Rename 'transmissibility' to 'transmission_rate', WIP #186

R/RcppExports.R

@@ -10,7 +10,7 @@
 #' [model_default_cpp()].
 #'
 #' @param initial_state A matrix for the initial state of the compartments.
-#' @param transmissibility The transmission rate \eqn{\beta} at which
+#' @param transmission_rate The transmission rate \eqn{\beta} at which
 #' unvaccinated and partially vaccinated individuals are infected by the
 #' disease.
 #' @param infectiousness_rate The rate of transition from exposed to infectious
@@ -35,8 +35,8 @@
 #' as specified in the initial conditions matrix (see [population()]).
 #' The second list element is a vector of timesteps.
 #' @keywords internal
-.model_default_cpp <- function(initial_state, transmissibility, 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 = 100.0, increment = 1.0) {
-    .Call(`_epidemics_model_default_internal`, initial_state, transmissibility, 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, increment)
+.model_default_cpp <- function(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 = 100.0, increment = 1.0) {
+    .Call(`_epidemics_model_default_internal`, 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, increment)
 }
 
 #' @title Run an SEIHR ODE model for diphtheria using a Boost solver
@@ -49,7 +49,7 @@
 #' [model_diphtheria_cpp()].
 #'
 #' @param initial_state A matrix for the initial state of the compartments.
-#' @param transmissibility The transmission rate \eqn{\beta}.
+#' @param transmission_rate The transmission rate \eqn{\beta}.
 #' @param infectiousness_rate The rate of transition from exposed to infectious
 #' \eqn{\alpha}.
 #' @param recovery_rate The recovery rate \eqn{\gamma}.
@@ -73,8 +73,8 @@
 #' as specified in the initial conditions matrix.
 #' The second list element is a vector of timesteps.
 #' @keywords internal
-.model_diphtheria_cpp <- function(initial_state, transmissibility, 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 = 100.0, increment = 1.0) {
-    .Call(`_epidemics_model_diphtheria_internal`, initial_state, transmissibility, 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, increment)
+.model_diphtheria_cpp <- function(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 = 100.0, increment = 1.0) {
+    .Call(`_epidemics_model_diphtheria_internal`, 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, increment)
 }
 
 #' @title Run the RIVM Vacamole model
@@ -90,10 +90,10 @@
 #' [model_vacamole_cpp()].
 #'
 #' @param initial_state A matrix for the initial state of the compartments.
-#' @param transmissibility The transmission rate \eqn{\beta} at which
+#' @param transmission_rate The transmission rate \eqn{\beta} at which
 #' unvaccinated and partially vaccinated individuals are infected by the
 #' disease.
-#' @param transmissibility_vax The transmission rate \eqn{\beta_V} at which
+#' @param transmission_rate_vax The transmission rate \eqn{\beta_V} at which
 #' individuals who have received two vaccine doses are infected by the disease.
 #' @param infectiousness_rate The rate of transition from exposed to infectious
 #' \eqn{\alpha}.
@@ -127,7 +127,7 @@
 #' as specified in the initial conditions matrix (see [population()]).
 #' The second list element is a vector of timesteps.
 #' @keywords internal
-.model_vacamole_cpp <- function(initial_state, transmissibility, transmissibility_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 = 100.0, increment = 1.0) {
-    .Call(`_epidemics_model_vacamole_internal`, initial_state, transmissibility, transmissibility_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, increment)
+.model_vacamole_cpp <- function(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 = 100.0, increment = 1.0) {
+    .Call(`_epidemics_model_vacamole_internal`, 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, increment)
 }
 

R/check_args_default.R

@@ -14,7 +14,7 @@
 #'  - `initial_state`: the initial conditions modified to represent absolute
 #' rather than proportional values;
 #'
-#'  - `transmissibility`, `infectiousness_rate`, `recovery_rate`: three numbers
+#'  - `transmission_rate`, `infectiousness_rate`, `recovery_rate`: three numbers
 #' representing the transmission rate of the infection, the rate of transition
 #' from exposed to infectious, and the recovery rate, respectively;
 #'
@@ -50,7 +50,7 @@
   # check the interventions list against the population
   mod_args[["intervention"]] <- .cross_check_intervention(
     mod_args[["intervention"]], mod_args[["population"]],
-    c("contacts", "transmissibility", "infectiousness_rate", "recovery_rate")
+    c("contacts", "transmission_rate", "infectiousness_rate", "recovery_rate")
   )
   # check the vaccination against the population
   mod_args[["vaccination"]] <- .cross_check_vaccination(

