The potential effects of climate change on malaria transmission in Africa using bias-corrected regionalised climate projections and a simple malaria seasonality model |
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| Authors: | Volker Ermert Andreas H Fink Heiko Paeth |
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| Institution: | 1. Institute of Geophysics and Meteorology, University of Cologne, Kerpener Stra?e 13, 50923, Cologne, Germany
2. Institute of Geography, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
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| Abstract: | Climatic conditions such as relatively cold temperatures and dryness are able to limit malaria transmission. Climate change is therefore expected to alter malaria spread. A previous assessment of the potential impacts of climate change on the seasonality of malaria in Africa is revisited. Bias-corrected regional climate projections with a horizontal resolution of 0.5° are used from the Regional Model (REMO), which include land use and land cover changes. The malaria model employed is the climate-driven seasonality model (MSM) from the Mapping Malaria Risk in Africa project for which a comparison with data from the Malaria Atlas Project (MAP) and the Liverpool Malaria Model (LMM), and a novel validation procedure lends more credence to results. For climate scenarios A1B and B1 and for 2001–2050, REMO projects an overall drying and warming trend in the African malaria belt, that is largely imposed by the man-made degradation of vegetation. As a result, the malaria projections of the MSM show a decreased length of the malaria season in West Africa. The northern Sahel is no more longer suitable for malaria in the projections and shorter malaria seasons are expected for various areas farther south. In East Africa, higher temperatures and nearly unchanged precipitation patterns lead to longer transmission seasons and an increase in highland malaria. Assuming constant population numbers, an overall increase in person-months of exposure of up to 6 % is found. The results of this simple seasonality model are similar to previous projections from the more complex LMM. However, a different response to the warming of highlands is found for the two models. It is concluded that the MSM is an efficient tool to assess the climate-driven malaria seasonality and that an uncertainty analysis of future malaria spread would benefit from a multi-model approach. |
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