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

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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Bibliographic Details
Main Authors: Maurice W. M. L. Kalthof, Mathieu Gravey, Flore Wijnands, Derek Karssenberg
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2023-10-01
Series:GeoHealth
Subjects:
malaria
surface water
machine learning
remote sensing
Plasmodium falciparum
malaria prediction
Online Access:https://doi.org/10.1029/2023GH000811

Internet

https://doi.org/10.1029/2023GH000811

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