作者: Ibrahima Diouf , Roberto Suárez-Moreno , Belen Rodríguez-Fonseca , Cyril Caminade , Malick Wade
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摘要: Climate variability is a key factor in driving malaria outbreaks. As shown in previous studies, climate-driven malaria modeling provides a better understanding of malaria transmission dynamics, generating malaria-related parameters validated as a reliable benchmark to assess the impact of climate on malaria. In this framework, the present study uses climate observations and reanalysis products to evaluate the predictability of malaria incidence in West Africa. Sea surface temperatures (SSTs) are shown as a skillful predictor of malaria incidence, which is derived from climate-driven simulations with the Liverpool Malaria Model (LMM). Using the SST-based Statistical Seasonal Forecast model (S4CAST) tool, we find robust modes of anomalous SST variability associated with skillful predictability of malaria incidence Accordingly, significant SST anomalies in the tropical Pacific and Atlantic Ocean basins are …