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README.Rmd
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---
output: github_document
bibliography: vignettes/references.bib
link-citations: true
editor_options:
markdown:
wrap: 72
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
## *{{ packagename }}*: Tools for estimating vaccine effectiveness and vaccine related metrics <img src="man/figures/logo.png" align="right" width="130"/>
<!-- badges: start -->
[](https://opensource.org/license/mit)
[](https://github.com/epiverse-trace/vaccineff/actions/workflows/R-CMD-check.yaml)
[](https://app.codecov.io/gh/epiverse-trace/vaccineff?branch=main)
[](https://www.repostatus.org/#wip)
[](https://www.reconverse.org/lifecycle.html#concept)
[](https://CRAN.R-project.org/package=vaccineff)
[](https://doi.org/10.5281/zenodo.14258965)
<!-- badges: end -->
*{{ packagename }}* is developed at [Pontificia Universidad Javeriana](https://www.javeriana.edu.co/inicio) as part of the
[Epiverse-TRACE initiative](https://data.org/initiatives/epiverse/).
*{{ packagename }}* is an R package that offers tools for estimating vaccine effectiveness (VE), using a series of epidemiological designs including cohort studies, test-negative case-control, and screening methods [@bookvaccine]. The current version of the package provides a set of features for preparing, visualizing, and managing cohort data, estimating vaccine effectiveness, and assessing the performance of the models. Test-negative design and screening method will be included in future versions.
## Installation
Our stable versions are released on CRAN, and can be installed using:
```r
install.packages("vaccineff", build_vignettes = TRUE)
```
The current development version of _{{ packagename }}_ can be installed from [GitHub](https://github.com/) using the `pak` package.
```{r, eval = FALSE}
if(!require("pak")) install.packages("pak")
pak::pak("{{ gh_repo }}")
```
Or using the `remotes` package
```{r, eval = FALSE }
if(!require("remotes")) install.packages("remotes")
remotes::install_github("{{ gh_repo }}")
```
## Quick start
```{r cleaning, include = FALSE, echo = TRUE}
library(vaccineff)
```
*{{ packagename }}* provides a minimal cohort dataset that can be used to test out the models.
```{r example, include = TRUE, echo = TRUE}
# Load example `cohortdata` included in the package
data("cohortdata")
head(cohortdata, 5)
```
The function `make_vaccineff_data` allows defining different aspects of the study design—such as vaccination dates, immunization delays, and potential confounding factors—and creates an object of class `vaccineff_data`. Its output is used to estimate VE using a Cox model regression invoked by the function `estimate_vaccineff`, which returns the object `vaccineff`.
The proportional hazard assumption can be tested both through the Schoenfeld test and visually using the `plot` method by setting `type = "loglog"`.
```{r}
# Create `vaccineff_data`
vaccineff_data <- make_vaccineff_data(
data_set = cohortdata,
outcome_date_col = "death_date",
censoring_date_col = "death_other_causes",
vacc_date_col = "vaccine_date_2",
vaccinated_status = "v",
unvaccinated_status = "u",
immunization_delay = 15,
end_cohort = as.Date("2021-12-31"),
match = TRUE,
exact = "sex",
nearest = c(age = 1)
)
# Estimate VE
ve <- estimate_vaccineff(vaccineff_data, at = 180)
# Print summary of VE
summary(ve)
# Generate loglog plot to check proportional hazards
plot(ve, type = "loglog")
```
## Package vignettes
More details on how to use _{{ packagename }}_ can be found in the [online documentation as package vignettes](https://epiverse-trace.github.io/vaccineff/), and in the articles "Get Started with vaccineff" and "Introduction to cohort design with vaccineff".
## Help
To report a bug or to request a new feature please open an [issue](https://github.com/epiverse-trace/vaccineff/issues/new/choose).
## Contribute
Contributions to _{{ packagename }}_ are welcomed. Contributions are welcome via [pull
requests](https://github.com/epiverse-trace/vaccineff/pulls).
Contributors to the project include:
**Authors**: [David Santiago Quevedo](https://github.com/davidsantiagoquevedo) and [Zulma M. Cucunubá](https://github.com/zmcucunuba) (maintainer)
**Contributors**:
[Geraldine Gómez](https://github.com/GeraldineGomez), [Pratik Gupte](https://github.com/pratikunterwegs), [Érika J. Cantor](https://github.com/ErikaCantor), [Santiago Loaiza](https://github.com/santilo9513), [Jaime A. Pavlich-Mariscal](https://github.com/jpavlich), [Hugo Gruson](https://github.com/Bisaloo), [Chris Hartgerink](https://github.com/chartgerink), [Felipe Segundo Abril-Bermúdez](https://github.com/fsabrilb), [Joshua W. Lambert](https://github.com/joshwlambert), [Julian Otero](https://github.com/jd-otero)
## Code of conduct
Please note that the _{{ packagename }}_ project is released with a [Contributor Code of Conduct](https://github.com/epiverse-trace/.github/blob/main/CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.
## References