Predicting Continental Scale Malaria With Land Surface Water Predictors Based on Malaria Dispersal Mechanisms and High‐Resolution Earth Observation Data

Abstract Despite malaria prevalence being linked to surface water through vector breeding, spatial malaria predictors representing surface water often predict malaria poorly. Furthermore, precipitation, which precursors surface water, often performs better. Our goal is to determine whether novel sur...

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Detalhes bibliográficos

Principais autores:	Maurice W. M. L. Kalthof, Mathieu Gravey, Flore Wijnands, Derek Karssenberg
Formato:	Artigo
Idioma:	Inglês
Publicado em:	American Geophysical Union (AGU) 2023-10-01
coleção:	GeoHealth
Assuntos:	malaria surface water machine learning remote sensing Plasmodium falciparum malaria prediction
Acesso em linha:	https://doi.org/10.1029/2023GH000811
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