Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?

Malaria burden is increasing in sub-Saharan cities because of their rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between the urban environments and malaria. Additionally, no standardized urban land-use/land-cover has been defined for urban malaria studies. Here, we demonstrate the potential of Local Climate Zones (LCZs) for modelling malaria (PfPR 2-10) prevalence and studying malaria prevalence in urban settings across nine sub-Saharan African cities. Using a random forest classification algorithm over a set of 365 malaria surveys we: (i) identify a suitable set of covariates derived from open-source earth observations; and (ii) depict the best buffer size at which to aggregate them for modelling PfPR 2-10. Our results demonstrate that geographical models can learn from LCZ over a set of cities and be transferred over a city of choice that has few or no malaria surveys. In particular, we find that urban areas systematically have lower PfPR 2-10 (5 % to 30 %) than rural areas (15 % to 40 %). The PfPR 2-10 urban-to-rural gradient is dependent on the climatic environment in which the city is located. Further, LCZs show that more open urban environments located close to wetlands have higher PfPR 2-10. We also find that informal settlements -- represented by the LCZ~7 (lightweight lowrise) -- have higher malaria prevalence than other densely built-up residential areas with a mean prevalence of 11.11 %. Overall, we suggest the applicability of LCZs for more exploratory modelling in urban malaria studies.