate\". population optional argument population object. present, used check whether intervention object x corresponding values reduction demographic group population.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assert properties of a intervention object — assert_intervention","text":"Silently returns <intervention>-superclass object x class x, .e., <rate_intervention> <contacts_intervention>. Primarily called side effects throwing errors x meet certain requirements.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert properties of a population object — assert_population","title":"Assert properties of a population object — assert_population","text":"Assert objects population class parameters expected epidemic model. See population() specific epidemic functions check population parameters required model. function internal use argument checking functions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert properties of a population object — assert_population","text":"","code":"assert_population(x, compartments, demography_vector = NULL)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert properties of a population object — assert_population","text":"x <population> object. compartments character vector giving names model compartments whose length taken reference number columns initial_conditions matrix x. demography_vector optional numeric vector whose length used check length demography vector present x.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assert properties of a population object — assert_population","text":"Silently returns <population> object x. Primarily called side effects throwing errors x meet certain requirements.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Assert properties of a vaccination object — assert_vaccination","title":"Assert properties of a vaccination object — assert_vaccination","text":"Assert objects vaccination class parameters expected epidemic model. See vaccination() specific epidemic functions check vaccination properties required model. function internal use argument checking functions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assert properties of a vaccination object — assert_vaccination","text":"","code":"assert_vaccination(x, doses, population = NULL)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assert properties of a vaccination object — assert_vaccination","text":"x vaccination object. doses number doses expected vaccination object. population optional argument <population> object. present, used check whether vaccination object x corresponding values demographic group population.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/assert_vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assert properties of a vaccination object — assert_vaccination","text":"Silently returns <vaccination> object x. Primarily called side effects throwing errors x meet certain requirements.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":null,"dir":"Reference","previous_headings":"","what":"Cross-check model elements — cross_checking_inputs","title":"Cross-check model elements — cross_checking_inputs","text":"Check model elements compatibility population epidemic model, returning compatible dummy values model elements applied, erroring appropriately model elements compatible population characteristics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cross-check model elements — cross_checking_inputs","text":"","code":".cross_check_intervention(x, population, allowed_targets)  .cross_check_vaccination(x, population, doses)  .cross_check_timedep(x, allowed_targets)  .cross_check_popchange(x, population)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cross-check model elements — cross_checking_inputs","text":"x Model input checked. expected value x depends function: .cross_check_intervention(): named list <intervention> objects; .cross_check_vaccination(): <vaccination> object; .cross_check_timedep(): named list functions two arguments, time x, typically returning x function time; .cross_check_popchange(): named list two elements, time values, describing times values number susceptibles changes epidemic model. population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). allowed_targets model components, infection parameters, model input x affects. doses expected number vaccination doses.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cross_checking_inputs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cross-check model elements — cross_checking_inputs","text":".cross_check_intervention() returns named list least elements \"contacts\" describing <contacts_intervention> population (among allowed targets), <rate_intervention> transmission rate parameter. present x, returned , substituted missing. interventions also returned. x NULL, dummy contact rate interventions returned list. .cross_check_vaccination() returns x checking suitable population, dummy vaccination regime doses number doses age group. .cross_check_timedep() returns x x NULL, otherwise returns dummy function operating transmission rate parameter default; see .no_time_dependence(); .cross_check_popchange() returns x checks population x NULL, otherwise returns dummy list population change; see .no_population_change().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"Calculate Cumulative Effect Interventions Social Contacts Scale Contact Matrix Active Interventions Social Contacts","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"","code":"cumulative_contacts_intervention(t, time_begin, time_end, reduction)  intervention_on_cm(t, cm, time_begin, time_end, cr)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"t current time. time_begin numeric vector start times interventions modelled. time_end numeric vector end times interventions modelled. Must length time_begin. reduction numeric matrix rows give effect interventions demographic group, columns give proportion reduction contacts. two interventions overlap, proportions added, maximum possible value 1.0 (.e., contacts). cm numeric matrix social contacts demographic groups.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_contacts_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the Cumulative Effect of Interventions on Social Contacts — cumulative_contacts_intervention","text":"cumulative_contacts_intervention() returns numeric vector proportion reduction contacts demographic group. intervention_on_cm() returns contact matrix cm scaled cumulative effect active interventions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":"Calculate Cumulative Effect Interventions Rate Parameters","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":"","code":".cumulative_rate_intervention(t, time_begin, time_end, reduction)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":"t current time. time_begin numeric vector start times interventions modelled. time_end numeric vector end times interventions modelled. Must length time_begin. reduction numeric vector element gives effect corresponding intervention model rate parameters. two interventions overlap, proportions added, maximum possible value 1.0 (.e., rate set zero).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the Cumulative Effect of Interventions on Rate Parameters — cumulative_rate_intervention","text":".cumulative_rate_intervention() returns number proportion reduction model rate parameter. intervention_on_cm() returns contact matrix cm scaled cumulative effect active interventions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-intervention_on_rates.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply interventions to rate parameters — .intervention_on_rates","title":"Apply interventions to rate parameters — .intervention_on_rates","text":"Apply interventions rate parameters","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-intervention_on_rates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply interventions to rate parameters — .intervention_on_rates","text":"","code":".intervention_on_rates(t, interventions, parameters)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-intervention_on_rates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply interventions to rate parameters — .intervention_on_rates","text":"t single number simulation time. interventions named list list-like objects least three members \"time_begin\", \"time_end\", \"reduction\". used calculate effect named parameters simulation. parameters named list numeric parameters affected interventions. represents model parameters, transmission rate, \\(\\beta\\), recovery rate, \\(\\gamma\\).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-intervention_on_rates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Apply interventions to rate parameters — .intervention_on_rates","text":"named list length parameters, names. parameters can used timestep ODE model.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":null,"dir":"Reference","previous_headings":"","what":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"compartmental model optional non-pharmaceutical intervention optional vaccination regime. function intended called internally model_default_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"","code":".model_default_cpp(   initial_state,   transmission_rate,   infectiousness_rate,   recovery_rate,   contact_matrix,   npi_time_begin,   npi_time_end,   npi_cr,   vax_time_begin,   vax_time_end,   vax_nu,   rate_interventions,   time_dependence,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"initial_state matrix initial state compartments. transmission_rate transmission rate \\(\\beta\\) unvaccinated partially vaccinated individuals infected disease. infectiousness_rate rate transition exposed infectious \\(\\alpha\\). recovery_rate recovery rate \\(\\gamma\\). contact_matrix population contact matrix. npi_time_begin start time non-pharmaceutical interventions . npi_time_end end time non-pharmaceutical interventions. npi_cr reduction contacts non-pharmaceutical interventions. vax_time_begin start time vaccination campaigns. vax_time_end end time vaccination campaigns. vax_nu vaccination rate vaccination campaigns. rate_interventions named list <rate_intervention> objects. time_dependence named list functions parameter time dependence. time_end end time simulation. increment time increment simulation.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run an age-structured SEIR-V epidemic ODE model using a Boost solver — .model_default_cpp","text":"two element list, first element list matrices whose elements correspond numbers individuals compartment specified initial conditions matrix (see population()). second list element vector timesteps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":null,"dir":"Reference","previous_headings":"","what":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"compartmental model diphtheria parameters help account case reporting rate, delays seeking hospitalisation, time spent hospitalised compartment. function intended called internally model_diphtheria_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"","code":".model_diphtheria_cpp(   initial_state,   transmission_rate,   infectiousness_rate,   recovery_rate,   reporting_rate,   prop_hosp,   hosp_entry_rate,   hosp_exit_rate,   rate_interventions,   time_dependence,   pop_change_times,   pop_change_values,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"initial_state matrix initial state compartments. transmission_rate transmission rate \\(\\beta\\). infectiousness_rate rate transition exposed infectious \\(\\alpha\\). recovery_rate recovery rate \\(\\gamma\\). reporting_rate recovery rate \\(\\r\\). prop_hosp proportion individuals hospitalised \\(\\eta\\). hosp_entry_rate rate individuals hospitalised, represented 1 / time hospitalisation \\(\\tau_1\\). hosp_exit_rate rate individuals discharged hospital, represented 1 / time discharge \\(\\tau_2\\). rate_interventions named list <rate_intervention> objects. time_dependence named list functions parameter time dependence. pop_change_times numeric vector times population susceptibles changes. pop_change_values Rcpp List numeric vectors giving value changes demographic group change population. time_end end time simulation. increment time increment simulation.