The control of epidemic malaria is a priority for the international health community and specific targets for the early detection and effective control of epidemics have been agreed1. Interannual climate variability is an important determinant of epidemics in parts of Africa2 where climate drives both mosquito vector dynamics and parasite development rates3. Hence, skilful seasonal climate forecasts may provide early warning of changes of risk in epidemic-prone regions. Here we discuss the development of a system to forecast probabilities of anomalously high and low malaria incidence with dynamically based, seasonal-timescale, multi-model ensemble predictions of climate, using leading global coupled ocean–atmosphere climate models developed in Europe. This forecast system is successfully applied to the prediction of malaria risk in Botswana, where links between malaria and climate variability are well established4, adding up to four months lead time over malaria warnings issued with observed precipitation and having a comparably high level of probabilistic prediction skill. In years in which the forecast probability distribution is different from that of climatology, malaria decision-makers can use this information for improved resource allocation.
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We thank the WHO-AFRO Southern Africa Inter-Country Malaria Team (SAMC) in Zimbabwe and the National Malaria Control Unit in Botswana for enabling this study. The work reported here is part of the EU-funded DEMETER and ENSEMBLES projects. It was additionally supported financially by the UK Department for International Development through the Malaria Knowledge Programme, Liverpool School of Tropical Medicine, UK, and by a cooperative agreement from the US National Oceanic and Atmospheric Administration. The authors acknowledge considerable technical support from ECMWF staff and consultants, in particular from the Seasonal Forecast Section. The views herein contained are those of the authors and do not necessarily reflect the views of WHO, DfID, EU, NOAA or any of their sub-agencies.
Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.
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Thomson, M., Doblas-Reyes, F., Mason, S. et al. Malaria early warnings based on seasonal climate forecasts from multi-model ensembles. Nature 439, 576–579 (2006). https://doi.org/10.1038/nature04503
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