Estimate Global Clustering in Infectious Disease.
IDSpatialStats
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)
Installation
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')
Troubleshooting
For general questions, contact package maintainers Justin Lessler ([email protected]) or John Giles ([email protected]).
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.