Better prediction of malaria at local levels

Fine-scale climate model projections suggest the possibility that population centres in cool, highland regions of East Africa could be more vulnerable to malaria than previously thought, while population centres in hot, lowland areas could be less vulnerable, according to a study published in Climatic Change. The team of researchers from Penn State University and the ISGlobal research centre CRESIB applied a statistical technique to conventional, coarse-scale climate models to better predict malaria dynamics at local levels.

"Malaria predictions using global climate model simulation results don't necessarily tell you what's going to happen at a specific location. What is likely to happen in one location can be very different from another location just 50 miles down the road. To really understand the impact of climate change on malaria dynamics we need to adopt a higher-resolution approach", said Matthew Thomas, Penn State researcher and coordinator of the study.

The ability of mosquitoes to transmit malaria is strongly influenced by environmental temperature. "Malaria mosquitoes are ectothermic organisms, which means that their body temperature matches the temperature of their direct surroundings," states Krijn Paaijmans, first author of the study and researcher at ISGlobal.

The scientists examined how changes in temperature due to future climate warming might impact the potential for mosquitoes to transmit malaria in four locations in Kenya that differed in their baseline environmental characteristics. The team used a statistical technique to "downscale" projections from conventional global climate models to generate high-resolution, daily temperature data. Then, using a simple mathematical model that describes the influence of temperature on the ability of adult mosquitoes to transmit malaria parasites, they compared the predictions obtained in the four locations with the predictions from the coarse-scale model simulations.

The team found that downscaled model results predicted large increases in future malaria transmission potential in the cool upland sites, but reduced transmission in the hot savannah-like site. According to the researchers, the warm lower-altitude site is characterized by relatively consistent, year-round transmission, so even modest increases in transmission potential may translate into measurable changes in disease risk. "Fine-scale predictions of malaria risk will be better tailored to the needs of local communities and can improve local adaptation and mitigation strategies," Paaijmans said.

Reference:

KP Paaijmans, JI Blanford, RG Crane, ME Mann, L Ning, KV Schreiber & MB Thomas. Downscaling reveals diverse effects of anthropogenic climate warming on the potential for local environments to support malaria transmission. Climatic Change, 2014, in press, DOI 10.1007/s10584-014-1172-6

More info: http://news.psu.edu/story/319877/2014/07/02/research/fine-scale-climate-model-projections-predict-malaria-local-levels