Impact of climate change on global malaria distribution
- Cyril Caminadea,b,1,
- Sari Kovatsc,
- Joacim Rocklovd,
- Adrian M. Tompkinse,
- Andrew P. Morseb,
- Felipe J. Colón-Gonzáleze,
- Hans Stenlundd,
- Pim Martensf, and
- Simon J. Lloydc
- aInstitute of Infection and Global Health, Department of Epidemiology and Population Health and
- bSchool of Environmental Sciences, Department of Geography and Planning, University of Liverpool, Liverpool L69 7ZT, United Kingdom;
- cDepartment of Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom;
- dDepartment of Public Health and Clinical Medicine, Epidemiology and Global Health, Umea University, 901 87 Umea, Sweden;
- eAbdus Salam International Centre for Theoretical Physics, I-34151Trieste, Italy; and
- fMaastricht University, 6211 LK, Maastricht, The Netherlands
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Edited by Hans Joachim Schellnhuber, Potsdam Institute for Climate Impact Research, Potsdam, Germany, and approved January 10, 2014 (received for review January 31, 2013)
Significance
This study is the first multimalaria model intercomparison exercise. This is carried out to estimate the impact of future climate change and population scenarios on malaria transmission at global scale and to provide recommendations for the future. Our results indicate that future climate might become more suitable for malaria transmission in the tropical highland regions. However, other important socioeconomic factors such as land use change, population growth and urbanization, migration changes, and economic development will have to be accounted for in further details for future risk assessments.
Abstract
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.
Footnotes
- ↵1To whom correspondence should be addressed. E-mail: Cyril.Caminade{at}liverpool.ac.uk.
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Author contributions: C.C., S.K., J.R., A.M.T., and A.P.M. designed research; C.C., A.M.T., and S.J.L. performed research; C.C., A.M.T., F.J.C.-G., H.S., and S.J.L. analyzed data; and C.C., S.K., J.R., A.M.T., and P.M. wrote the paper.
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The authors declare no conflict of interest.
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This article is a PNAS Direct Submission.
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This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1302089111/-/DCSupplemental.




