Mapping malaria risk in sub-Saharan African cities

This repository contains data and material to model and predict malaria risk (measured as PfPR_2-10) in four sub-Saharan African cities, Dakar (Senegal), Ouagadougou (Burkina Faso), Kampala (Uganda) and Dar es Salaam (Tanzania), using a set of environmental and socio-economic predictors derived from remote sensing imagery. These predictors are multi-resolution variables depicting the urban climate, the land use and the land cover. PfPR_2-10 modelling and prediction are achieved using a popular machine learning algorithm, namely random forest (RF).

Please refer to the ReadMe file for instructions on how to use this code, or to CamilleMorlighem/REACT2citi….