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run an SEIHR ODE model for diphtheria using a Boost solver — .model_diphtheria_cpp","text":"two element list, first element list matrices whose elements correspond numbers individuals compartment specified initial conditions matrix. second list element vector timesteps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_ebola_internal.html","id":null,"dir":"Reference","previous_headings":"","what":"Internal code for the Ebola model — .model_ebola_internal","title":"Internal code for the Ebola model — .model_ebola_internal","text":"Internal code Ebola model","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_ebola_internal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Internal code for the Ebola model — .model_ebola_internal","text":"","code":".model_ebola_internal(   initial_state,   erlang_subcompartments,   transmission_rate,   infectiousness_rate,   removal_rate,   prop_community,   etu_risk,   funeral_risk,   intervention,   time_dependence,   time_end,   replicates,   local_seeds )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_ebola_internal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Internal code for the Ebola model — .model_ebola_internal","text":"erlang_subcompartments numeric, integer-like vector number Erlang sub-compartments assumed exposed, infectious, hospitalised compartments. Defaults 2. transmission_rate numeric vector rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. infectiousness_rate numeric vector rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. removal_rate numeric vector rate infectious individuals transition infectious hospitalised compartments funeral removed compartments. model distinguish recoveries deaths. Denoted Getz Dougherty \\(\\gamma^\\) (see Details). prop_community numeric vector proportion infectious individuals remain community hospitalised treatment. Defaults 0.9. etu_risk numeric vector relative risk onward transmission EVD hospitalised individuals, values 0.0 1.0, 0.0 indicates hospitalisation completely prevents onward transmission, 1.0 indicates hospitalisation prevent onward transmission ; values relative baseline transmission rate \\(\\beta\\). Defaults 0.7. funeral_risk numeric vector relative risk onward transmission EVD funerals individuals died EVD. Must 0.0 1.0, 0.0 indicates onward transmission, 1.0 indicates funeral transmission equivalent baseline transmission rate community \\(\\beta\\). Defaults 0.5. intervention optional named list <rate_intervention> objects representing optional pharmaceutical non-pharmaceutical interventions applied model parameters listed . May also list lists, case set interventions treated separate scenario. See Details . time_dependence optional named list element function first two arguments current simulation time, x, value dependent time (x represents model parameter). List names must correspond model parameters modified function. Alternatively, may list lists, case set functions treated distinct scenario. See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). time_end numeric, integer-like vector maximum number replicates single number replicates run. Defaults 100. timesteps run model, days. Defaults 100 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_ebola_internal.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Internal code for the Ebola model — .model_ebola_internal","text":"NOTE arguments internal function must scalars infection parameters single intervention time-dependence sets composable elements.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":null,"dir":"Reference","previous_headings":"","what":"Run the RIVM Vacamole model — .model_vacamole_cpp","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"Vacamole deterministic, compartmental epidemic model built Kylie Ainslie others RIVM, Dutch Public Health Institute Covid-19 pandemic, focus scenario modelling hospitalisation vaccination. Model code: https://github.com/kylieainslie/vacamole Manuscript describing model application: https://doi.org/10.2807/1560-7917.ES.2022.27.44.2101090 function intended called internally model_vacamole_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"","code":".model_vacamole_cpp(   initial_state,   transmission_rate,   transmission_rate_vax,   infectiousness_rate,   mortality_rate,   mortality_rate_vax,   hospitalisation_rate,   hospitalisation_rate_vax,   recovery_rate,   contact_matrix,   npi_time_begin,   npi_time_end,   npi_cr,   vax_time_begin,   vax_time_end,   vax_nu,   rate_interventions,   time_dependence,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"initial_state matrix initial state compartments. transmission_rate transmission rate \\(\\beta\\) unvaccinated partially vaccinated individuals infected disease. transmission_rate_vax transmission rate \\(\\beta_V\\) individuals received two vaccine doses infected disease. infectiousness_rate rate transition exposed infectious \\(\\alpha\\). common fully susceptible, partially vaccinated, fully vaccinated individuals (fully vaccinated represents two doses). mortality_rate mortality rate fully susceptible partially vaccinated unprotected individuals. mortality_rate_vax mortality rate individuals protected vaccination. hospitalisation_rate hospitalisation rate fully susceptible partially vaccinated unprotected individuals. hospitalisation_rate_vax hospitalisation rate individuals protected vaccination. recovery_rate recovery rate \\(\\gamma\\). contact_matrix population contact matrix. npi_time_begin start time non-pharmaceutical interventions . npi_time_end end time non-pharmaceutical interventions. npi_cr reduction contacts non-pharmaceutical interventions. vax_time_begin start time vaccination campaigns. vax_time_end end time vaccination campaigns. vax_nu vaccination rate vaccination campaigns. rate_interventions named list <rate_intervention> objects. time_dependence named list functions parameter time dependence. time_end end time simulation. increment time increment simulation.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run the RIVM Vacamole model — .model_vacamole_cpp","text":"two element list, first element list matrices whose elements correspond numbers individuals compartment specified initial conditions matrix (see population()). second list element vector timesteps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":null,"dir":"Reference","previous_headings":"","what":"Ordinary Differential Equations for the Default Model — .ode_model_default","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"Provides ODEs default SEIR-V model format suitable passing deSolve::lsoda(). See model_default() list required parameters.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"","code":".ode_model_default(t, y, params)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"t single number timestep integrate. y conditions epidemiological compartments. params parameters, passed named list.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_default.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ordinary Differential Equations for the Default Model — .ode_model_default","text":"list vector many elements number demographic groups times number epidemiological compartments. value gives change number individuals compartment.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":null,"dir":"Reference","previous_headings":"","what":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"Provides ODEs RIVM Vacamole model format suitable passing deSolve::lsoda(). See model_vacamole() list required parameters.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"","code":".ode_model_vacamole(t, y, params)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"t single number timestep integrate. y conditions epidemiological compartments. params parameters, passed named list.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ordinary Differential Equations for the Vacamole Model — .ode_model_vacamole","text":"list vector many elements number demographic groups times number epidemiological compartments. value gives change number individuals compartment.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare a <population> for an epidemic model — .prepare_population","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"Prepare <population> epidemic model","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"","code":".prepare_population(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"x <population>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare a <population> for an epidemic model — .prepare_population","text":"named list \"contact_matrix\", population social contacts matrix scaled largest real eigenvalue demography vector, \"initial_state\", proportional initial state multiplied demography vector.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the epidemic size — epidemic_size","title":"Get the epidemic size — epidemic_size","text":"Get size epidemic stage start end. calculated number individuals recovered infection stage epidemic.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the epidemic size — epidemic_size","text":"","code":"epidemic_size(   data,   stage = 1,   time = NULL,   by_group = TRUE,   include_deaths = FALSE,   simplify = TRUE )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the epidemic size — epidemic_size","text":"data table model output, typically output model_de  ault() similar functions. stage numeric vector stage epidemic return epidemic size; 0.0 represents start time epidemic .e., initial conditions epidemic simulation, 1.0 represents end epidemic simulation model (100% model time). Defaults 1.0, stage returned values represent final size epidemic. value overridden values passed time argument. time Alternative stage, integer-like vector timepoint epidemic return epidemic size. Overrides values passed stage. by_group logical representing whether epidemic size returned demographic group, whether single population-wide value returned. Defaults TRUE. include_deaths logical value indicates whether count dead individuals epidemic size calculation. Defaults FALSE. Setting include_deaths = TRUE makes function look \"dead\" compartment data. column, function returns final number recovered removed individuals demographic group. simplify logical determining whether epidemic size data simplified vector one element demographic group. length stage time $>$ 1, argument overridden data returned <data.table>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the epidemic size — epidemic_size","text":"simplify == TRUE single timepoint requested, returns vector epidemic sizes length number demographic groups. by_group == FALSE, sums epidemic size return overall value full population. multiple timepoints requested, multiple replicates present specially named column \"replicate\" (Ebola model), simplification vector possible; returns <data.table> timepoints epidemic sizes timepoint. options return absolute sizes proportions.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get the epidemic size — epidemic_size","text":"function can used calculate final size epidemic, setting stage = 1.0 (100% model time; default). function allows calculation epidemic sizes demographic group well total epidemic size.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemic_size.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the epidemic size — epidemic_size","text":"","code":"# create a population uk_population <- population(   name = \"UK population\",   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0, 0),     nrow = 1, ncol = 5L   ) )  # run epidemic simulation with no vaccination or intervention data <- model_default(   population = uk_population )  # get the final epidemic size if no other arguments are specified epidemic_size(data) #> [1] 481200.2  # get the epidemic size at the halfway point epidemic_size(data, stage = 0.5) #> [1] 81921.88  # alternatively, get the epidemic size at `time = 50` epidemic_size(data, time = 50) #> epidemic_size(): `time` provided will override any `stage` provided #> [1] 81921.88"},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemics-package.html","id":null,"dir":"Reference","previous_headings":"","what":"epidemics: Composable Epidemic Scenario Modelling — epidemics-package","title":"epidemics: Composable Epidemic Scenario Modelling — epidemics-package","text":"library compartmental epidemic models taken published literature, classes represent affected populations, public health response measures including non-pharmaceutical interventions social contacts, non-pharmaceutical pharmaceutical interventions affect disease transmissibility, vaccination regimes, disease seasonality, can combined compose epidemic scenario models.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/reference/epidemics-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"epidemics: Composable Epidemic Scenario Modelling — epidemics-package","text":"Maintainer: Pratik Gupte pratik.gupte@lshtm.ac.uk (ORCID) [copyright holder] Authors: Rosalind Eggo rosalind.eggo@lshtm.ac.uk (ORCID) [copyright holder] Edwin Van Leeuwen edwin.vanleeuwen@ukhsa.gov.uk (ORCID) [copyright holder] contributors: Adam Kucharski adam.kucharski@lshtm.ac.uk (ORCID) [contributor, reviewer] Tim Taylor tim.taylor@hiddenelephants.co.uk (ORCID) [contributor, reviewer] Banky Ahadzie bahadzie@gmail.com [contributor] Hugo Gruson hugo.gruson@data.org (ORCID) [reviewer] Joshua W. Lambert joshua.lambert@lshtm.ac.uk (ORCID) [reviewer] James M. Azam james.azam@lshtm.ac.uk (ORCID) [reviewer]","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Create an intervention for an epidemic model — intervention","title":"Create an intervention for an epidemic model — intervention","text":"Prepare object <intervention> super-class specifies modification model parameters. <contacts_intervention> used simulate non-pharmaceutical intervention (NPI) regime reduces population's social contacts. <rate_intervention> used simulate reduction model's rate parameters (transmission rate \\(\\beta\\)), can used represent pharmaceutical interventions improved treatment, also NPIs wearing masks. Interventions single start end time applies demographic groups population, can groups-specific effects reduction contacts. Combine <intervention>-inheriting objects create sequential overlapping intervention regimes using c() two <intervention>-inheriting objects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create an intervention for an epidemic model — intervention","text":"","code":"intervention(name = NA_character_, type, time_begin, time_end, reduction)  is_intervention(x)  is_contacts_intervention(x)  is_rate_intervention(x)  # S3 method for class 'contacts_intervention' c(x, ...)  # S3 method for class 'rate_intervention' c(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create an intervention for an epidemic model — intervention","text":"name String name intervention. type String type intervention. May one \"contacts\" \"rate\", <contacts_intervention> <rate_intervention> respectively. time_begin Single number start time intervention. time_end Single number end time intervention. reduction <contacts_intervention>s, matrix many rows number demographic groups type population, single column. element gives group-specific proportion reduction contacts. <rate_intervention>s, single number giving proportion reduction model parameter contacts. See details c() can used combine interventions sub-class. x <intervention> object, object checked <intervention> object. ... intervention objects combine x create multi-dose <intervention> object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create an intervention for an epidemic model — intervention","text":"object <intervention> S3 super-class, possible sub-classes <contact_intervention> <rate_intervention>. Concatenating two <intervention>-inheriting objects using c() also returns <intervention>-inheriting object sub-class. object holds intervention-specific start end times, reductions specified constituent intervention actions (demographic group intervention contacts). combined effect actions population handled internally epidemic model functions. \"null\" intervention generated using .no_contacts_intervention(population) .no_rate_intervention() returns <intervention> appropriate sub-class start end times, effect set 0.0. is_intervention(), is_contacts_intervention(), is_rate_intervention() return logical value whether object <intervention>, <contacts_intervention>, <rate_intervention> class, respectively.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create an intervention for an epidemic model — intervention","text":"Epidemic models can accommodate interventions contacts able accommodate number interventions different start end times different group-specific effects. Epidemic models can accommodate interventions rates also able accommodate number interventions different start end times, uniform effect relevant rate. multiple contact interventions combined using c(), reduction contacts stacked column wise form matrix \\([, j]\\). multiple rate interventions combined using c(), reduction rate concatenated vector length number interventions. Models model_default_cpp() set treat interventions overlapping periods (.e., overlap time active ) additive effect contact rate reductions. contact reductions, group-specific effect \\(J\\) overlapping interventions thus vector \\(\\sum_{j = 1}^J x_{ij}\\), demographic group \\(\\). handled internally epidemic model code. example, contact reduction matrix two perfectly overlapping interventions (\\(J = 2\\)) different effects across three demographic groups (\\(= 3\\)) represented : \\(\\begin{bmatrix}0.1 & 0.05\\\\0.1 & 0.1\\\\0.1 & 0.0\\end{bmatrix}\\) epidemic models, cumulative group-specific effect interventions active \\((0.15, 0.2, 0.1)\\). rate reductions, effect overlapping interventions reduce particular rate also considered additive.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create an intervention for an epidemic model — intervention","text":"","code":"# assuming a population with two age groups, 0 -- 18, and 18+ # an example in which schools are closed for 30 days (or other time units) close_schools <- intervention(   name = \"close schools\",   type = \"contacts\",   time_begin = 50,   time_end = 80,   reduction = matrix(c(0.5, 0.01)) # reduces contacts differentially ) close_schools #> <contacts_intervention> object #>  #>  Intervention name:  #> \"close schools\" #>  #>  Begins at:  #> [1] 50 #>  #>  Ends at:  #> [1] 80 #>  #>  Reduction:  #>              Interv. 1 #> Demo. grp. 1      0.50 #> Demo. grp. 2      0.01  # Check for intervention class is_contacts_intervention(close_schools) #> [1] TRUE  # Concatenating interventions # create first intervention npi_1 <- intervention(   type = \"contacts\",   time_begin = 30,   time_end = 60,   reduction = matrix(0.1) )  # second intervention npi_2 <- intervention(   type = \"contacts\",   time_begin = 45,   time_end = 75,   reduction = matrix(0.1) )  c(npi_1, npi_2) #> <contacts_intervention> object #>  #>  Intervention name:  #> NA #>  #>  Begins at:  #>      npi_1 npi_2 #> [1,]    30    45 #>  #>  Ends at:  #>      npi_1 npi_2 #> [1,]    60    75 #>  #>  Reduction:  #>              Interv. 1 Interv. 2 #> Demo. grp. 1       0.1       0.1"},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":null,"dir":"Reference","previous_headings":"","what":"Constructor for the  super-class and sub-classes — intervention_constructor","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"Constructor  super-class sub-classes Constructor new <contacts_intervention> Constructor new <rate_intervention>","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"","code":"new_intervention(   name = NA_character_,   time_begin,   time_end,   reduction,   ...,   class )  new_contacts_intervention(name, time_begin, time_end, reduction)  new_rate_intervention(name, time_begin, time_end, reduction)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"name String name intervention. time_begin matrix single element giving start time intervention. time_end matrix single element giving end time intervention. reduction matrix single column many rows demographic groups targeted intervention. See intervention() details types intervention can created requirements type reduction. ... parameters passed constructor. class string giving type intervention; used generate intervention sub-classes.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Constructor for the  super-class and sub-classes — intervention_constructor","text":"new_intervention() returns object inherits <intervention> class. new_contacts_intervention() returns object sub-class <intervention> called <contacts_intervention>. new_rate_intervention() returns object sub-class <intervention> called <rate_intervention>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":null,"dir":"Reference","previous_headings":"","what":"Model an SEIR-V epidemic with interventions — model_default","title":"Model an SEIR-V epidemic with interventions — model_default","text":"Simulate epidemic using deterministic, compartmental epidemic model compartments \"susceptible\", \"exposed\", \"infectious\", \"recovered\", \"vaccinated\". model can accommodate heterogeneity social contacts among demographic groups, well differences sizes demographic groups. population, transmission_rate, infectiousness_rate, recovery_rate arguments mandatory, passing intervention vaccination optional can used simulate scenarios different epidemic responses different levels type response. See Details information.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model an SEIR-V epidemic with interventions — model_default","text":"","code":"model_default(   population,   transmission_rate = 1.3/7,   infectiousness_rate = 1/2,   recovery_rate = 1/7,   intervention = NULL,   vaccination = NULL,   time_dependence = NULL,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model an SEIR-V epidemic with interventions — model_default","text":"population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). transmission_rate numeric rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. infectiousness_rate numeric rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. recovery_rate numeric rate individuals move infectious recovered compartment. Often denoted \\(\\gamma\\), \\(\\gamma = 1.0 / \\text{infectious period}\\). See Details default values. intervention named list <intervention>s representing optional non-pharmaceutical pharmaceutical interventions applied epidemic. single intervention social contacts class <contacts_intervention> allowed named element \"contacts\". Multiple <rate_interventions> model parameters allowed; see Details model parameters interventions supported. vaccination <vaccination> object representing optional vaccination regime single dose, followed course epidemic, start end time, age-specific vaccination rates. time_dependence named list name model parameter, element function first two arguments current simulation time, x, value dependent time (x represents model parameter). See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). time_end maximum number timesteps run model. Taken days, default value 100 days. May numeric vector. increment size time increment. Taken days, default value 1 day.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model an SEIR-V epidemic with interventions — model_default","text":"<data.table>. model parameters composable elements scalars, single <data.table> columns \"time\", \"compartment\", \"age_group\", \"value\", giving number individuals per demographic group compartment timestep long (\"tidy\") format returned. model parameters composable elements lists list-like, nested <data.table> returned list column \"data\", holds compartmental values described . columns hold parameters composable elements relating model run. Columns \"scenario\" \"param_set\" identify combinations composable elements (population, interventions, vaccination regimes), infection parameters, respectively.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model an SEIR-V epidemic with interventions — model_default","text":"model allows single, population-wide rates transitions compartments per model run. However, model parameters may passed numeric vectors. vectors must follow Tidyverse recycling rules: vectors must length, , vectors length 1 recycled length vector. default values : Transmission rate (\\(\\beta\\), transmission_rate): 0.186, assuming \\(R_0\\) = 1.3 infectious period 7 days. Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.5, assuming pre-infectious period 2 days. Recovery rate (\\(\\gamma\\), recovery_rate): 0.143, assuming infectious period 7 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_default.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model an SEIR-V epidemic with interventions — model_default","text":"","code":"# create a population uk_population <- population(   name = \"UK population\",   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0, 0),     nrow = 1, ncol = 5L   ) )  # run epidemic simulation with no vaccination or intervention # and three discrete values of transmission rate data <- model_default(   population = uk_population,   transmission_rate = c(1.3, 1.4, 1.5) / 7.0, # uncertainty in R0 )  # view some data data #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571      100         1 #> 2:         0.2000000                 0.5     0.1428571      100         2 #> 3:         0.2142857                 0.5     0.1428571      100         3 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #>                   data #>                 <list> #> 1: <data.table[505x4]> #> 2: <data.table[505x4]> #> 3: <data.table[505x4]>  # run epidemic simulations with differences in the end time # may be useful when considering different start dates with a fixed end point data <- model_default(   population = uk_population,   time_end = c(50, 100, 150) )  data #>    transmission_rate infectiousness_rate recovery_rate time_end param_set #>                <num>               <num>         <num>    <num>     <int> #> 1:         0.1857143                 0.5     0.1428571       50         1 #> 2:         0.1857143                 0.5     0.1428571      100         2 #> 3:         0.1857143                 0.5     0.1428571      150         3 #>         population intervention vaccination time_dependence increment scenario #>             <list>       <list>      <list>          <list>     <num>    <int> #> 1: <population[4]>                                <list[1]>         1        1 #> 2: <population[4]>                                <list[1]>         1        1 #> 3: <population[4]>                                <list[1]>         1        1 #>                   data #>                 <list> #> 1: <data.table[255x4]> #> 2: <data.table[505x4]> #> 3: <data.table[755x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":null,"dir":"Reference","previous_headings":"","what":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"Simulate diphtheria outbreak using deterministic, compartmental ordinary differential equation model compartments \"susceptible\", \"exposed\", \"infectious\", \"hospitalised\", \"recovered\". model based Finger et al. (2019) intended used context internally displaced people (IDP) refugee camps. model allows proportion demographic group vaccinated start outbreak, thus contribute outbreak. model also allows changes number susceptibles age group model influxes evacuations camps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"","code":"model_diphtheria(   population,   transmission_rate = 4/4.5,   infectiousness_rate = 1/3,   recovery_rate = 1/3,   reporting_rate = 0.03,   prop_hosp = 0.01,   hosp_entry_rate = 0.2,   hosp_exit_rate = 0.2,   prop_vaccinated = 0 * population[[\"demography_vector\"]],   intervention = NULL,   time_dependence = NULL,   population_change = NULL,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). transmission_rate numeric rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. infectiousness_rate numeric rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. recovery_rate numeric rate individuals move infectious recovered compartment. Often denoted \\(\\gamma\\), \\(\\gamma = 1.0 / \\text{infectious period}\\). See Details default values. reporting_rate numeric proportion infectious cases reported; precursor hospitalisation reported cases hospitalised. prop_hosp numeric proportion reported cases hospitalised. hosp_entry_rate numeric rate reported cases infectious individuals hospitalised. calculated 1 / time hospitalisation, denoted \\(\\tau_1\\). hosp_exit_rate numeric rate individuals discharged hospital enter 'recovered' compartment. calculated 1 / time discharge, denoted \\(\\tau_2\\). prop_vaccinated numeric vector length number demographic groups indicated proportion group vaccinated. individuals included model dynamics. intervention named list <rate_intervention> objects representing optional pharmaceutical non-pharmaceutical interventions applied model parameters listed . time_dependence named list name model parameter, element function first two arguments current simulation time, x, value dependent time (x represents model parameter). See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). population_change two-element list, elements named \"time\" \"values\", giving times population changes, corresponding changes population demographic group times. \"time\" must numeric vector, \"values\" must list length \"time\", element numeric vector length number demographic groups population. time_end maximum number timesteps run model. Taken days, default value 100 days. May numeric vector. increment size time increment. Taken days, default value 1 day.