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| Titel |
The potential effects of climate change on malaria in tropical Africa using regionalised climate projections |
| VerfasserIn |
V. Ermert, A. H. Fink, H. Paeth, A. P. Morse |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250059690
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| Zusammenfassung |
| The projected climate change will probably alter the range and transmission potential of
malaria in Africa. The potential impacts of climate change on the malaria distribution is
assessed for tropical Africa. 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 models employed are the 2010 version
of the Liverpool Malaria Model (LMM2010), the Garki model, the Plasmodium
falciparum infection model from Smith et al. (2005) (S2005), and the Malaria Seasonality
Model (MSM) from the Mapping Malaria Risk in Africa project. The results of
the models are compared with data from the Malaria Atlas Project (MAP) and
novel validation procedures for the LMM2010 and MSM lend more credence to their
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 show a
decreased malaria spread in West Africa. The northern Sahel is no more suitable for
malaria in the projections. More unstable malaria transmission and shorter malaria
seasons are expected for various areas farther south. An increase in the malaria
epidemic risk is found for more densely populated areas in the southern part of
the Sahel. In East Africa, higher temperatures and nearly unchanged precipitation
patterns lead to longer transmission seasons and an increase in the area of highland
malaria. For altitudes up to 2000Â m the malaria transmission stabilises and the
epidemic risk is reduced but for higher altitudes the risk of malaria epidemics is
increased.
The results of the more complex and simple malaria models are similar to each other.
However, a different response to the warming of highlands is found for the LMM2010 and
MSM. This shows the requirement of a multi model uncertainty analysis for the projection of
the future malaria spread. |
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