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A weather-driven model of malaria transmission

BACKGROUND: Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. METHODS: This paper describes a mathematical-biological model of the parasite dynamics, comprising both the...

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Detalles Bibliográficos
Autores principales: Hoshen, Moshe B, Morse, Andrew P
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC520827/
https://www.ncbi.nlm.nih.gov/pubmed/15350206
http://dx.doi.org/10.1186/1475-2875-3-32
Descripción
Sumario:BACKGROUND: Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission. METHODS: This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages. RESULTS: Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection. CONCLUSION: A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.