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This GitHub repository provides source code for the
IDSpatialStats R package, which is designed to help
epidemiologists assess the scale of spatial and temporal dependence in
epidemic case occurrence data.
The current implementation of the package includes a function which simulates infectious disease spread as a spatial branching process, along with two novel spatial statistics that estimate: 1) the mean of the spatial transmission kernel, which is a measure of fine-scale spatial dependence between two cases, and 2) the tau-statistic, a measure of global clustering based on pathogen subtype.
Detailed description of the methods can be found here:
Measuring spatial dependence for infectious disease epidemiology (Lessler et al. 2016)
To install the offical release of the IDSpatialStats
package, open R and type:
install.packages('IDSpatialStats')To install the install the development version, first install the
devtools package and then install
IDSpatialStats from source via GitHub:
install.packages('devtools')
devtools::install_github('HopkinsIDD/IDSpatialStats')For general questions, contact package maintainers Justin Lessler (jlessler@unc.edu) or John Giles (jrgiles@uw.edu).
To report bugs or problems with documentation, please go to the Issues page associated with this GitHub page and click new issue.
If you wish to contribute to IDSpatialStats, please get
in touch via email and then fork the latest version of the package.
After committing your code to your own forked version, submit a pull
request when you are ready to share.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.