WHO

getTBinR 0.5.5 now on CRAN - 2017 data.

getTBinR 0.5.5 is now on CRAN and should be available on a mirror near you shortly! This update is mainly about highlighting the availability of TB data for 2017, although some small behind the scenes changes were required to get the code set up going forward for yearly updates. A few more plotting options have been added, along with the corresponding tests (definitely the most exciting news). The full changelog is below along with a short example highlighting some of the changes in the 2017 data.

getTBinR 0.5.4 now on CRAN - new data, map updates and a new summary function.

getTBinR 0.5.4 is now on CRAN and should be available on a mirror near you shortly! This update includes an additional data set for 2016 containing variables related to drug resistant Tuberculosis, some aesthetic updates to mapping functionality and a new summarise_tb_burden function for summarising TB metrics. Behind the scenes there has been an extensive test overhaul, with vdiffr being used to test images, and several bugs fixes. See below for a full list of changes and some example code exploring the new functionality.

Exploring Estimates of the Tuberculosis Case Fatality Ratio - with getTBinR

This is a quick post exploring estimates of the case fatality ratio for Tuberculosis (TB) from data published by the World Health Organisation (WHO). It makes use of getTBinR (which is now on CRAN), pacman for package management, hrbrthemes for plot themes, and pathwork for combining multiple plots into a storyboard. For an introduction to using getTBinR to explore the WHO TB data see this post. It is estimated that in 2016 there was more than 10 million cases of active TB, with 1.

Exploring Global Trends in Tuberculosis Incidence Rates - with GetTBinR

In November I attended Epidemics, which is a conference focused on modelling infectious diseases. There was a lot of great work and perhaps most excitingly a lot of work being offered as R packages. I’ve recently begun wrapping all my analytical work in R packages, as it makes producing reproducible research a breeze! Unfortunately all of this work is still making it’s way towards publication and for a variety of reasons can’t be shared until it has passed this hurdle.

getTBinR

Quickly and easily import analysis ready TB burden data, from the World Health Orgnaisation (WHO), into R. The aim of the package is to speed up access to high quality TB burden data, using a simple R interface. Generic plotting functions are provided to allow for rapid graphical exploration of the WHO TB data. This package is inspired by a blog post, which looked at WHO TB incidence rates. See here for the WHO data permissions.