Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?

Brousse, O; Georganos, S; Demuzere, M; Dujardin, S; Lennert, M; Linard, C; Snow, R W; Thiery, W; van Lipzig, N P M

Brousse, O; Georganos, S; Demuzere, M; Dujardin, S; Lennert, M; Linard, C; Snow, R W; Thiery, W; van Lipzig, N P M.

Afiliación

Brousse O; Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium.
Georganos S; UCL Institute for Environmental Design and Engineering, University College London, London, United Kingdom.
Demuzere M; Department of Geosciences, Environment and Society, Université Libre de Bruxelles, Brussels, Belgium.
Dujardin S; Department of Geography, Ruhr-University Bochum, Bochum, Germany.
Lennert M; Department of Environment, Ghent University, Ghent, Belgium.
Linard C; Department of Geography, Université de Namur, Namur, Belgium.
Snow RW; Department of Geosciences, Environment and Society, Université Libre de Bruxelles, Brussels, Belgium.
Thiery W; Department of Geography, Université de Namur, Namur, Belgium.
van Lipzig NPM; Population and Health Unit, Kenya Medical Research Institute Wellcome Trust, Nairobi, Kenya.

Environ Res Lett ; 15(12): 124051, 2020 Dec 15.

Article en En | MEDLINE | ID: mdl-35211191

Palabras clave

WUDAPT; local climate zones; malaria; random forest modeling; sub-Saharan africa; urban health; urban malaria modeling

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prevalence_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Environ Res Lett Año: 2020 Tipo del documento: Article País de afiliación: Bélgica

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google