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Modeling Malaria Risk in Mozambique Using Climate and Health Data

Domain:

healthcareclimate

Record type:

paper
Creator:
Gul
Publisher:
Zenodo
Host:avatar

This study develops machine learning models to predict monthly malaria incidence in Mopeia, Mozambique, integrating epidemiological, climatic, and spatial features. A novel Malaria Proneness Index (MPI) is proposed to enhance prediction accuracy and support targeted public health interventions

Visit

doi.org

Tags

Machine LearningSupervised Machine LearningMalariaMalaria ForecastingSub-Saharan AfricaClimate DataPublic HealthPredictive ModelingDisease surveillanceMozambique+1

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode