Using remote sensing environmental data to forecast malaria incidence at a rural district hospital in Western Kenya
Abstract Malaria surveillance data provide opportunity to develop forecasting models. Seasonal variability in environmental factors correlate with malaria transmission, thus the identification of transmission patterns is useful in developing prediction models. However, with changing seasonal transmi...
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Autores principales: | Maquins Odhiambo Sewe, Yesim Tozan, Clas Ahlm, Joacim Rocklöv |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2017
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Materias: | |
Acceso en línea: | https://doaj.org/article/aca57109d9bb4340a8df10ac5865201b |
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