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"data.table columns \"time\", \"compartment\", \"age_group\", \"value\", \"run\", giving number individuals per demographic group compartment timestep long (\"tidy\") format, \"run\" indicating unique parameter combination.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"details-model-an-infection-outbreak-in-a-humanitarian-camp-setting","dir":"Reference","previous_headings":"","what":"Details: Model an infection outbreak in a humanitarian camp setting","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"model developed diphtheria outbreaks settings interventions social contacts difficult implement. suitable application outbreak similar, directly transmitted infectious diseases well.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"model allows single, population-wide rates transitions compartments per model run. However, model parameters may passed numeric vectors. vectors must follow Tidyverse recycling rules: vectors must length, , vectors length 1 recycled length vector. default values taken Finger et al. (2019) possible: Transmission rate (\\(\\beta\\), transmission_rate): 0.8888889, assuming \\(R_0\\) 4.0 total infectious period 4.5 days. Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.333, assuming pre-infectious period 3 days. Reporting rate (\\(r\\), reporting_rate): 0.03, assuming 3% infectious cases detected reported. Proportion hospitalised (\\(\\eta\\), prop_hosp): 0.01, assuming 1% reported cases need hospital treatment. Hospital entry rate (\\(\\tau_1\\), hosp_entry_rate): 0.2, assuming takes 5 days infectious individuals seek hospital treatment. Hospital exit rate (\\(\\tau_2\\), hosp_exit_rate): 0.2, assuming individuals discharged hospital 5 days. Recovery rate (\\(\\gamma\\), recovery_rate): 0.333, assuming infectious period following symptoms, 3 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"modelling-population-changes","dir":"Reference","previous_headings":"","what":"Modelling population changes","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"model allows changes number susceptibles demographic group, represent influxes evacuations camp expected humanitarian relief situations. Users can specify times changes (demographic group) changes using population_changes argument, examine effect outbreak dynamics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"Finger, F., Funk, S., White, K., Siddiqui, M. R., Edmunds, W. J., & Kucharski, . J. (2019). Real-time analysis diphtheria outbreak forcibly displaced Myanmar nationals Bangladesh. BMC Medicine, 17, 58. doi:10.1186/s12916-019-1288-7 .","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_diphtheria.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model a diphtheria outbreak using a compartmental ODE model — model_diphtheria","text":"","code":"# create a dummy camp population with three age groups # diphtheria model is SEIHR # assume that most are susceptible, some infectious # values taken from supplementary material in Finger et al. for the # Kutupalong camp, rounded to the nearest 100 n_age_groups <- 3 demography_vector <- c(83000, 108200, 224600) initial_conditions <- matrix(0, nrow = n_age_groups, ncol = 5)  # set susceptibles and infectious initial_conditions[, 1] <- demography_vector - 1 initial_conditions[, 3] <- rep(1, n_age_groups)  camp_pop <- population(   contact_matrix = matrix(1, nrow = n_age_groups, ncol = n_age_groups),   demography_vector = demography_vector,   initial_conditions = initial_conditions / demography_vector )  # assume younger age groups are vaccinated prop_vaccinated <- c(0.2, 0.10, 0.1)  # run model for single, default parameter set data <- model_diphtheria(   camp_pop,   prop_vaccinated = prop_vaccinated ) head(data) #>     time demography_group compartment    value #>    <num>           <char>      <char>    <num> #> 1:     0     demo_group_1 susceptible  66399.2 #> 2:     0     demo_group_2 susceptible  97379.1 #> 3:     0     demo_group_3 susceptible 202139.1 #> 4:     0     demo_group_1     exposed      0.0 #> 5:     0     demo_group_2     exposed      0.0 #> 6:     0     demo_group_3     exposed      0.0 tail(data) #>     time demography_group  compartment        value #>    <num>           <char>       <char>        <num> #> 1:   100     demo_group_1 hospitalised 2.596196e-02 #> 2:   100     demo_group_2 hospitalised 3.807505e-02 #> 3:   100     demo_group_3 hospitalised 7.903602e-02 #> 4:   100     demo_group_1    recovered 6.052999e+04 #> 5:   100     demo_group_2    recovered 8.877102e+04 #> 6:   100     demo_group_3    recovered 1.842694e+05  # run model with increase in population # create population change data p <- list(   time = 70,   values = list(     c(1e4, 2e5, 1e5)   ) )  data <- model_diphtheria(   camp_pop,   prop_vaccinated = prop_vaccinated,   population_change = p ) head(data) #>     time demography_group compartment    value #>    <num>           <char>      <char>    <num> #> 1:     0     demo_group_1 susceptible  66399.2 #> 2:     0     demo_group_2 susceptible  97379.1 #> 3:     0     demo_group_3 susceptible 202139.1 #> 4:     0     demo_group_1     exposed      0.0 #> 5:     0     demo_group_2     exposed      0.0 #> 6:     0     demo_group_3     exposed      0.0 tail(data) #>     time demography_group  compartment        value #>    <num>           <char>       <char>        <num> #> 1:   100     demo_group_1 hospitalised 2.457804e-01 #> 2:   100     demo_group_2 hospitalised 2.881630e+00 #> 3:   100     demo_group_3 hospitalised 1.694441e+00 #> 4:   100     demo_group_1    recovered 6.598005e+04 #> 5:   100     demo_group_2    recovered 1.704198e+05 #> 6:   100     demo_group_3    recovered 2.285045e+05"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":null,"dir":"Reference","previous_headings":"","what":"Model an Ebola virus disease epidemic — model_ebola","title":"Model an Ebola virus disease epidemic — model_ebola","text":"Simulate epidemic using discrete-time, stochastic SEIR compartmental model compartments based Li et al. (2019), Erlang passage times based model developed Getz Dougherty (2017), developed model West African Ebola virus disease (EVD) outbreak 2013 -- 2016. See Details information. model_ebola_cpp() Rcpp implementation model currently lags behind R implementation, likely removed.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model an Ebola virus disease epidemic — model_ebola","text":"","code":"model_ebola(   population,   transmission_rate = 1.5/12,   erlang_subcompartments = 2,   infectiousness_rate = erlang_subcompartments/5,   removal_rate = erlang_subcompartments/12,   prop_community = 0.9,   etu_risk = 0.7,   funeral_risk = 0.5,   intervention = NULL,   time_dependence = NULL,   time_end = 100,   replicates = 100 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model an Ebola virus disease epidemic — model_ebola","text":"population object <population> class, see population(). model accepts <population> without demographic structure, , demography_vector must single number representing total size affected population. model also account demographic differences social contacts, means contact_matrix ignored. consistency, matrix must square many rows demography groups, one. transmission_rate numeric vector rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. erlang_subcompartments numeric, integer-like vector number Erlang sub-compartments assumed exposed, infectious, hospitalised compartments. Defaults 2. infectiousness_rate numeric vector rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. removal_rate numeric vector rate infectious individuals transition infectious hospitalised compartments funeral removed compartments. model distinguish recoveries deaths. Denoted Getz Dougherty \\(\\gamma^\\) (see Details). prop_community numeric vector proportion infectious individuals remain community hospitalised treatment. Defaults 0.9. etu_risk numeric vector relative risk onward transmission EVD hospitalised individuals, values 0.0 1.0, 0.0 indicates hospitalisation completely prevents onward transmission, 1.0 indicates hospitalisation prevent onward transmission ; values relative baseline transmission rate \\(\\beta\\). Defaults 0.7. funeral_risk numeric vector relative risk onward transmission EVD funerals individuals died EVD. Must 0.0 1.0, 0.0 indicates onward transmission, 1.0 indicates funeral transmission equivalent baseline transmission rate community \\(\\beta\\). Defaults 0.5. intervention optional named list <rate_intervention> objects representing optional pharmaceutical non-pharmaceutical interventions applied model parameters listed . May also list lists, case set interventions treated separate scenario. See Details . time_dependence optional named list element function first two arguments current simulation time, x, value dependent time (x represents model parameter). List names must correspond model parameters modified function. Alternatively, may list lists, case set functions treated distinct scenario. See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). time_end numeric, integer-like vector maximum number replicates single number replicates run. Defaults 100. timesteps run model, days. Defaults 100 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model an Ebola virus disease epidemic — model_ebola","text":"<data.table>. model parameters composable elements scalars, single <data.table> columns \"time\", \"compartment\", \"age_group\", \"value\", giving number individuals per demographic group compartment timestep long (\"tidy\") format returned. model parameters composable elements lists list-like, nested <data.table> returned list column \"data\", holds compartmental values described . columns hold parameters composable elements relating model run. Columns \"scenario\" \"param_set\" identify combinations composable elements (population, interventions, vaccination regimes), infection parameters, respectively.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"details-discrete-time-ebola-virus-disease-model","dir":"Reference","previous_headings":"","what":"Details: Discrete-time Ebola virus disease model","title":"Model an Ebola virus disease epidemic — model_ebola","text":"model compartments adopted consensus model Ebola virus disease presented Li et al. (2019), transitions epidemiological compartments modelled using Erlang sub-compartments adapted Getz Dougherty (2018); see References. R code model adapted code Ha Minh Lam initially made available Epirecipes (https://github.com/epirecipes/epicookbook) MIT license. shape Erlang distributions passage times exposed infectious compartments (\\(k^E\\) \\(k^\\)) recommended set 2 sensible choice, default value erlang_sbubcompartments argument, can allowed vary (independently). transition rates exposed infectious, infectious funeral compartments (also hospitalised removed), \\(\\gamma^E\\) \\(\\gamma^\\) Getz Dougherty's notation, passed user infectiousness_rate removal_rate respectively. Getz Dougherty's equation (6) gives relationship parameters mean pre-infectious \\(\\rho^E\\) infectious \\(\\rho^\\) periods. $$\\gamma^E = \\dfrac{k^E}{\\rho^E} = \\dfrac{2}{\\rho^E} ~\\text{}~ \\gamma^= \\dfrac{k^}{\\rho^} = \\dfrac{2}{\\rho^}$$ discrete time model, \\(\\gamma^E\\) \\(\\gamma^\\) used determine passage times newly exposed infectious individuals respective compartments (thus allowing variation passage times).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"hospitalisation-funerals-and-removal","dir":"Reference","previous_headings":"","what":"Hospitalisation, funerals, and removal","title":"Model an Ebola virus disease epidemic — model_ebola","text":"proportion, 1.0 - prop_community, infectious individuals transferred hospitalised compartment timestep, compartment represents Ebola Treatment Units (ETUs), individuals hospitalised compartment considered infectious longer community. passage time individuals hospitalised compartment similar individuals infectious compartment (.e., infectious community), means infectious individual \\(N\\) timesteps exiting infectious compartment exit hospitalised compartment time. Hospitalised individuals can contribute transmission Ebola susceptibles depending value etu_risk scales baseline transmission rate \\(\\beta\\) hospitalised individuals. assume deaths hospital lead Ebola-safe funerals, individuals exiting hospitalised compartment move 'removed' compartment, holds recoveries deaths. assume deaths outside hospital lead funerals potentially unsafe burials, funeral_risk argument scales baseline transmission rate \\(\\beta\\) funeral transmission Ebola susceptibles. Individuals assumed spend single timestep funeral transmission compartment, move 'removed' compartment. Individuals 'removed' compartment affect model dynamics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model an Ebola virus disease epidemic — model_ebola","text":"default values : Transmission rate (\\(\\beta\\), transmission_rate): 0.125, resulting \\(R_0\\) = 1.5 infectious period 12 days. Infectiousness rate (\\(\\gamma^E\\), infectiousness_rate): 0.4, assuming pre-infectious period 5 days two Erlang subcompartments. Removal rate (\\(\\gamma^\\), recovery_rate): 0.1667, assuming infectious period 12 days two Erlang subcompartments.