{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T11:49:46Z","timestamp":1774612186521,"version":"3.50.1"},"reference-count":0,"publisher":"PAGEPress Publications","issue":"1","license":[{"start":{"date-parts":[[2015,6,3]],"date-time":"2015-06-03T00:00:00Z","timestamp":1433289600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Geospat Health"],"abstract":"<jats:p>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 &lt;em&gt;Schistosoma mansoni&lt;\/em&gt; among school-aged children in four regions of western C\u00f4te d\u2019Ivoire; ii) to determine demographic, climatic and environmental factors that influence the distribution of &lt;em&gt;S. mansoni&lt;\/em&gt;; 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 &lt;em&gt;S. mansoni&lt;\/em&gt; 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 &lt;em&gt;S. mansoni&lt;\/em&gt; 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 &lt;em&gt;S. mansoni&lt;\/em&gt; infection. The &lt;em&gt;S. mansoni&lt;\/em&gt; risk map presented here is being been used by the national schistosomiasis control programme for spatial targeting of praziquantel and other interventions.<\/jats:p>","DOI":"10.4081\/gh.2015.345","type":"journal-article","created":{"date-parts":[[2015,6,10]],"date-time":"2015-06-10T09:02:07Z","timestamp":1433926927000},"source":"Crossref","is-referenced-by-count":20,"title":["The spatial distribution of Schistosoma mansoni infection in four regions of western C\u00f4te d\u2019Ivoire"],"prefix":"10.4081","volume":"10","author":[{"given":"Rufin K.","family":"Assar\u00e9","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying-Si","family":"Lai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahoua","family":"Yapi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yves-Nathan T.","family":"Tian-Bi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mamadou","family":"Ouattara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick K.","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefanie","family":"Knopp","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Penelope","family":"Vounatsou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00fcrg","family":"Utzinger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eli\u00e9zer K.","family":"N'Goran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2549","published-online":{"date-parts":[[2015,6,3]]},"container-title":["Geospatial Health"],"original-title":[],"link":[{"URL":"http:\/\/www.geospatialhealth.net\/index.php\/gh\/article\/viewFile\/345\/322","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2016,5,18]],"date-time":"2016-05-18T06:15:02Z","timestamp":1463552102000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.geospatialhealth.net\/index.php\/gh\/article\/view\/345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,6,3]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,5,18]]}},"URL":"https:\/\/doi.org\/10.4081\/gh.2015.345","relation":{},"ISSN":["1970-7096","1827-1987"],"issn-type":[{"value":"1970-7096","type":"electronic"},{"value":"1827-1987","type":"print"}],"subject":[],"published":{"date-parts":[[2015,6,3]]}}}