{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T06:33:24Z","timestamp":1768286004185,"version":"3.49.0"},"reference-count":49,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2005,3,24]],"date-time":"2005-03-24T00:00:00Z","timestamp":1111622400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Parasitology"],"published-print":{"date-parts":[[2005,7]]},"abstract":"<jats:p>The objectives of this study were (1) to examine risk factors for <jats:italic>Schistosoma mansoni<\/jats:italic> infection among schoolchildren living in western C\u00f4te d'Ivoire, and (2) to carry forward spatial risk prediction and mapping at non-sampled locations. First, demographic and socio-economic data were obtained from 3818 children, aged 6\u201316 years, from 55 schools. Second, a single stool sample was examined from each child by the Kato-Katz technique to assess infection status of <jats:italic>S. mansoni<\/jats:italic> and its intensity. Third, remotely sensed environmental data were derived from satellite imagery and digitized ground maps. With these databases a comprehensive geographical information system was established. Bayesian variogram models were applied for spatial risk modelling and prediction. The infection prevalence of <jats:italic>S. mansoni<\/jats:italic> was 38\u00b79%, ranging from 0% to 89\u00b73% among schools. Results showed that age, sex, the richest wealth quintile, elevation and rainfall explained the geographical variation of the school prevalences of <jats:italic>S. mansoni<\/jats:italic> infection. The goodness of fit of different spatial models revealed that age, sex and socio-economic status had a stronger influence on infection prevalence than environmental covariates. The generated risk map can be used by decision-makers for the design and implementation of schistosomiasis control in this setting. If successfully validated elsewhere, this approach can guide control programmes quite generally.<\/jats:p>","DOI":"10.1017\/s0031182005007432","type":"journal-article","created":{"date-parts":[[2005,6,28]],"date-time":"2005-06-28T13:55:57Z","timestamp":1119966957000},"page":"97-108","source":"Crossref","is-referenced-by-count":114,"title":["Spatial risk prediction and mapping of <i>Schistosoma mansoni<\/i> infections among schoolchildren living in western C\u00f4te d'Ivoire"],"prefix":"10.1017","volume":"131","author":[{"given":"G.","family":"RASO","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B.","family":"MATTHYS","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"E. 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