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Predictive risk mapping of schistosomiasis in Brazil using Bayesian geostatistical models

Scholte, Ronaldo G. C. and Gosoniu, Laura and Malone, John B. and Chammartin, Frédérique and Utzinger, Jürg and Vounatsou, Penelope. (2014) Predictive risk mapping of schistosomiasis in Brazil using Bayesian geostatistical models. Acta tropica, 132. pp. 57-63.

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Official URL: http://edoc.unibas.ch/dok/A6243558

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Abstract

Schistosomiasis is one of the most common parasitic diseases in tropical and subtropical areas, including Brazil. A national control programme was initiated in Brazil in the mid-1970s and proved successful in terms of morbidity control, as the number of cases with hepato-splenic involvement was reduced significantly. To consolidate control and move towards elimination, there is a need for reliable maps on the spatial distribution of schistosomiasis, so that interventions can target communities at highest risk. The purpose of this study was to map the distribution of Schistosoma mansoni in Brazil. We utilized readily available prevalence data from the national schistosomiasis control programme for the years 2005-2009, derived remotely sensed climatic and environmental data and obtained socioeconomic data from various sources. Data were collated into a geographical information system and Bayesian geostatistical models were developed. Model-based maps identified important risk factors related to the transmission of S. mansoni and confirmed that environmental variables are closely associated with indices of poverty. Our smoothed predictive risk map, including uncertainty, highlights priority areas for intervention, namely the northern parts of North and Southeast regions and the eastern part of Northeast region. Our predictive risk map provides a useful tool for to strengthen existing surveillance-response mechanisms.
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) > Department of Epidemiology and Public Health (EPH) > Eco System Health Sciences > Health Impact Assessment (Utzinger)
UniBasel Contributors:Utzinger, Jürg and Vounatsou, Penelope
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:Elsevier Science Publ.
ISSN:0001-706X
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:25 Oct 2017 05:24
Deposited On:15 Aug 2014 07:16

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