Predicting malaria outbreaks using earth observation measurements and spatiotemporal deep learning modelling: a South Asian case study from 2000 to 2017.

Background: Malaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infection, predominantly in African and South Asian countries. Although malaria is preventable, heterogeneity in sociodemographic and environmental risk factors over time and across diverse geographical and climatological regions make outbreak prediction challenging.