How can we predict where and when people are likely to contract malaria in a near future 🦟 ☀️ ☔ ?

How can we make the results of these predictions easily accessible to anyone, including the authorities in charge of malaria prevention ?

Through a series of R scripts and related R Markdown documents, we propose a transparent, reproducible and as much as possible reusable method to model the risk of residual malaria transmission at a micro-scale and communicate the predictions. Our study areas are two distinct 2500 km2 wide rural regions of Western Africa. We use epidemiological, entomological and sociological data collected during the 3 years-long REACT project over these two areas, in conjunction with environmental data mostly free of charge and available at global scale.

Our work uses exclusively free and open source softwares/libraries. All the scripts are developed using the R programming language and rely on many, many packages developed by the huge R community. We attempt to develop generic scripts (e.g. land cover mapping, extraction of spatial-temporal environmental data at sampling points) that can be reused in various contexts, so do not hesitate to have a look at the vignettes even if you are not working in the public health research field !

Our vignettes :

This work is part of my PhD project realized at the MIVEGEC unit of the French Research Institute for Sustainable Development.