Climate change and infectious diseases: Can we meet the needs for better prediction?

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch Climatic Change DOI 10.1007/s10584-013-0744-1 Electronic supplementary material The online version of this article (doi:10.1007/s10584-013-0744-1) contains supplementary material, which is available to authorized users. X. Rodó : F. J. Doblas-Reyes Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys, 23, 08005 Barcelona, Catalunya, Spain X. Rodó (*) : F. J. Doblas-Reyes :M.-À. Rodríguez-Arias : J. García-Serrano Institut Català de Ciències del Clima (IC3), c/Doctor Trueta 203, 3rd, 08005 Barcelona, Catalunya, Spain e-mail: [email protected] M. Pascual Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109-1048, USA A. Gershunov Climate, Atmospheric Science and Physical Oceanography, Scripps Institution of Oceanography, UC San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0224, USA D. A. Stone Scientific Computing Group, Berkeley Lab Computing Sciences, Lawrence Berkeley National Laboratory, Building 50B, 1 Cyclotron Road, Berkeley, CA 94720, USA F. Giorgi Earth System Physics Section, The Abdus Salam International Centre for Theoretical Physics, P.O. BOX 586, 34100 Trieste, Italy between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.