In EDS ansehen

Modeling Malaria Risk in Mozambique Using Climate and Health Data

Gespeichert in:

Bibliographische Detailangaben
Titel:	Modeling Malaria Risk in Mozambique Using Climate and Health Data
Autoren:	Girma, Milky
Verlagsinformationen:	Zenodo, 2025.
Publikationsjahr:	2025
Schlagwörter:	Machine Learning, Sub-Saharan Africa, Disease surveillance, Malaria Forecasting, Supervised Machine Learning, Public Health, Predictive Modeling, Risk Prediction, Climate Data, Mozambique, Malaria
Beschreibung:	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
Publikationsart:	Journal
Sprache:	English
DOI:	10.5281/zenodo.17218068
DOI:	10.5281/zenodo.17009862
DOI:	10.5281/zenodo.17009861
Rights:	CC BY
Dokumentencode:	edsair.doi.dedup.....1746d8a80dc0de523e094d82700fbc9a
Datenbank:	OpenAIRE

Beschreibung
Abstract:	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
DOI:	10.5281/zenodo.17218068