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

Assaré, Rufin K. and Lai, Ying-Si and Yapi, Ahoua and Tian-Bi, Yves-Nathan T. and Ouattara, Mamadou and Yao, Patrick K. and Knopp, Stefanie and Vounatsou, Penelope and Utzinger, Jürg and N'Goran, Eliézer K.. (2015) The spatial distribution of Schistosoma mansoni infection in four regions of western Côte d'Ivoire. Geospatial health, Vol. 10, H. 345. pp. 69-79.

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Official URL: http://edoc.unibas.ch/dok/A6391024

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Abstract

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 Côte 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.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Biostatistics > Bayesian Modelling and Analysis (Vounatsou)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Former Units within Swiss TPH > Health Impact Assessment (Utzinger)
UniBasel Contributors:Vounatsou, Penelope and Utzinger, Jürg
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:GnosisGIS
ISSN:1827-1987
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:03 Jul 2015 08:53
Deposited On:03 Jul 2015 08:53

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