R/check_args_diphtheria.R

@@ -14,7 +14,7 @@
 #'  - `initial_state`: the initial conditions modified to represent absolute
 #' rather than proportional values;
 #'
-#'  - `transmissibility`, `transmissibility_vax`: two numbers representing the
+#'  - `transmission_rate`, `transmission_rate_vax`: two numbers representing the
 #' transmission rate
 #' of the infection for unvaccinated or single-dose vaccinated, and two-dose
 #' vaccinated individuals, respectively;
@@ -84,7 +84,7 @@
   mod_args[["intervention"]] <- .cross_check_intervention(
     mod_args[["intervention"]], mod_args[["population"]],
     c(
-      "transmissibility", "infectiousness_rate", "prop_hosp",
+      "transmission_rate", "infectiousness_rate", "prop_hosp",
       "hosp_entry_rate", "hosp_exit_rate", "recovery_rate"
     )
   )

R/check_args_vacamole.R

@@ -12,7 +12,7 @@
 #'  - `initial_state`: the initial conditions modified to represent absolute
 #' rather than proportional values;
 #'
-#'  - `transmissibility`, `transmissibility_vax`: two numbers representing the
+#'  - `transmission_rate`, `transmission_rate_vax`: two numbers representing the
 #' transmission rate
 #' of the infection for unvaccinated or single-dose vaccinated, and two-dose
 #' vaccinated individuals, respectively;
@@ -63,7 +63,7 @@
   # check the interventions list against the population
   mod_args[["intervention"]] <- .cross_check_intervention(
     mod_args[["intervention"]], mod_args[["population"]],
-    c("contacts", "transmissibility", "infectiousness_rate", "recovery_rate")
+    c("contacts", "transmission_rate", "infectiousness_rate", "recovery_rate")
   )
   # check the vaccination against the population
   mod_args[["vaccination"]] <- .cross_check_vaccination(

R/dummy_elements.R

@@ -1,14 +1,14 @@
 #' Specify no time dependence of model rates
 #'
 #' @param func_target A string for the parameter to be targeted. Defaults to the
-#' transmissibility parameter.
-#' @return A list with a single named element, `transmissibility`, which is a
+#' transmission rate parameter.
+#' @return A list with a single named element, `transmission_rate`, which is a
 #' function that returns its second argument. This matches the specification for
 #' functions to be passed as the `time_dependence` argument of epidemic
 #' functions.
 #' @noRd
 #' @keywords internal
-.no_time_dependence <- function(func_target = "transmissibility") {
+.no_time_dependence <- function(func_target = "transmission_rate") {
   l <- list(
     function(time, x) x
   )

R/model_default.R

@@ -9,7 +9,7 @@
 #' This model can accommodate heterogeneity in social contacts among demographic
 #' groups, as well as differences in the sizes of demographic groups.
 #'
-#' The `population`, `transmissibility`, `infectiousness_rate`, and
+#' The `population`, `transmission_rate`, `infectiousness_rate`, and
 #' `recovery_rate`
 #' arguments are mandatory, while passing an `intervention` and `vaccination`
 #' are optional and can be used to simulate scenarios with different epidemic
@@ -19,7 +19,7 @@
 #' @param population An object of the `population` class, which holds a
 #' population contact matrix, a demography vector, and the initial conditions
 #' of each demographic group. See [population()].
-#' @param transmissibility A numeric for the rate at which individuals
+#' @param transmission_rate A numeric for the rate at which individuals
 #' move from the susceptible to the exposed compartment upon contact with an
 #' infectious individual. Often denoted as \eqn{\beta}, with
 #' \eqn{\beta = R_0 / \text{infectious period}}. See **Details** for default
@@ -67,7 +67,7 @@
 #'
 #' The default values are:
 #'
-#' - Transmissibility (\eqn{\beta}, `transmissibility`): 0.186, assuming an
+#' - Transmission rate (\eqn{\beta}, `transmission_rate`): 0.186, assuming an
 #' \eqn{R_0} = 1.3 and an infectious period of 7 days.
 #'
 #' - Infectiousness rate (\eqn{\sigma}, `infectiousness_rate`): 0.5, assuming
@@ -102,10 +102,10 @@
 #' )
 #'
 #' # run epidemic simulation with no vaccination or intervention
-#' # and three discrete values of transmissibility
+#' # and three discrete values of transmission rate
 #' data <- model_default(
 #'   population = uk_population,
-#'   transmissibility = c(1.3, 1.4, 1.5) / 7.0, # uncertainty in R0
+#'   transmission_rate = c(1.3, 1.4, 1.5) / 7.0, # uncertainty in R0
 #' )
 #'
 #' # view some data
@@ -121,7 +121,7 @@
 #' data
 #' @export
 model_default <- function(population,
-                          transmissibility = 1.3 / 7.0,
+                          transmission_rate = 1.3 / 7.0,
                           infectiousness_rate = 1.0 / 2.0,
                           recovery_rate = 1.0 / 7.0,
                           intervention = NULL,
@@ -136,7 +136,7 @@ model_default <- function(population,
   assert_population(population, compartments)
 
