# covidseir <img src='man/figures/covidseir-logo.png' align="right" height="139" />
> Bayesian SEIR Modelling for Multivariate COVID-19 Case Data
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## Overview
**covidseir** fits a Bayesian SEIR (Susceptible, Exposed, Infectious, Recovered)
model to daily COVID-19 case data. The package focuses on estimating the
fraction of the usual contact rate for individuals participating in physical
distancing (social distancing). The model is coded in
[**Stan**](https://mc-stan.org/). The model can accommodate multiple types of
case data at once (e.g., reported cases, hospitalizations, ICU admissions) and
accounts for delays between symptom onset and case appearance.
The model is a continuation of the model described in the preprints:
Anderson, S. C., Edwards, A. M., Yerlanov, M., Mulberry, N., Stockdale, J., Iyaniwura, S. A., Falcao, R. C., Otterstatter, M. C., Irvine, M. A., Janjua, N. Z., Coombs, D., & Colijn, C. (2020). Estimating the impact of COVID-19 control measures using a Bayesian model of physical distancing. medRxiv, 2020.04.17.20070086. https://doi.org/10.1101/2020.04.17.20070086
Anderson, S. C., Mulberry, N., Edwards, A. M., Stockdale, J. E., Iyaniwura, S. A., Falcao, R. C., Otterstatter, M. C., Janjua, N. Z., Coombs, D., and Colijn, C. (2020). How much leeway is there to relax COVID-19 control measures? medRxiv 2020.06.12.20129833. https://doi.org/10.1101/2020.06.12.20129833
[Illustration for logo by Alissa Eckert, MSMI; Dan Higgins, MAMS](https://phil.cdc.gov/Details.aspx?pid=23311).
*This package is a work in progress: arguments and output format may still change and not all functionality has been tested.*
## Installation
Before installation, you will need a C++ compiler installed to compile the Stan model. If you are on a Mac or Linux, follow [these instructions](https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started). If you are on Windows, follow the 'Configuration' section [here](https://github.com/stan-dev/rstan/wiki/Installing-RStan-from-source-on-Windows) (you do not need to follow the rest of the instructions from that page to install rstan itself from source).
The following must return `TRUE` before continuing:
```r
# install.packages("pkgbuild")
pkgbuild::has_build_tools(debug = TRUE)
```
Then, install the covidseir package with:
```r
# install.packages("remotes")
remotes::install_github("seananderson/covidseir")
```
See the examples in `?fit_seir` and `?project_seir` and the [vignette](https://seananderson.github.io/covidseir/articles/fitting-case-data.html).
To install the package with the vignette:
```r
remotes::install_github("seananderson/covidseir", build_vignettes = TRUE)
```
and run:
```r
browseVignettes("covidseir")
```
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covidseir-master.zip (44个子文件)
covidseir-master
.gitignore 98B
NAMESPACE 958B
NEWS.md 5KB
vignettes
.gitignore 11B
restarting.Rmd 7KB
fitting-case-data.Rmd 15KB
configure 117B
R
project_seir.R 11KB
tidy-plot.R 8KB
post2prior.R 3KB
get_threshold.R 5KB
get_rt.R 3KB
seeiqr-package.R 697B
methods.R 999B
stanmodels.R 1020B
fit_seir.R 20KB
src
stanExports_seir.cc 2KB
RcppExports.cpp 566B
Makevars.win 727B
Makevars 751B
.Rbuildignore 212B
_pkgdown.yml 0B
.github
.gitignore 7B
workflows
R-CMD-check.yaml 3KB
pkgdown.yaml 1KB
man
post2prior.Rd 1KB
fit_seir.Rd 9KB
get_doubling_time.Rd 1KB
covidseir-package.Rd 414B
project_seir.Rd 4KB
plot_projection.Rd 2KB
get_threshold.Rd 1KB
figures
covidseir-logo.png 127KB
get_rt.Rd 745B
tidy_seir.Rd 868B
README.md 3KB
inst
stan
seir.stan 13KB
include
license.stan 649B
mm.R 4KB
f-mult.R 3KB
include
stan_meta_header.hpp 48B
configure.win 134B
DESCRIPTION 3KB
covidseir.Rproj 385B
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