期刊
CLIMATIC CHANGE
卷 118, 期 3-4, 页码 625-640出版社
SPRINGER
DOI: 10.1007/s10584-013-0744-1
关键词
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资金
- La Caixa Foundation
- ENSEMBLES project [GOCE-CT-2003-505539]
- CIRCE-EUFP6
- NIH/NSF EID [0430120]
- NOAA
- EU
- European Commission [243964]
- DENFREE: DENgue research Framework for Resisting Epidemics in Europe of the EUFP7 programme project
- Direct For Biological Sciences
- Emerging Frontiers [0430120] Funding Source: National Science Foundation
- Direct For Education and Human Resources
- Division Of Graduate Education [1239797] Funding Source: National Science Foundation
- ICREA Funding Source: Custom
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.
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