Impact of climate change on global malaria distribution

被引:357
作者
Caminade, Cyril [1 ,2 ]
Kovats, Sari [3 ]
Rocklov, Joacim [4 ]
Tompkins, Adrian M. [5 ]
Morse, Andrew P. [2 ]
Colon-Gonzalez, Felipe J. [5 ]
Stenlund, Hans [4 ]
Martens, Pim [6 ]
Lloyd, Simon J. [3 ]
机构
[1] Univ Liverpool, Dept Epidemiol & Populat Hlth, Inst Infect & Global Hlth, Liverpool L69 7ZT, Merseyside, England
[2] Univ Liverpool, Dept Geog & Planning, Sch Environm Sci, Liverpool L69 7ZT, Merseyside, England
[3] Univ London London Sch Hyg & Trop Med, Dept Social & Environm Hlth Res, London WC1E 7HT, England
[4] Umea Univ, Dept Publ Hlth & Clin Med Epidemiol & Global Hlth, S-90187 Umea, Sweden
[5] Abdus Salam Int Ctr Theoret Phys, I-34151 Trieste, Italy
[6] Maastricht Univ, NL-6211 LK Maastricht, Netherlands
关键词
global climate impacts; disease modeling; uncertainty; TRANSMISSION; MODEL; POPULATION; HEALTH; FUTURE;
D O I
10.1073/pnas.1302089111
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution.
引用
收藏
页码:3286 / 3291
页数:6
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