Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist

Raso, Giovanna and Vounatsou, Penelope and McManus, Donald P. and Utzinger, Jürg (2007) Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist. Geospatial health , 2 (1). pp. 85-96. ISSN 1970-7096

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Abstract

There is growing interest in the use of Bayesian geostatistical models for predicting the spatial distribution of parasitic infections, including hookworm, Schistosoma mansoni and co-infections with both parasites. The aim of this study was to predict the spatial distribution of mono-infections with either hookworm or S. mansoni in a setting where both parasites co-exist. School-based cross-sectional parasitological and questionnaire surveys were carried out in 57 rural schools in the Man region, western Côte d’Ivoire. A single stool specimen was obtained from each schoolchild attending grades 3-5. Stool specimens were processed by the Kato-Katz technique and an ether concentration method and examined for the presence of hookworm and S. mansoni eggs. The combined results from the two diagnostic approaches were considered for the infection status of each child. Demographic data (i.e. age and sex) were obtained from readily available school registries. Each child’s socio-economic status was estimated, using the questionnaire data following a household-based asset approach. Environmental data were extracted from satellite imagery. The different data sources were incorporated into a geographical information system. Finally, a Bayesian spatial multinomial regression model was constructed and the spatial patterns of S. mansoni and hookworm mono-infections were investigated using Bayesian kriging. Our approach facilitated the production of smooth risk maps for hookworm and S. mansoni mono-infections that can be utilized for targeting control interventions. We argue that in settings where S. mansoni and hookworm co-exist and control efforts are under way, there is a need for both mono- and co-infection risk maps to enhance the cost-effectiveness of control programmes

Item Type:	Article
Uncontrolled Keywords:	Hookworm, schistosomiasis, Schistosoma mansoni, geographical information system, risk mapping, coinfection, Bayesian geostatistics, Côte d’Ivoire
Subjects:	600 Tecnologia - Scienze applicate > 610 Medicina e salute (Classificare qui la tecnologia dei servizi medici) > 614 Medicina legale; incidenza delle malattie; Medicina preventiva pubblica > 614.4 Incidenza delle malattie e misure pubblica per prevenirle (classificare qui l'Epidemiologia, l'Epidemiologia clinica) > 614.42 Incidenza delle malattie, e misure pubbliche per prevenirle. Incidenza (classificare qui la prevalenza; la Geografia medica; l'Epidemiologia spaziale; i rilevamenti sanitari) 900 Storia, Geografia e discipline ausiliarie > 910 Geografia e viaggi > 910.285 Geographic information systems
Depositing User:	Users 66 not found.
Date Deposited:	05 Jul 2010 10:39
Last Modified:	05 Jul 2010 10:39
URI:	http://eprints.bice.rm.cnr.it/id/eprint/2864

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