Shifting suitability for malaria vectors across Africa with warming climates.
BACKGROUND
Climates are changing rapidly, producing warm climate conditions globally not previously observed in modern history. Malaria is of great concern as a cause of human mortality and morbidity, particularly across Africa, thanks in large part to the presence there of a particularly competent suite of mosquito vector species.


METHODS
I derive spatially explicit estimates of human populations living in regions newly suitable climatically for populations of two key Anopheles gambiae vector complex species in Africa over the coming 50 years, based on ecological niche model projections over two global climate models, two scenarios of climate change, and detailed spatial summaries of human population distributions.


RESULTS
For both species, under all scenarios, given the changing spatial distribution of appropriate conditions and the current population distribution, the models predict a reduction of 11.3-30.2% in the percentage of the overall population living in areas climatically suitable for these vector species in coming decades, but reductions and increases are focused in different regions: malaria vector suitability is likely to decrease in West Africa, but increase in eastern and southern Africa.


CONCLUSIONS
Climate change effects on African malaria vectors shift their distributional potential from west to east and south, which has implications for overall numbers of people exposed to these vector species. Although the total is reduced, malaria is likely to pose novel public health problems in areas where it has not previously been common.
Peterson
A Townsend
AT
Biodiversity Research Center, The University of Kansas, Lawrence, Kansas 66045, USA. town@ku.edu.
D000349:Africa / Q000453:epidemiology; D000465:Algorithms; D000818:Animals; D000852:Anopheles / Q000254:growth & development*; D005843:Geography; D017752:Greenhouse Effect; D006801:Humans; D007303:Insect Vectors / Q000254:growth & development*; D008288:Malaria / Q000453:epidemiology*; D008954:Models, Biological; D011156:Population Density