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ABSTRACT: Background
Malaria epidemics result from extreme precipitation and flooding, which are increasing with global climate change. Local adaptation and mitigation strategies will be essential to prevent excess morbidity and mortality.Methods
We investigated the spatial risk of malaria infection at multiple timepoints after severe flooding in rural western Uganda employing longitudinal household surveys measuring parasite prevalence and leveraging remotely sensed information to inform spatial models of malaria risk in the 3 months after flooding.Results
We identified clusters of malaria risk emerging in areas (1) that showed the greatest changes in Normalized Difference Vegetation Index from pre- to postflood and (2) where residents were displaced for longer periods of ti
SUBMITTER: Xu E
PROVIDER: S-EPMC10786254 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature