- The goal of this repository is to evaluate software packages for estimating the effective reproduction number.
- We do this by fitting models from a range of software packages to simulated and real data
- In the future, these data will be stored in another repository ("
rtdata") - In the future, we will summarise the output of each package consistently using the
summrtR package - We hope that this repository will contain evaluations which are run semi-regularly using GitHub actions so as to serve as a living, rather than static, comparison
The following vignettes (which are hosted under the vignettes folder) were automatically built using GitHubActions:
- epiestim: https://epistorm.github.io/RtEval/epiestim_vignette.html
- EpiLPS: https://epistorm.github.io/RtEval/EpiLPS_vignette.html
- EpiNow2: https://epistorm.github.io/RtEval/EpiNow2_vignette.html
- RtEstim: https://epistorm.github.io/RtEval/RtEstim_vignette.html
- Joint: https://epistorm.github.io/RtEval/eval_vignette.html
Remains to scope!
To run the code in this repository you'll need at least R version 4.0.0:
required_version <- "4.0.0"
if (getRversion() < required_version) {
stop(paste("Your R version is", getRversion(), ". Please update to version", required_version, "or higher."))
} else {
cat(paste("R version is sufficient:", getRversion(), "\n"))
}You will also need these packages:
install.packages(
c(
"rmarkdown", "shiny", "knitr", "plotly",
"purrr", "splines", "tidyverse", "readr",
"EpiLPS", "EpiNow2", "lubridate", "rstan",
"cmdstanr", "R0", "remotes", "ggpubr",
"ggtext", "lemon", "patchwork"
)
)
remotes::install_github("dajmcdon/rtestim")
install.packages("EpiEstim", repos = c("https://mrc-ide.r-universe.dev", "https://cloud.r-project.org"))This work is a part of the Epistorm Rt Collabathon.
Participants in the workshop may be interested in these links:
Some remaining todo's include:
- having some distributions vary over time in the simulated data (e.g., mean reporting delay gets shorter over time)