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

16 páginas, 3 figuras.
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 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
FJDR received financial support from the ENSEMBLES project (GOCE-CT-2003-505539). Support for this work was also provided by CIRCE-EUFP6 to X.R., by NIH/NSF EID Grant 0430120 and a NOAA award to X.R., M.P., J.K. and A.J.D. J.G-S and X. Rodó wants to acknowledge support from the EU project QWeCI (Quantifying Weather and Climate Impacts on health in developing countries; funded by the European Commission’s Seventh Framework Research Programme under the grant agreement 243964). and the DENFREE: DENgue research Framework for Resisting Epidemics in Europe of the EUFP7 programme project. M. Pascual is an investigator of the Howard Hughes Medical Institute.