Warning: This package is a prototype and is under active development. Breaking changes are likely.
Summary
Understanding and accurately estimating epidemiological delay distributions is important for public health policy. These estimates directly influence epidemic situational awareness, control strategies, and resource allocation. In this package, we provide methods to address the key challenges in estimating these distributions, including truncation, interval censoring, and dynamical biases. Despite their importance, these issues are frequently overlooked, often resulting in biased conclusions.
Installation
Installing the package
You can install the latest released version using the normal R function, though you need to point to r-universe instead of CRAN:
install.packages(
"epidist", repos = "https://epinowcast.r-universe.dev"
)Alternatively, you can use the remotes package to install the development version from Github (warning! this version may contain breaking changes and/or bugs):
remotes::install_github(
"epinowcast/epidist", dependencies = TRUE
)Similarly, you can install historical versions by specifying the release tag (e.g. this installs 0.1.0):
remotes::install_github(
"epinowcast/epidist", dependencies = TRUE, ref = "v0.2.0"
)Note: You can also use that last approach to install a specific commit if needed, e.g. if you want to try out a specific unreleased feature, but not the absolute latest developmental version.
Installing CmdStan
If you wish to do model fitting and nowcasting, you will need to install CmdStan, which also entails having a suitable C++ toolchain setup. We recommend using the cmdstanr package. The Stan team provides instructions in the Getting started with cmdstanr vignette, with other details and support at the package site, but the brief version is:
# if you not yet installed `epinowcast`, or you installed it without `Suggests` dependencies
install.packages("cmdstanr", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
# once `cmdstanr` is installed:
cmdstanr::install_cmdstan()Note: You can speed up CmdStan installation using the cores argument. If you are installing a particular version of epinowcast, you may also need to install a past version of CmdStan, which you can do with the version argument.
Alternative: Docker
We also provide a Docker image with epinowcast and all dependencies installed. You can use this image to run epidist without installing dependencies.
Resources
Organisation Website
Our organisation website includes links to other resources, guest posts, and seminar schedule for both upcoming and past recordings.
Community Forum
Our community forum has areas for question and answer and considering new methods and tools, among others. If you are generally interested in real-time analysis of infectious disease, you may find this useful even if do not use epinowcast.
Contributing
We welcome contributions and new contributors! We particularly appreciate help on identifying and identified issues. Please check and add to the issues, and/or add a pull request and see our contributing guide for more information.
How to make a bug report or feature request
Please briefly describe your problem and what output you expect in an issue. If you have a question, please don’t open an issue. Instead, ask on our Q and A page. See our contributing guide for more information.
Code of Conduct
Please note that the epidist project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Citation
If making use of our methodology or the methodology on which ours is based, please cite the relevant papers from our model outline. If you use epidist in your work, please consider citing it with citation("epidist").
Contributors
All contributions to this project are gratefully acknowledged using the allcontributors package following the all-contributors specification. Contributions of any kind are welcome!