{EstZoonoticTB} is an R package containing data relevant to global zoonotic tuberculosis (TB), tools for manipulating and visualising these data, and analysis aiming to improve country level estimates of zoonotic TB. Packaged datasets include: cleaned data from a recent systematic review; data on the country specific epidemiology of TB; demographic data (including data on rural populations); animal demographic data; and data on the presence of zoonotic TB in animal populations (both domesticated and wild). Tooling includes functions for linking the built in datasets (built with the aim of accommodating external data sources), data mapping functions, and convenience functions for manipulating the linked datasets. The long term aim of the package is to provide a suite of data and tools that can be used to iteratively improve the estimation of global zoonotic TB burden. A secondary aim is to provide a user friendly interface to zoonotic TB relevant data in order to help spread awareness of zoonotic TB. See the package vignettes for further details.

Installation

Install the development version from GitHub:

Documentation

Overview

Documentation Development documentation Functions

Vignettes

Data sources Data linkage Data exploration Data mapping

Testing

Travis-CI Build Status AppVeyor Build Status Coverage Status

Shiny dashboard

Work in progress

To explore the package functionality in an interactive session, or to investigate Zoonotic TB without having to code extensively in R, a shiny dashboard has been built into the package. This can either be used locally using,

Or accessed online.

Contributing

File an issue here if there is a feature, or a dataset, that you think is missing from the package, or better yet submit a pull request!

Please note that the EstZoonoticTB project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Docker

This package has been developed in docker based on the rocker/geospatial image, to access the development environment enter the following at the command line (with an active docker daemon running),

The rstudio client can be accessed on port 8787 at localhost (or your machines ip). The default username is EstZoonoticTB and the default password is EstZoonoticTB. Alternatively, access the development environment via binder.