Climate change and malaria: analysis of the SRES climate and socio-economic scenarios

The distribution and seasonal transmission of malaria is affected by climate, as both vector and parasite are sensitive to temperature. A global model ofmalaria transmission has been developed to estimate the potential impact of climate change on seasonal transmission and populations at risk ofthe disease (MIASMA v.2.2). ‘‘Population at risk’’ is defined as the population living in areas where climate conditions are suitable for malaria transmission. This assessment describes model simulations driven by the latest scenarios from the IPCC. The climate scenarios were derived from the Hadley Centre model HadCM3 runs with four SRES emissions scenarios: A1FI, A2, B1 and B2. The additional population at risk was determined under each ofthe SRES population scenarios by downscaling national estimates to the 0.5
0.5 scale grid and re-aggregating by region. Additional population at risk due to climate change are projected in East Africa, central Asia, China and areas around the southern limit of the distribution in South America. Decreases in the transmission season are indicated in many areas where reductions in precipitation are projected by the Hadley Centre model, such as the Amazon and in Central America. The outcomes ofthe malaria model are sensitive to (1) spatial distribution ofprecipitation projections and (2) population growth in those areas where there is new risk due to climate change. This paper describes a new method for describing vulnerability to the potential impacts of climate change. Countries were classified according to their current vulnerability and malaria control status using expert judgement. This vulnerability incorporates both socio-economic status, as a measure for adaptive capacity, and climate as malaria at the fringes of its climate-determined distribution is easier to control than malaria in tropical endemic regions. Thus, current malaria control status is used as an indicator ofadaptive capacity. For those countries that currently have a limited capacity to control the disease, the model estimates additional populations at risk by 2080s in the range of90 m (A1FI) to 200m (B2b). The greatest impact under B2 reflects population growth in risk areas in Eurasia and Africa. Climate-induced changes in the potential distribution of malaria is projected in the poor and vulnerable regions of the world. However, climate change is not likely to affect malaria transmission in the poorest countries where the climate is already highly favourable for transmission.