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"implementing-vaccination","dir":"Reference","previous_headings":"","what":"Implementing vaccination","title":"Model an Ebola virus disease epidemic — model_ebola","text":"Vaccination currently implemented model \"vaccinated\" epidemiological compartment. prevents use <vaccination> object. Instead, users can use time_dependence argument pass function modifies model parameters --- specifically, transmission rate --- way consistent effect vaccination. example shown vignette model; run code open vignette: vignette(\"ebola_model\", package = \"epidemics\")","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"vector-parameter-inputs","dir":"Reference","previous_headings":"","what":"Vector parameter inputs","title":"Model an Ebola virus disease epidemic — model_ebola","text":"model infection parameters model duration may passed numeric integer-like vectors (appropriate parameter), simulate effect parameter uncertainty. parameter vectors must length, one parameter vector may length > 1 length 1. first case, -th combination parameters treated parameter set. second case, single value parameters (scalars) recycled length non-scalar parameter. model run $N$ stochastic realisations parameter set. Random number seeds preserved across parameter sets, differences outcomes j-th run due differences parameters alone.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"vector-inputs-for-composable-elements","dir":"Reference","previous_headings":"","what":"Vector inputs for composable elements","title":"Model an Ebola virus disease epidemic — model_ebola","text":"intervention time_dependence arguments also accept vectorised inputs form lists intervention time dependence sets. combination intervention time-dependence sets treated distinct 'scenario', realisations parameter set run scenario.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Model an Ebola virus disease epidemic — model_ebola","text":"Li, S.-L., Ferrari, M. J., Bjørnstad, O. N., Runge, M. C., Fonnesbeck, C. J., Tildesley, M. J., Pannell, D., & Shea, K. (2019). Concurrent assessment epidemiological operational uncertainties optimal outbreak control: Ebola case study. Proceedings Royal Society B: Biological Sciences, 286(1905), 20190774. doi:10.1098/rspb.2019.0774 Getz, W. M., & Dougherty, E. R. (2018). Discrete stochastic analogs Erlang epidemic models. Journal Biological Dynamics, 12(1), 16–38. doi:10.1080/17513758.2017.1401677","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_ebola.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model an Ebola virus disease epidemic — model_ebola","text":"","code":"# create a population with 6 compartments population <- population(   contact_matrix = matrix(1),   demography_vector = 14e6,   initial_conditions = matrix(     c(0.999998, 0.000001, 0.000001, 0, 0, 0),     nrow = 1, ncol = 6L   ) )  # run epidemic simulation with no vaccination or intervention data <- model_ebola(   population = population )  # view some data head(data) #>     time demography_group  compartment    value replicate #>    <int>           <char>       <char>    <num>     <int> #> 1:     0     demo_group_1  susceptible 13999972         1 #> 2:     0     demo_group_1      exposed       14         1 #> 3:     0     demo_group_1   infectious       14         1 #> 4:     0     demo_group_1 hospitalised        0         1 #> 5:     0     demo_group_1      funeral        0         1 #> 6:     0     demo_group_1      removed        0         1"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":null,"dir":"Reference","previous_headings":"","what":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"Simulate epidemic using Vacamole model Covid-19 developed RIVM, National Institute Public Health Environment Netherlands. model aimed estimating impact 'leaky' vaccination epidemic. See Details References information.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"","code":"model_vacamole(   population,   transmission_rate = 1.3/7,   transmission_rate_vax = 0.8 * transmission_rate,   infectiousness_rate = 1/2,   hospitalisation_rate = 1/1000,   hospitalisation_rate_vax = 0.8 * hospitalisation_rate,   mortality_rate = 1/1000,   mortality_rate_vax = 0.8 * mortality_rate,   recovery_rate = 1/7,   intervention = NULL,   vaccination = NULL,   time_dependence = NULL,   time_end = 100,   increment = 1 )"},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"population object population class, holds population contact matrix, demography vector, initial conditions demographic group. See population(). transmission_rate numeric rate individuals move susceptible exposed compartment upon contact infectious individual. Often denoted \\(\\beta\\), \\(\\beta = R_0 / \\text{infectious period}\\). See Details default values. transmission_rate_vax numeric values 0.0 1.0 giving transmission_rate infection individuals received two doses vaccine. default values 80% transmission_rate infection individuals doubly vaccinated. infectiousness_rate numeric rate individuals move exposed infectious compartment. Often denoted \\(\\sigma\\), \\(\\sigma = 1.0 / \\text{pre-infectious period}\\). value depend upon number infectious individuals population. See Details default values. hospitalisation_rate numeric hospitalisation rate infectious individuals. hospitalisation_rate_vax numeric values 0.0 1.0 giving hospitalisation rate infectious individuals received two doses vaccine. default value 80% hospitalisation rate individuals doubly vaccinated. mortality_rate numeric mortality rate infectious hospitalised individuals. mortality_rate_vax numeric values 0.0 1.0 giving mortality infectious hospitalised individuals received two doses vaccine. default value 80% mortality rate individuals doubly vaccinated. recovery_rate numeric rate individuals move infectious recovered compartment. Often denoted \\(\\gamma\\), \\(\\gamma = 1.0 / \\text{infectious period}\\). See Details default values. intervention named list <intervention>s representing optional non-pharmaceutical pharmaceutical interventions applied epidemic. single intervention social contacts class <contacts_intervention> allowed named element \"contacts\". Multiple <rate_interventions> model parameters allowed; see Details model parameters interventions supported. vaccination optional <vaccination> object representing vaccination regime two doses followed course epidemic, start end time, age-specific vaccination rates dose. See vaccination(). time_dependence named list name model parameter, element function first two arguments current simulation time, x, value dependent time (x represents model parameter). See Details information, well vignette time- dependence vignette(\"time_dependence\", package = \"epidemics\"). time_end maximum number timesteps run model. Taken days, default value 100 days. May numeric vector. increment size time increment. Taken days, default value 1 day.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"<data.table>. model parameters composable elements scalars, single <data.table> columns \"time\", \"compartment\", \"age_group\", \"value\", giving number individuals per demographic group compartment timestep long (\"tidy\") format returned. model parameters composable elements lists list-like, nested <data.table> returned list column \"data\", holds compartmental values described . columns hold parameters composable elements relating model run. Columns \"scenario\" \"param_set\" identify combinations composable elements (population, interventions, vaccination regimes), infection parameters, respectively.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"details-vacamole-covid-model-with-leaky-two-dose-vaccination","dir":"Reference","previous_headings":"","what":"Details: Vacamole Covid-19 model with leaky, two-dose vaccination","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"Vacamole model compartments \"susceptible\", \"vaccinated_one_dose\", \"vaccinated_two_dose\", \"exposed\", \"infectious\" \"infectious_vaccinated\", \"hospitalised\", \"hospitalised_vaccinated\", \"recovered\",  \"dead\". model allows : 'hospitalised' compartment along hospitalisation rate; Two doses vaccination, 'leaky' protection, .e., vaccination prevent infection completely allows reduction infection rate, well reduced rates moving states considered serious, 'hospitalised' 'dead'.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"model-parameters","dir":"Reference","previous_headings":"","what":"Model parameters","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"model allows single, population-wide rates transitions compartments per model run. However, model parameters may passed numeric vectors. vectors must follow Tidyverse recycling rules: vectors must length, , vectors length 1 recycled length vector. Transmission rate (\\(\\beta\\), transmission_rate): 0.186, resulting \\(R_0\\) = 1.3 infectious period 7 days. transmission rate doubly vaccinated individuals (\\(\\beta_v\\)) 80% \\(\\beta\\), 0.1488. Infectiousness rate (\\(\\sigma\\), infectiousness_rate): 0.5, assuming pre-infectious period 2 days. Hospitalisation rate (\\(\\eta\\), hospitalistion_rate): 1.0 / 1000, assuming one every thousand infectious individuals hospitalised. hospitalisation rate doubly vaccinated individuals (\\(\\eta_v\\)) 80% \\(\\eta\\), 0.8 / 1000. Mortality rate (\\(\\omega\\), mortality_rate): 1.0 / 1000, assuming one every thousand infectious hospitalised individuals dies. mortality rate doubly vaccinated (\\(\\omega_v\\)) 80% \\(\\omega\\), 0.8 / 1000. Recovery rate (\\(\\gamma\\), recovery_rate): 0.143, assuming infectious period 7 days.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"Ainslie, K. E. C., Backer, J. ., Boer, P. T. de, Hoek, . J. van, Klinkenberg, D., Altes, H. K., Leung, K. Y., Melker, H. de, Miura, F., & Wallinga, J. (2022). scenario modelling analysis anticipate impact COVID-19 vaccination adolescents children disease outcomes Netherlands, summer 2021. Eurosurveillance, 27(44), 2101090. doi:10.2807/1560-7917.ES.2022.27.44.2101090","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/model_vacamole.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Model leaky, two-dose vaccination in an epidemic using Vacamole — model_vacamole","text":"","code":"# create a population, note eleven columns for compartments population <- population(   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0, 0, 0, 0, 0.0001, 0, 0, 0, 0, 0),     nrow = 1, ncol = 11L   ) )  # create a vaccination regime double_vax <- vaccination(   nu = matrix(1e-3, ncol = 2, nrow = 1),   time_begin = matrix(c(10, 30), nrow = 1),   time_end = matrix(c(50, 80), nrow = 1) )  # run epidemic simulation with vaccination but no intervention # with a single set of parameters data <- model_vacamole(   population = population,   vaccination = double_vax )  # view some data head(data) #>     time demography_group         compartment    value #>    <num>           <char>              <char>    <num> #> 1:     0     demo_group_1         susceptible 66993300 #> 2:     0     demo_group_1 vaccinated_one_dose        0 #> 3:     0     demo_group_1 vaccinated_two_dose        0 #> 4:     0     demo_group_1             exposed        0 #> 5:     0     demo_group_1  exposed_vaccinated        0 #> 6:     0     demo_group_1          infectious     6700  # run epidemic simulation with no vaccination or intervention # and three discrete values of transmission_rate data <- model_vacamole(   population = population,   transmission_rate = c(1.3, 1.4, 1.5) / 7.0, # uncertainty in R0 )  # view some data head(data) #>    transmission_rate infectiousness_rate hospitalisation_rate mortality_rate #>                <num>               <num>                <num>          <num> #> 1:         0.1857143                 0.5                0.001          0.001 #> 2:         0.2000000                 0.5                0.001          0.001 #> 3:         0.2142857                 0.5                0.001          0.001 #>    recovery_rate transmission_rate_vax hospitalisation_rate_vax #>            <num>                 <num>                    <num> #> 1:     0.1428571             0.1485714                    8e-04 #> 2:     0.1428571             0.1600000                    8e-04 #> 3:     0.1428571             0.1714286                    8e-04 #>    mortality_rate_vax time_end param_set      population intervention #>                 <num>    <num>     <int>          <list>       <list> #> 1:              8e-04      100         1 <population[4]>              #> 2:              8e-04      100         2 <population[4]>              #> 3:              8e-04      100         3 <population[4]>              #>    vaccination time_dependence increment scenario                 data #>         <list>          <list>     <num>    <int>               <list> #> 1:                   <list[1]>         1        1 <data.table[1111x4]> #> 2:                   <list[1]>         1        1 <data.table[1111x4]> #> 3:                   <list[1]>         1        1 <data.table[1111x4]> tail(data) #>    transmission_rate infectiousness_rate hospitalisation_rate mortality_rate #>                <num>               <num>                <num>          <num> #> 1:         0.1857143                 0.5                0.001          0.001 #> 2:         0.2000000                 0.5                0.001          0.001 #> 3:         0.2142857                 0.5                0.001          0.001 #>    recovery_rate transmission_rate_vax hospitalisation_rate_vax #>            <num>                 <num>                    <num> #> 1:     0.1428571             0.1485714                    8e-04 #> 2:     0.1428571             0.1600000                    8e-04 #> 3:     0.1428571             0.1714286                    8e-04 #>    mortality_rate_vax time_end param_set      population intervention #>                 <num>    <num>     <int>          <list>       <list> #> 1:              8e-04      100         1 <population[4]>              #> 2:              8e-04      100         2 <population[4]>              #> 3:              8e-04      100         3 <population[4]>              #>    vaccination time_dependence increment scenario                 data #>         <list>          <list>     <num>    <int>               <list> #> 1:                   <list[1]>         1        1 <data.table[1111x4]> #> 2:                   <list[1]>         1        1 <data.table[1111x4]> #> 3:                   <list[1]>         1        1 <data.table[1111x4]>"},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":null,"dir":"Reference","previous_headings":"","what":"Get new infections over model time — new_infections","title":"Get new infections over model time — new_infections","text":"Get new infections model time","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get new infections over model time — new_infections","text":"","code":"new_infections(data, compartments_from_susceptible = NULL, by_group = TRUE)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get new infections over model time — new_infections","text":"data table model output, typically output model_default() similar functions. compartments_from_susceptible optional argument, character vector names model compartments individuals transition \"susceptible\" compartment, related infection. common example compartment \"vaccinated\" individuals longer susceptible, also counted infected. by_group logical representing whether epidemic size returned demographic group, whether single population-wide value returned.