Oceanic Influence on Seasonal Malaria Incidence in West Africa

被引:3
|
作者
Diouf, Ibrahima [1 ,9 ]
Suarez-Moreno, Roberto [2 ]
Rodriguez-Fonseca, Belen [3 ,4 ]
Caminade, Cyril [5 ]
Wade, Malick [6 ]
Thiaw, Wassila M. [1 ]
Deme, Abdoulaye [6 ]
Morse, Andrew P. [7 ]
Ndione, Jaques-Andre [8 ]
Gaye, Amadou T. [9 ]
Diaw, Anta [10 ]
Ndiaye, Marie Khemesse Ngom [10 ]
机构
[1] NOAA, Ctr Weather & Climate Predict, College Pk, MD 20740 USA
[2] Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY USA
[3] Univ Complutense Madrid, Fac Fis Dept Meteorol, Madrid, Spain
[4] Univ Complutense Madrid, Agencia Estatal Consejo Super Invest Cient, Inst Geociencias, Madrid, Spain
[5] Univ Liverpool, Inst Infect Vet & Ecol Sci, Dept Livestock & One Hlth, Liverpool, Merseyside, England
[6] Univ Gaston Berger, Unite Format & Rech Sci Appl & Technol, St Louis, Senegal
[7] Univ Liverpool, Sch Environm Sci, Dept Geog & Planning, Liverpool, Merseyside, England
[8] Ctr Suivi Ecol, Dakar, Senegal
[9] Univ Cheikh Anta Diop, Lab Phys Atmosphere & Ocean Simeon Fongang, Ecole Super Polytech, Dakar, Senegal
[10] Minist Hlth & Social Act, Gen Direct Publ Hlth, Dakar, Senegal
关键词
Atmosphere; Ocean; Africa; Climate prediction; Climate variability; Oceanic variability; NINO SOUTHERN-OSCILLATION; EL-NINO; EXTENDED RECONSTRUCTION; INTERDECADAL CHANGES; CLIMATE VARIABILITY; SAHEL RAINFALL; SST MODES; TEMPERATURE; ATLANTIC; PACIFIC;
D O I
10.1175/WCAS-D-20-0160.1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
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 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.
引用
收藏
页码:287 / 302
页数:16
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