Wikindx Resources

Journal Article: BibTeX citation key:  Ermert2013a
Ermert, V., Fink, A. H. & Paeth, H. (2013) Revisiting the potential effects of climate change on malaria transmission in Africa using regionalised climate projections. IN Climatic Change, 120. 741–754.
Added by: Andreas Fink 2013-08-10 11:38:48    Last Edited by: Andreas Fink 2013-09-27 11:25:07
 B  
Categories: General
Creators: Ermert, Fink, Paeth
Collection: Climatic Change

Peer reviewed
Number of views:  626
Popularity index:  33.05%

 
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 theMapping 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 twomodels. 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.
Added by: Andreas Fink    Last Edited by: Andreas Fink