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get new infections over model time — new_infections","text":"table columns data, additional variable compartment, \"new_infections\", resulting additional rows.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/new_infections.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get new infections over model time — new_infections","text":"","code":"# create a population uk_population <- population(   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0, 0),     nrow = 1, ncol = 5L   ) )   # run epidemic simulation with no vaccination or intervention data <- model_default(   population = uk_population,   time_end = 200,   increment = 1 )  new_infections(data) #> Key: <time, demography_group> #>       time demography_group new_infections #>      <num>           <char>          <num> #>   1:     0     demo_group_1         0.0000 #>   2:     1     demo_group_1       255.6554 #>   3:     2     demo_group_1       597.4504 #>   4:     3     demo_group_1       786.9596 #>   5:     4     demo_group_1       899.2263 #>  ---                                       #> 197:   196     demo_group_1    194151.2197 #> 198:   197     demo_group_1    196154.0970 #> 199:   198     demo_group_1    198089.5442 #> 200:   199     demo_group_1    199954.3897 #> 201:   200     demo_group_1    201745.5414"},{"path":"https://epiverse-trace.github.io/epidemics/reference/output_to_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Return ODE model output as a data.table — output_to_df","title":"Return ODE model output as a data.table — output_to_df","text":"Return ODE model output data.table Return Ebola model output table","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/output_to_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return ODE model output as a data.table — output_to_df","text":"","code":".output_to_df(output, population, compartments)  .output_to_df_ebola(output, population, compartments)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/output_to_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return ODE model output as a data.table — output_to_df","text":"output model output, must two element list (epidemic) models, names \"x\" \"time\", \"x\" represents condition compartment timestep \"time\". population <population> object corresponding population used epidemic model. <population> object used generate names demographic groups, named. compartments vector model compartment names.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/output_to_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return ODE model output as a data.table — output_to_df","text":"<data.table> columns \"compartment\", \"demography_group\", \"value\", \"time\"; specify epidemiological compartment, name demography group, number individuals group compartment, model timestep, respectively. Names demographic groups generated names provided population object; form \"demo_group_X\".","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct a new population for an epidemic model — population","title":"Construct a new population for an epidemic model — population","text":"Construct new population epidemic model Check whether object <population>","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct a new population for an epidemic model — population","text":"","code":"population(   name = NA_character_,   contact_matrix,   demography_vector,   initial_conditions )  is_population(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct a new population for an epidemic model — population","text":"name Optional string population name. contact_matrix matrix giving contacts demographic groups population. Must square matrix. demography_vector vector sizes demographic group. Must length dimensions contact matrix. initial_conditions Matrix representing initial proportions demographic group four model compartments: 'susceptible', 'infected/infectious', 'recovered', 'vaccinated'. Must many rows number demographic groups. compartment represented columns matrix, element \\(M_{ij}\\) represents proportion individuals demographic group \\(\\) compartment \\(j\\) . x object checked valid population.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct a new population for an epidemic model — population","text":"object <population> S3 class. is_population() returns logical whether object <population>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/population.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct a new population for an epidemic model — population","text":"","code":"uk_pop <- population(   name = \"UK population\",   contact_matrix = matrix(1),   demography_vector = 67e6,   initial_conditions = matrix(     c(0.9999, 0.0001, 0, 0),     nrow = 1, ncol = 4   ) )  # print to check uk_pop #> <population> object #>  #>  Population name:  #> \"UK population\" #>  #>  Demography  #> Dem. grp. 1: 67,000,000 (100%) #>  #>  Contact matrix  #>              Dem. grp. 1: #> Dem. grp. 1:            1  # check for class <population> is_population(uk_pop) #> [1] TRUE"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare arguments to default model function — prepare_default_args","title":"Prepare arguments to default model function — prepare_default_args","text":"Prepare arguments model_default() .model_default_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare arguments to default model function — prepare_default_args","text":"","code":".check_prepare_args_default(mod_args)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare arguments to default model function — prepare_default_args","text":"mod_args named list population, epidemic modifiers.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare arguments to default model function — prepare_default_args","text":"list model arguments suitable .model_default_cpp(). named list consisting : initial_state: initial conditions modified represent absolute rather proportional values; transmission_rate, infectiousness_rate, recovery_rate: three numbers representing transmission rate infection, rate transition exposed infectious, recovery rate, respectively; contact_matrix, numeric matrix population contact matrix scaled largest real eigenvalue size groups; npi_time_begin, npi_time_end: two vectors start end times interventions applied; npi_cr: matrix age- intervention-specific effect social contacts; vax_time_begin,vax_time_end, vax_nu: three numeric matrices age- dose-specific start times, end times, rates vaccination doses implemented; time_end, increment: two numbers time end simulation, value simulation time incremented.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_default_args.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Prepare arguments to default model function — prepare_default_args","text":".check_prepare_args_default() prepares arguments .model_default_cpp(), C++ function solves default ODE system using Boost odeint solver, converting arguments collected mod_args simpler structures lists numeric integer vectors can interpreted C++ types Rcpp::List, Rcpp::NumericVector, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"Prepare arguments model_diphtheria() .model_diphtheria_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"","code":".check_prepare_args_diphtheria(mod_args)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"mod_args named list population, epidemic modifiers.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":"list model arguments suitable .model_diphtheria_cpp(). named list consisting : initial_state: initial conditions modified represent absolute rather proportional values; transmission_rate, transmission_rate_vax: two numbers representing transmission rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; infectiousness_rate: single number transition rate 'exposed' 'exposed_vaccinated' 'infectious' 'infectious_vaccinated' compartments; recovery_rate: single number recovery rate infection; reporting_rate: single number proportion infectious cases reported; prop_hosp: single number proportion reported cases need hospitalisation; hosp_entry_rate, hosp_exit_rate: two numbers representing rate entry exit 'hospitalised' compartment; rate_interventions: Rcpp List giving interventions model parameters; time_dependence: Rcpp List giving time-dependent effects model parameters form R functions; pop_change_times pop_change_values: times values changes population susceptibles; time_end, increment: two numbers time end simulation, value simulation time incremented.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Prepare arguments to diphtheria model function — prepare_diphtheria_args","text":".check_prepare_args_diphtheria() prepares arguments .model_diphtheria_cpp(), C++ function solves ODE system using Boost odeint solver, converting arguments collected mod_args simpler structures lists numeric integer vectors can interpreted C++ types Rcpp::List, Rcpp::NumericVector, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_ebola_args.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare arguments to ebola model function — prepare_ebola_args","title":"Prepare arguments to ebola model function — prepare_ebola_args","text":"Prepare arguments model_ebola() .model_ebola_internal().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_ebola_args.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare arguments to ebola model function — prepare_ebola_args","text":"","code":".check_prepare_args_ebola(mod_args)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_ebola_args.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prepare arguments to ebola model function — prepare_ebola_args","text":"mod_args named list composable elements; must include <population>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_ebola_args.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare arguments to ebola model function — prepare_ebola_args","text":"list model arguments suitable .model_ebola_internal(), elements mod_args suitable Ebola model. model composable elements suitable, side-effect throwing errors user. elements mod_args NULL, returns dummy placeholder values elements. returned list prepared model arguments named list consisting : \"initial_state\": initial conditions simulation, number individuals compartment. age stratification allowed. \"intervention\": either list <rate_intervention> objects, dummy <rate_intervention> interventions specified user. \"time_dependence\": time-dependence composable element passed user. Input checks element occur higher level model function.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_ebola_args.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Prepare arguments to ebola model function — prepare_ebola_args","text":".check_prepare_args_ebola() prepares arguments .model_ebola_internal(), converting arguments collected mod_args simpler structures appropriate internal model function.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":null,"dir":"Reference","previous_headings":"","what":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":"Prepare arguments model_vacamole() .model_vacamole_cpp().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":"","code":".check_prepare_args_vacamole(mod_args)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":"list model arguments suitable .model_vacamole_cpp(). named list consisting : initial_state: initial conditions modified represent absolute rather proportional values; transmission_rate, transmission_rate_vax: two numbers representing transmission rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; infectiousness_rate: single number transition rate 'exposed' 'exposed_vaccinated' 'infectious' 'infectious_vaccinated' compartments; mortality_rate, mortality_rate_vax: two numbers representing mortality rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; hospitalisation_rate, hospitalisation_rate_vax: two numbers representing hospitalisation rate infection unvaccinated single-dose vaccinated, two-dose vaccinated individuals, respectively; recovery_rate: single number recovery rate infection; contact_matrix, numeric matrix population contact matrix scaled largest real eigenvalue size groups; npi_time_begin, npi_time_end: two vectors start end times interventions applied; npi_cr: matrix age- intervention-specific effect social contacts; vax_time_begin,vax_time_end, vax_nu: three numeric matrices age- dose-specific start times, end times, rates vaccination doses implemented; time_end, increment: two numbers time end simulation, value simulation time incremented.