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Chapitre D'ouvrage Année : 2019

Predicting climate impacts on health at sub-seasonal to seasonal timescales.

Résumé

The potential to use sub-seasonal to seasonal (S2S) prediction systems for outcomes in health is presented, using four case studies of malaria, dengue, heat waves, and meningococcal meningitis. While promising, many such applications are currently in the demonstration phase, and examples of operationalizing S2S-based early warning systems, fully integrated with decision support, have yet to emerge. Potential reasons for this operationalization bottleneck are discussed, which include restrictions on open access to health and climate data, the unfulfilled requirement for training in the use of such systems, and the mismatch between the prediction paradigm and the decision entry points in health-planning systems. The S2S project sponsored by the World Meteorological Organization may help to demonstrate the potential application of climate information, but the lack of real-time access inhibits the operationalization of evaluated systems. It is recommended that partnership platforms, established through the Global Framework for Climate Services and related mechanisms, enable the climate and health academic and operational communities to work together on real-time provision and assessment of health early warning systems. This is particularly important in developing countries where climate-driven health outcomes can be severe.
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Dates et versions

hal-03373284 , version 1 (11-10-2021)

Identifiants

Citer

Adrian M. Tompkins, Rachel Lowe, Hannah Nissan, Nadège Martiny, Pascal Roucou, et al.. Predicting climate impacts on health at sub-seasonal to seasonal timescales.. A.W. Robertson & F. Vitart. Sub-Seasonal to Seasonal Prediction - The Gap Between Weather and Climate Forecasting, Elsevier, pp.455-477, 2019, 978-0-12-811714-9. ⟨10.1016/B978-0-12-811714-9.00022-X⟩. ⟨hal-03373284⟩
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