   # NOTE: model rates very likely bounded 0 - 1 but no upper limit set for now
-  checkmate::assert_numeric(transmissibility, lower = 0, finite = TRUE)
+  checkmate::assert_numeric(transmission_rate, lower = 0, finite = TRUE)
   checkmate::assert_numeric(infectiousness_rate, lower = 0, finite = TRUE)
   checkmate::assert_numeric(recovery_rate, lower = 0, finite = TRUE)
   checkmate::assert_integerish(time_end, lower = 0)
@@ -148,7 +148,7 @@ model_default <- function(population,
 
   # check all vector lengths are equal or 1L
   params <- list(
-    transmissibility = transmissibility,
+    transmission_rate = transmission_rate,
     infectiousness_rate = infectiousness_rate,
     recovery_rate = recovery_rate,
     time_end = time_end
@@ -221,7 +221,7 @@ model_default <- function(population,
   time_dependence <- list(
     .cross_check_timedep(
       time_dependence,
-      c("transmissibility", "infectiousness_rate", "recovery_rate")
+      c("transmission_rate", "infectiousness_rate", "recovery_rate")
     )
   )
 
@@ -310,7 +310,7 @@ model_default <- function(population,
   # `params` refers to the list passed as a function argument.
   # e.g. contact matrix, or interventions, are not included in `model_params`
   model_params <- params[c(
-    "transmissibility", "infectiousness_rate", "recovery_rate"
+    "transmission_rate", "infectiousness_rate", "recovery_rate"
   )]
 
   # apply time dependence before interventions
@@ -338,7 +338,7 @@ model_default <- function(population,
       (params[["vax_time_end"]] > t))
 
   # calculate transitions
-  sToE <- (model_params[["transmissibility"]] * y[, 1] *
+  sToE <- (model_params[["transmission_rate"]] * y[, 1] *
     contact_matrix_ %*% y[, 3])
   eToI <- model_params[["infectiousness_rate"]] * y[, 2]
   iToR <- model_params[["recovery_rate"]] * y[, 3]

R/model_diphtheria.R

@@ -57,8 +57,8 @@
 #'
 #' The default values are taken from Finger et al. (2019) where possible:
 #'
-#' - Transmissibility (\eqn{\beta}, `transmissibility`): 0.8888889, assuming an
-#' \eqn{R_0} of 4.0 and a total infectious period of 4.5 days.
+#' - Transmission rate (\eqn{\beta}, `transmission_rate`): 0.8888889, assuming
+#' an \eqn{R_0} of 4.0 and a total infectious period of 4.5 days.
 #'
 #' - Infectiousness rate (\eqn{\sigma}, `infectiousness_rate`): 0.333, assuming
 #' a pre-infectious period of 3 days.
@@ -145,7 +145,7 @@
 #' tail(data)
 #' @export
 model_diphtheria <- function(population,
-                             transmissibility = 4.0 / 4.5,
+                             transmission_rate = 4.0 / 4.5,
                              infectiousness_rate = 1.0 / 3.0,
                              recovery_rate = 1.0 / 3.0,
                              reporting_rate = 0.03,
@@ -166,7 +166,7 @@ model_diphtheria <- function(population,
   assert_population(population, compartments)
 
   # NOTE: model rates very likely bounded 0 - 1 but no upper limit set for now
-  checkmate::assert_numeric(transmissibility, lower = 0, finite = TRUE)
+  checkmate::assert_numeric(transmission_rate, lower = 0, finite = TRUE)
   checkmate::assert_numeric(infectiousness_rate, lower = 0, finite = TRUE)
   checkmate::assert_numeric(recovery_rate, lower = 0, finite = TRUE)
   # reporting rate and prop_hosp are expected to be proportions bounded 0 - 1
@@ -184,7 +184,7 @@ model_diphtheria <- function(population,
 
   # check all vector lengths are equal or 1L
   params <- list(
-    transmissibility = transmissibility,
+    transmission_rate = transmission_rate,
     infectiousness_rate = infectiousness_rate,
     recovery_rate = recovery_rate,
     reporting_rate = reporting_rate,
@@ -258,7 +258,7 @@ model_diphtheria <- function(population,
     .cross_check_timedep(
       time_dependence,
       c(
-        "transmissibility", "infectiousness_rate", "prop_hosp",
+        "transmission_rate", "infectiousness_rate", "prop_hosp",
         "reporting_rate", "hosp_entry_rate", "hosp_exit_rate", "recovery_rate"
       )
     )