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Climate Variability and Malaria over West Africa
被引:26
作者:
Diouf, Ibrahima
[1
,2
]
Rodriguez Fonseca, Belen
[3
,4
]
Caminade, Cyril
[5
,6
]
Thiaw, Wassila M.
[1
]
Deme, Abdoulaye
[7
]
Morse, Andrew P.
[6
,8
]
Ndione, Jacques-Andre
[9
]
Gaye, Amadou Thierno
[2
]
Diaw, Anta
[10
]
Ndiaye, Marie Khemesse Ngom
[10
]
机构:
[1] NOAA, Ctr Weather & Climate Predict, 5830 Univ Res Court, College Pk, MD 20740 USA
[2] Univ Cheikh Anta Diop, Ecole Super Polytech, Lab Phys Atmosphere & Ocean Simeon Fongang, Dakar, Senegal
[3] Univ Complutense Madrid, Dept Geophys & Meteorol, Madrid, Spain
[4] CSIC, Agencia Estatal, UCM, Inst Geociencias IGEO, Madrid, Spain
[5] Univ Liverpool, Inst Infect & Global Hlth, Dept Epidemiol & Populat Hlth, Liverpool, Merseyside, England
[6] Natl Inst Hlth Res M1 NIHR, Hlth Protect Res Unit Emerging & Zoonot Infect, Liverpool, Merseyside, England
[7] Univ Gaston Berger, Unite Format & Rech Sci Appl & Technol, St Louis, Senegal
[8] Univ Liverpool, Sch Environm Sci, Dept Geog & Planning, Liverpool, Merseyside, England
[9] Ctr Suivi Ecol, Dakar, Senegal
[10] Minist Hlth & Social Act, Gen Direct Publ Hlth, Dakar, Senegal
关键词:
ANOPHELES-GAMBIAE;
HOLOENDEMIC AREA;
SAHEL DROUGHT;
EL-NINO;
RAINFALL;
TRANSMISSION;
CHILDREN;
BURDEN;
IMPACT;
RISK;
D O I:
10.4269/ajtmh.19-0062
中图分类号:
R1 [预防医学、卫生学];
学科分类号:
1004 ;
120402 ;
摘要:
Malaria is a major public health problem in West Africa. Previous studies have shown that climate variability significantly affects malaria transmission. The lack of continuous observed weather station data and the absence of surveillance data for malaria over long periods have led to the use of reanalysis data to drive malaria models. In this study, we use the Liverpool Malaria Model (LMM) to simulate spatiotemporal variability of malaria in West Africa using daily rainfall and temperature from the following: Twentieth Century Reanalysis (20th CR), National Center for Environmental Prediction (NCEP), European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis of the Twentieth Century (ERA20C), and interim ECMWF Re-Analysis (ERA-Interim). Malaria case data from the national surveillance program in Senegal are used for model validation between 2001 and 2016. The warm temperatures found over the Sahelian fringe of West Africa can lead to high malaria transmission during wet years. The rainfall season peaks in July to September over West Africa and Senegal, and the malaria season lasts from September to November, about 1-2 months after the rainfall peak. The long-term trends exhibit interannual and decadal variabilities. The LMM shows acceptable performance in simulating the spatial distribution of malaria incidence. However, some discrepancies are found. These results are useful for decision-makers who plan public health and control measures in affected West African countries. The study would have substantial implications for directing malaria surveillance activities and health policy. In addition, this malaria modeling framework could lead to the development of an early warning system for malaria in West Africa.
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页码:1037 / 1047
页数:11
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