The spatial distribution of Schistosoma mansoni infection in four regions of western Cote d'Ivoire

被引:26
作者
Assare, Rufin K. [1 ,4 ]
Lai, Ying-Si [1 ,2 ]
Yapi, Ahoua [3 ]
Tian-Bi, Yves-Nathan T. [3 ]
Ouattara, Mamadou [3 ]
Yao, Patrick K. [3 ]
Knopp, Stefanie [1 ,2 ,5 ]
Vounatsou, Penelope [1 ,2 ]
Utzinger, Juerg [1 ,2 ]
N'Goran, Eliezer K. [3 ,4 ]
机构
[1] Swiss Trop & Publ Hlth Inst, Dept Epidemiol & Publ Hlth, CH-4002 Basel, Switzerland
[2] Univ Basel, Basel, Switzerland
[3] Univ Felix Houphouet Boigny, Unite Format & Rech Biosci, Abidjan, Cote Ivoire
[4] Ctr Suisse Rech Sci Cote Ivoire, Abidjan, Cote Ivoire
[5] Nat Hist Museum, Dept Life Sci, Wolfson Wellcome Biomed Labs, London SW7 5BD, England
基金
比尔及梅琳达.盖茨基金会;
关键词
Bayesian geostatistical analysis; Cote d'Ivoire; Geographical information system; Remote sensing; Schistosomiasis; KATO-KATZ TECHNIQUE; DAY-TO-DAY; BIOMPHALARIA-PFEIFFERI; INTERMEDIATE HOST; RISK PREDICTION; GLOBAL BURDEN; DISEASE; HOOKWORM; SCHOOLCHILDREN; EPIDEMIOLOGY;
D O I
10.4081/gh.2015.345
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Schistosomiasis poses a considerable public health burden in sub-Saharan Africa and a sound understanding of the spatial distribution facilitates to better target control interventions. The objectives of this study were i) to assess the prevalence of Schistosoma mansoni among school-aged children in four regions of western Cote d'Ivoire; ii) to determine demographic, climatic and environmental factors that influence the distribution of S. mansoni; and iii) to map and predict the distribution of S. mansoni in non-sampled locations. Parasitological surveys were carried out in 264 schools from June to December 2011. In each school, we aimed to examine 50 children for S. mansoni infection using duplicate Kato-Katz thick smears. Schools were georeferenced using a hand-held global positioning system receiver. Demographic data were obtained from readily available school lists, while climatic and environmental data were extracted from open-access remote sensing databases. Multivariable, binary non-spatial models and a Bayesian geostatistical logistic regression model were used to identify demographic, climatic and environmental risk factors for S. mansoni infection. Risk maps were developed based on observed S. mansoni prevalences and using Bayesian geostatistical models to predict prevalences at non-sampled locations. Overall, 12,462 children provided a sufficiently large stool sample to perform at least one Kato-Katz thick smear. The observed overall prevalence of S. mansoni infection was 39.9%, ranging from 0 to 100% at the unit of the school. Bayesian geostatistical analysis revealed that age, sex, altitude and difference between land surface temperature at day and night were significantly associated with S. mansoni infection. The S. mansoni risk map presented here is being been used by the national schistosomiasis control programme for spatial targeting of praziquantel and other interventions.
引用
收藏
页码:69 / 79
页数:11
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