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Integrating DHS/MIS Biomarkers with 34 Years of CHIRPS-NDVI Climate Data for Malaria Risk Prediction in Nigeria: A Machine Learning and Spatial Mapping Approach
2025-12-15
epidemiology
Title + abstract only
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BackgroundThe estimates of national disease risk are considerably limited by the time of conducted surveys and the geographical inadequacies in surveillance, notwithstanding malarias continued prominence in morbidity and mortality in Nigeria. There is limited research employing machine learning to integrate long term environmental trends with DHS/MIS biomarker data on a national scale, despite the established influence of climate, rainfall patterns, vegetation, and population on transmission dyn...
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