Warning: This package is a prototype and is under active development. Breaking changes are likely.
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.
Installing the package
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 epidist, you may also
need to install a past version of CmdStan, which you can do with the
version argument.
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 epidist.
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.
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").
All contributions to this project are gratefully acknowledged using the
allcontributors
package following the
all-contributors specification.
Contributions of any kind are welcome!
seabbs, athowes, parksw3, medewitt