Oceanic Influence on Seasonal Malaria Incidence in West Africa

Diouf, Ibrahima, Suarez-Moreno, Roberto, Rodriguez-Fonseca, Belen, Caminade, Cyril ORCID: 0000-0002-3846-7082, Wade, Malick, Thiaw, Wassila M, Deme, Abdoulaye, Morse, Andrew P ORCID: 0000-0002-0413-2065, Ndione, Jaques-Andre, Gaye, Amadou T
et al (show 2 more authors) (2022) Oceanic Influence on Seasonal Malaria Incidence in West Africa. WEATHER CLIMATE AND SOCIETY, 14 (1). pp. 287-302.

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<jats:title>Abstract</jats:title> <jats:p>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 related to a significant response of malaria incidence over West Africa. For the Mediterranean Sea, warm SST anomalies are responsible for increased surface air temperatures and precipitation over West Africa, resulting in higher malaria incidence; conversely, cold SST anomalies are responsible for decreased surface air temperatures and precipitation over West Africa, resulting in lower malaria incidence.. Our results put forward the key role of SST variability as a source of predictability of malaria incidence, being of paramount interest to decision-makers who plan public health measures against malaria in West Africa. Accordingly, SST anomalies could be used operationally to forecast malaria risk over West Africa for early warning systems.</jats:p>

Item Type: Article
Uncontrolled Keywords: Atmosphere, Ocean, Africa, Climate prediction, Climate variability, Oceanic variability
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences
Faculty of Science and Engineering > School of Environmental Sciences
Depositing User: Symplectic Admin
Date Deposited: 10 Jun 2022 09:01
Last Modified: 18 Jan 2023 21:15
DOI: 10.1175/WCAS-D-20-0160.1
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3147203