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Prepare arguments to Vacamole epidemic function — prepare_vacamole_args","text":".check_prepare_args_vacamole() prepares arguments .model_vacamole_cpp(), C++ function solves Vacamole ODE system using Boost odeint solver, converting arguments collected mod_args simpler structures lists numeric integer vectors can interpreted C++ types Rcpp::List, Rcpp::NumericVector, Eigen::MatrixXd.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":null,"dir":"Reference","previous_headings":"","what":"Print a <population> object — print.population","title":"Print a <population> object — print.population","text":"Print <population> object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print a <population> object — print.population","text":"","code":"# S3 method for class 'population' print(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print a <population> object — print.population","text":"x <population> object. ... parameters passed print().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.population.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print a <population> object — print.population","text":"Invisibly returns <population> object x. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Print a <vaccination> object — print.vaccination","title":"Print a <vaccination> object — print.vaccination","text":"Print <vaccination> object","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print a <vaccination> object — print.vaccination","text":"","code":"# S3 method for class 'vaccination' print(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print a <vaccination> object — print.vaccination","text":"x <vaccination> object. ... parameters passed print().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print.vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print a <vaccination> object — print.vaccination","text":"Invisibly returns <vaccination> object x. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Print an object of the <intervention> super-class — print_intervention","title":"Print an object of the <intervention> super-class — print_intervention","text":"Print object <intervention> super-class Print objects <contact_intervention> class Print objects <rate_intervention> class","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print an object of the <intervention> super-class — print_intervention","text":"","code":"# S3 method for class 'intervention' print(x, ...)  # S3 method for class 'contact_intervention' print(x, ...)  # S3 method for class 'rate_intervention' print(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print an object of the <intervention> super-class — print_intervention","text":"x object inherits <intervention> class. print.contacts_intervention(), object <contacts_intervention> class. print.rate_intervention(), object <rate_intervention> class. ... parameters passed print().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/print_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print an object of the <intervention> super-class — print_intervention","text":"Invisibly returns object x. Called printing side-effects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":null,"dir":"Reference","previous_headings":"","what":"Construct a new vaccination regime for an epidemic model — vaccination","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"Prepare <vaccination> object specifies vaccination regime use epidemic model. objects can handle different vaccination start end times, well different vaccination rates, demographic group epidemic modelling scenario. Combine <vaccination> objects create multi-dose vaccination regimes using c() two <vaccination> objects.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"","code":"vaccination(name = NA_character_, nu, time_begin, time_end)  is_vaccination(x)  # S3 method for class 'vaccination' c(x, ...)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"name String name vaccination regime. nu Matrix group-specific rate vaccination, expressed rate parameter \\(nu\\). element matrix \\(nu_{ij}\\) represents rate delivering vaccine dose \\(j\\) demographic group \\(\\). time_begin Matrix start time delivering vaccination dose \\(j\\) demographic group \\(\\). demographic group \\(\\). time_end Matrix end time delivering vaccination dose \\(j\\) demographic group \\(\\). x <vaccination> object, object checked <vaccination>. ... Vaccination objects combine x create multi-dose <vaccination> object.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"object <vaccination> S3 class. vaccination() returns <vaccination> object specified parameters. Concatenating two <vaccination> objects using c() also returns <vaccination> object. object holds group-specific start end times, group-specific vaccination rates specified constituent vaccination regimes. .no_vaccination() returns <vaccination> effect population, start end times set 0.0, rate vaccination \\(nu\\) also set 0.0. is_vaccination() return logical whether object <vaccination> class.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"Multi-dose vaccinations can passed epidemic models, models accommodate multi-dose vaccinations. example, default SEIR-V model provided model_default() single vaccinated compartment, use first parameter set multi-dose regime determine individuals transition vaccinated compartment. contrast, Vacamole model considers two doses, make use first two parameter sets multi-dose regime. doses can specified, disregarded model.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vaccination.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construct a new vaccination regime for an epidemic model — vaccination","text":"","code":"# Assuming a population with two age groups, children 0 -- 5, and others 5+ # an example for childhood vaccination only childhood_vaccination <- vaccination(   name = \"childhood_vaccination\",   time_begin = matrix(c(0, 100)), # assuming a simulation over 100 days   time_end = matrix(c(100, 100)),   nu = matrix(c(0.0001, 0.0)) # over 5s never vaccinated ) #> Vaccination: some `time_end`s are not greater than `time_begin`s #> Vaccination: some `time_end`s are not greater than `time_begin`s childhood_vaccination #> Vaccination: some `time_end`s are not greater than `time_begin`s #> <vaccination> object #>  #>  Vaccination name:  #> \"childhood_vaccination\" #>  #>  Begins at:  #>      dose_1 #> [1,]      0 #> [2,]    100 #>  #>  Ends at:  #>      dose_1 #> [1,]    100 #> [2,]    100 #>  #>  Vaccination rate:  #>      dose_1 #> [1,]  1e-04 #> [2,]  0e+00  # check whether the object is a <vaccination> is_vaccination(childhood_vaccination) #> [1] TRUE  # Concatenating vaccinations # create first dose regime vax_1 <- vaccination(   name = \"vax_regime\",   time_begin = matrix(1),   time_end = matrix(100),   nu = matrix(0.001) )  # second dose regime vax_2 <- vaccination(   name = \"vax_regime\",   time_begin = matrix(101),   time_end = matrix(200),   nu = matrix(0.001) )  c(vax_1, vax_2) #> <vaccination> object #>  #>  Vaccination name:  #> \"vax_regime\" #>  #>  Begins at:  #>      dose_1 dose_2 #> [1,]      1    101 #>  #>  Ends at:  #>      dose_1 dose_2 #> [1,]    100    200 #>  #>  Vaccination rate:  #>      dose_1 dose_2 #> [1,]  0.001  0.001"},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":null,"dir":"Reference","previous_headings":"","what":"Validate objects that inherit from the  class — validate_intervention","title":"Validate objects that inherit from the  class — validate_intervention","text":"Validate objects inherit  class Validate objects inherit  class","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validate objects that inherit from the  class — validate_intervention","text":"","code":"validate_contacts_intervention(x)  validate_rate_intervention(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validate objects that inherit from the  class — validate_intervention","text":"x validate_contacts_intervention(), object validated <contacts_intervention>. validate_rate_intervention(), object validated <rate_intervention>.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/validate_intervention.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Validate objects that inherit from the  class — validate_intervention","text":"Invisibly returns input x. Called primarily input checking validator objects <intervention> superclass.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":null,"dir":"Reference","previous_headings":"","what":"Vector recyclability checks and vector recycling — vector_recycling","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"Internal functions check whether vectors can recycled recycle vectors.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"","code":".test_recyclable(x)  .recycle_vectors(x)"},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"x list vectors checked compliance Tidyverse recycling rules, recycled. x list recycled, two cases envisaged: elements x expected length, , one element x scalars.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Vector recyclability checks and vector recycling — vector_recycling","text":".test_recyclable returns single logical value. .recycle_vectors returns list vectors recycled length following Tidyverse recycling rules.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"Note .test_recyclable() return vectors unequal lengths x comply length rules. compliance enforced function expected used internally, call .test_recyclable() (e.g. stopifnot()).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/reference/vector_recycling.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Vector recyclability checks and vector recycling — vector_recycling","text":"Tim Taylor","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"epidemics-030","dir":"Changelog","previous_headings":"","what":"epidemics 0.3.0","title":"epidemics 0.3.0","text":"minor version release epidemics end point project allows vector inputs Ebola model (#211, #212).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"breaking-changes-0-3-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"epidemics 0.3.0","text":"Ebola model run single parameter set single set composable (.e., functionality vignette) now runs 100 replicates model default, output returns additional column name “replicate” (#211). Ebola model disallows rate interventions , time-dependence , ‘infectiousness rate’ ‘removal rate’ control number epidemiological sub-compartments allowed vary run time. default behaviour epidemic_size() exclude ‘dead’ compartment epidemic size calculations; changed including default, models don’t ‘dead’ compartment (#212);","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"model-functions-0-3-0","dir":"Changelog","previous_headings":"","what":"Model functions","title":"epidemics 0.3.0","text":"Ebola model code split two-level structure similar ODE models. user facing function model_ebola() now handles input checking cross-checking, makes combinations infection parameter sets scenarios, handles output. internal model function .model_ebola_internal() now called combinations parameters scenario elements (#211). .model_ebola_internal() relies functionality {withr} package preserve random number seed parameter set-scenario combinations, ensure -th replicate scenario starts random number stream.","code":""},{"path":[]},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"classes-0-3-0","dir":"Changelog","previous_headings":"","what":"Classes","title":"epidemics 0.3.0","text":"<intervention> helper functions .cumulative_rate_intervention() .intervention_on_rates() renamed include prefix . indicate internal functions (#211). Small updates .cross_check_intervention() better handle intervention sets contacts interventions optional (Ebola model) (#211).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"helper-functions-0-3-0","dir":"Changelog","previous_headings":"","what":"Helper functions","title":"epidemics 0.3.0","text":".check_prepare_args_ebola() new argument cross-checking preparation function Ebola model (#212). epidemic_size() substantially updated (#212): Added option time returns epidemic size specific time point, overriding stage argument, defaults NULL intended use function return final size; Added option return epidemic sizes multiple stages time points (stage time can vectors); Added option simplify output vector, TRUE default keep consistency previous functionality; Added functionality handle replicates Ebola model; Added tests new functionality. Added function .output_to_df_ebola() handle output Ebola model (#211).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"documentation-0-3-0","dir":"Changelog","previous_headings":"","what":"Documentation","title":"epidemics 0.3.0","text":"Updates Ebola model vignette showing new functionality. Updates design decisions vignette documenting decisions taken Ebola model. Updated sections handling social contacts data ‘Getting started’ ‘Modelling interventions social contacts’ vignettes, added reference Wallinga et al. 2006 https://doi.org/10.1093/aje/kwj317 (#217). Enables auto development mode website _pkgdown.yml, manually specify Bootstrap version 5 (#213). Updates WORDLIST. Updates installation instructions Readme; link ‘Contribute’ correctly directs pull requests page (#217).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"package-0-3-0","dir":"Changelog","previous_headings":"","what":"Package","title":"epidemics 0.3.0","text":"{withr} moved Suggests Imports due use seed management. Added @bahadzie contributor @jamesmbaazam reviewer. Updates GitHub Actions workflows linter config file. Updates license year 2024 files year.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"epidemics-020","dir":"Changelog","previous_headings":"","what":"epidemics 0.2.0","title":"epidemics 0.2.0","text":"second GitHub release epidemics makes substantial additions functionality v0.1.0, introduces significant breaking changes (#176). release end point project ship vectorised ODE models. release focuses ODE models epidemics.