We implemented a multi-sensor, multi-scale, and multi-temporal approach. The project consisted of three broad main phases: data
acquisition and preparation, sub-model generation, and final epidemiological modelling for understanding intra-city and inter-city
epidemiological variability. The predictability of inter-urban variations of malaria infection risk was be studied at
sub-continental scale in a set of about 20 large cities of sub-Saharan Africa using HRRS and L/MRRS, whereas the intra-urban analysis focused
on a subset of 4 cities using VHRRS and HRRS. The methodology was innovative in many aspects. Highlights include the development of
the first high resolution (100 meters) intra-urban malaria models relying on EO-data, for two sub-Saharan African (SSA) cities.
Besides, due to the high thematic level of our input LULC maps, we could make strong associations of malaria prevalence with types
of urban neighbourhoods and biophysical characteristics, expanding our current knowledge of urban malaria. We also successfully
tested the transferability potential of high- to moderate resolution malaria models in a set of 9 cities, harnessing the potential
of Local Climate Zones (LCZ) and climate-related data.
Web site: http://react.ulb.be/