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"breaking-changes-0-2-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"epidemics 0.2.0","text":"model functions renamed model_<NAME>(), removing language suffix (#176). wrappers around R-implementations ‘default’ ‘Vacamole’ models removed, ODE system functions retained potential future use (#176). “Vacamole” model refactored arguments *_reduction_vax effect double vaccination compartmental transition rates renamed *_vax, * may one “susceptibility”, “hospitalisation”, “mortality”. Previously, parameters implemented internal C++ code, presented inverse values users (.e., susceptibility_vax = susceptibility * (1 - (susceptibility_reduction_vax)))). change brings user-facing representation line internal implementation, allows parameters targeted rate interventions time-dependence, possible earlier (#176, #203, overriding #144). function get_parameter() removed (#176). infection parameter “transmissibility” renamed “transmission rate” corresponding function argument transmission_rate (#196).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"model-functions-0-2-0","dir":"Changelog","previous_headings":"","what":"Model functions","title":"epidemics 0.2.0","text":"ODE model functions can now passed numeric vectors infection parameters, lists intervention sets (list <intervention>s), lists <vaccination> intervention vaccination argument respectively. main change minor version. (#176) ODE model functions take {data.table} make combinations interventions vaccinations (together called ‘scenario’), infection parameter sets run scenario parameter set (#176). ODE model functions return <data.table>s - may nested model arguments identity columns vectors parameters multiple scenarios passed. simple, unnested <data.table> passed model function called scalar arguments (#176).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"model-structures-0-2-0","dir":"Changelog","previous_headings":"","what":"Model structures","title":"epidemics 0.2.0","text":"fix vaccination implemented default Vacamole models: group-specific vaccination rates passed <vaccination> internally converted count multiplication group-specific population size, value subtracted susceptibles, vaccination active. previous implementation made number vaccinations dependent number susceptibles, line public health understanding vaccination (details: #198, fix: #202). C++ ODE model implementation now access values std::unordered_map model parameters using operator keys (model_params.(\"parameter_name\")) rather using [ (model_params[\"parameter_name\"]); latter method introduce key-value pair parameter_name : 0 numeric value types key missing map. led issues Vacamole model *_vax parameters correctly transferred C++ substituted 0s without throwing error (#203).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"classes-0-2-0","dir":"Changelog","previous_headings":"","what":"Classes","title":"epidemics 0.2.0","text":"substantial changes classes; small additions input checking <population> class.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"helper-functions-0-2-0","dir":"Changelog","previous_headings":"","what":"Helper functions","title":"epidemics 0.2.0","text":"Internal helper functions .check_args_model_*() .prepare_args_model_*() combined single functions .check_prepare_args_*() called output input checking side effects. new internal functions .prepare_population(), .cross_check_intervention(), .cross_check_vaccination(), .cross_check_timedep(), .cross_check_popchange() check prepare model population check inputs compatibility . used .check_prepare_args_*(). New internal functions added check recycle lists vectors; original implementations @TimTaylor. output_to_df() renamed .output_to_df().","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"documentation-0-2-0","dir":"Changelog","previous_headings":"","what":"Documentation","title":"epidemics 0.2.0","text":"benchmarking vignette removed R-model implementations longer provided users (#176). vignette parameter uncertainty rewritten show pass vectors infection parameters model composable elements model functions, renamed “Modelling parameter uncertainty epidemic scenarios” (#176). design decisions vignette added help developers contributors understand package architecture design choices made epidemics development; includes conceptual design diagram well architecture diagram (#188). function documentation updated reflect name changes minor improvements (#176). README reorganised shift model list end, make installation instructions easier find (#176). Corrected website URL _pkgdown.yml; allows search functionality package website (#195). Updated WORDLIST.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"package-0-2-0","dir":"Changelog","previous_headings":"","what":"Package","title":"epidemics 0.2.0","text":"ODE model functions received extensive standardised (much possible) test suite. Filenames standardised show files related, e.g. R/model_default.R, src/model_default.cpp, inst/include/model_default.h; references filenames package header updated. Removed {deSolve} dependencies. Added {ggdist}, {withr}, {purr} {tidyr} Suggests; CITATION.cff updated match. Added basic infrastructure continuous relative benchmarking (#206).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"epidemics-010","dir":"Changelog","previous_headings":"","what":"epidemics 0.1.0","title":"epidemics 0.1.0","text":"initial GitHub release epidemics, R package ships library compartmental epidemic model structures can used, along supplied classes help define population characteristics epidemic response interventions including vaccinations, compose model epidemic scenarios. epidemics still actively developed, major changes planned near future. release aimed supporting reproducibility projects used epidemics subject breaking changes due planned package development. sections describe contents release.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"model-structures-0-1-0","dir":"Changelog","previous_headings":"","what":"Model structures","title":"epidemics 0.1.0","text":"release epidemics includes four model structures supporting range composable elements modify epidemic trajectories. “Default” model: deterministic SEIR-V model allowing heterogeneity social contacts demographic groups, optional, single-dose non-leaky vaccination; “Vacamole” model: deterministic SEI-HRD-V2 implementation model allowing heterogeneity social contacts demographic groups, two-dose leaky vaccination, supporting different infection trajectories infectious hospitalised (H) compartments doubly vaccinated individuals, tracks deaths (D), initially developed Dutch public health agency RIVM vaccine impact modelling Covid-19 pandemic, published Ainslie et al. 2022 https://doi.org/10.2807/1560-7917.ES.2022.27.44.2101090; “Diphtheria” model: deterministic SEIHR model tracking outcomes different demographic groups, including heterogeneity social contacts, adapted Finger et al. 2019 https://doi.org/10.1186/s12916-019-1288-7 intended application disease outbreaks humanitarian camp setting; “Ebola” model: discrete time stochastic SEIHFR model suitable modelling Ebola virus disease haemorrhagic fevers, allows varying efficacy isolation hospital setting (H), allows modelling transmission funeral context (F), adapted consensus Ebola virus disease model Li et al. 2019 https://doi.org/10.1098/rspb.2019.0774 using simulation methods Getz Dougherty 2018 https://doi.org/10.1080/17513758.2017.1401677.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"solving-ode-systems-using-boost-odeint-0-1-0","dir":"Changelog","previous_headings":"","what":"Solving ODE systems using Boost odeint","title":"epidemics 0.1.0","text":"epidemics uses Boost’s odeint https://www.boost.org/doc/libs/1_84_0/libs/numeric/odeint/doc/html/boost_numeric_odeint/getting_started/overview.html treat deterministic models’ ordinary differential equations (ODEs) initial value problems solve . Model ODEs defined structs operators package headers, exposed R internal Rcpp functions. ‘default’, ‘Vacamole’, ‘diphtheria’ models ODE models defined way. intended help reduce overheads associated passing ODE systems written R back forth solver (provided {deSolve}), easier way define feature-rich models writing C code solvers provided {deSolve} accept compiled code. epidemics headers include tools handling C++ representations R objects used package (see ), can imported Rcpp packages. ‘default’ ‘Vacamole’ models equivalent R-implementations well use {deSolve} package; intended made unavailable future releases.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"composable-elements-as-classes-0-1-0","dir":"Changelog","previous_headings":"","what":"Composable elements as classes","title":"epidemics 0.1.0","text":"epidemics provides classes help organise components epidemic scenario model. <population>: S3 class store population characteristics including size demographic groups, social contacts matrix, initial conditions model; <intervention>: S3 abstract class super-class allows definition events modify epidemic trajectory: <rate_intervention>: sub-class <intervention> allows reduction transition rates model compartments simulate effect policy interventions specific period; <contacts_intervention>: sub-class <intervention> allows reduction social contacts simulate effect policy interventions specific period; <vaccination>: S3 class holds intervals group-specific rates individuals transition ‘vaccinated’ compartment(s) model, available;","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"other-composable-elements-0-1-0","dir":"Changelog","previous_headings":"","what":"Other composable elements","title":"epidemics 0.1.0","text":"epidemics allows models include elements affect epidemic trajectory, custom classes. Time-dependence: models can passed list functions two arguments, time x expected return x function time, may used model effect seasonality model parameters; Population changes: Applicable diphtheria model, two element list time values, allow definition changes number susceptible individuals model, may used model influxes evacuations individuals humanitarian camps.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"output-processing-functions-0-1-0","dir":"Changelog","previous_headings":"","what":"Output processing functions","title":"epidemics 0.1.0","text":"epidemics provides functions help process output epidemic model run, calculate size epidemic demographic group stage (epidemic_size()), calculate number new infections demographic group timepoint model (new_infections()).","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"usage-vignettes-0-1-0","dir":"Changelog","previous_headings":"","what":"Usage vignettes","title":"epidemics 0.1.0","text":"epidemics includes range usage vignettes demonstrate : Get started package; Get started modelling interventions social contacts control outbreaks; Model overlapping sequential interventions social contacts; Model interventions modify transition rates model compartments; Get started modelling vaccination campaign; Model time-dependence seasonality disease transmission dynamics; Generate model uncertainty model parameters; Reduce number parameters required final size estimation; Use ‘Vacamole’ model scenarios leaky vaccination vaccine impact hospitalisation; Use ‘Ebola’ model scenarios responses Ebola virus disease outbreak; Use ‘diphtheria’ model scenarios outbreaks humanitarian camp setting.","code":""},{"path":"https://epiverse-trace.github.io/epidemics/news/index.html","id":"miscellaneous-0-1-0","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"epidemics 0.1.0","text":"Workflows render vignettes README website; Test code coverage 93%.","code":""}]
diff --git a/sitemap.xml b/sitemap.xml
index 8c1eeb8c..45d995ab 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -81,12 +81,18 @@
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/cumulative_rate_intervention.html</loc>
   </url>
+  <url>
+    <loc>https://epiverse-trace.github.io/epidemics/reference/dot-intervention_on_rates.html</loc>
+  </url>
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/dot-model_default_cpp.html</loc>
   </url>
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/dot-model_diphtheria_cpp.html</loc>
   </url>
+  <url>
+    <loc>https://epiverse-trace.github.io/epidemics/reference/dot-model_ebola_internal.html</loc>
+  </url>
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/dot-model_vacamole_cpp.html</loc>
   </url>
@@ -96,9 +102,6 @@
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/dot-ode_model_vacamole.html</loc>
   </url>
-  <url>
-    <loc>https://epiverse-trace.github.io/epidemics/reference/dot-output_to_df.html</loc>
-  </url>
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/dot-prepare_population.html</loc>
   </url>
@@ -117,9 +120,6 @@
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/intervention_constructor.html</loc>
   </url>
-  <url>
-    <loc>https://epiverse-trace.github.io/epidemics/reference/intervention_on_rates.html</loc>
-  </url>
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/model_default.html</loc>
   </url>
@@ -135,6 +135,9 @@
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/new_infections.html</loc>
   </url>
+  <url>
+    <loc>https://epiverse-trace.github.io/epidemics/reference/output_to_df.html</loc>
+  </url>
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/population.html</loc>
   </url>
@@ -144,6 +147,9 @@
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/prepare_diphtheria_args.html</loc>
   </url>
+  <url>
+    <loc>https://epiverse-trace.github.io/epidemics/reference/prepare_ebola_args.html</loc>
+  </url>
   <url>
     <loc>https://epiverse-trace.github.io/epidemics/reference/prepare_vacamole_args.html</loc>
   </url>