Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium - Schistosoma mansoni Co-distribution in Côte d'Ivoire: e3407
Background Schistosoma haematobium and Schistosoma mansoni are blood flukes that cause urogenital and intestinal schistosomiasis, respectively. In Côte d'Ivoire, both species are endemic and control efforts are being scaled up. Accurate knowledge of the geographical distribution, including del...
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creator | Chammartin, Frédérique Houngbedji, Clarisse A Hürlimann, Eveline Yapi, Richard B Silué, Kigbafori D Soro, Gotianwa Kouamé, Ferdinand N N'Goran, Eliézer K Utzinger, Jürg Raso, Giovanna Vounatsou, Penelope |
description | Background Schistosoma haematobium and Schistosoma mansoni are blood flukes that cause urogenital and intestinal schistosomiasis, respectively. In Côte d'Ivoire, both species are endemic and control efforts are being scaled up. Accurate knowledge of the geographical distribution, including delineation of high-risk areas, is a central feature for spatial targeting of interventions. Thus far, model-based predictive risk mapping of schistosomiasis has relied on historical data of separate parasite species. Methodology We analyzed data pertaining to Schistosoma infection among school-aged children obtained from a national, cross-sectional survey conducted between November 2011 and February 2012. More than 5,000 children in 92 schools across Côte d'Ivoire participated. Bayesian geostatistical multinomial models were developed to assess infection risk, including S. haematobium-S. mansoni co-infection. The predicted risk of schistosomiasis was utilized to estimate the number of children that need preventive chemotherapy with praziquantel according to World Health Organization guidelines. Principal Findings We estimated that 8.9% of school-aged children in Côte d'Ivoire are affected by schistosomiasis; 5.3% with S. haematobium and 3.8% with S. mansoni. Approximately 2 million annualized praziquantel treatments would be required for preventive chemotherapy at health districts level. The distinct spatial patterns of S. haematobium and S. mansoni imply that co-infection is of little importance across the country. Conclusions/Significance We provide a comprehensive analysis of the spatial distribution of schistosomiasis risk among school-aged children in Côte d'Ivoire and a strong empirical basis for a rational targeting of control interventions. |
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In Côte d'Ivoire, both species are endemic and control efforts are being scaled up. Accurate knowledge of the geographical distribution, including delineation of high-risk areas, is a central feature for spatial targeting of interventions. Thus far, model-based predictive risk mapping of schistosomiasis has relied on historical data of separate parasite species. Methodology We analyzed data pertaining to Schistosoma infection among school-aged children obtained from a national, cross-sectional survey conducted between November 2011 and February 2012. More than 5,000 children in 92 schools across Côte d'Ivoire participated. Bayesian geostatistical multinomial models were developed to assess infection risk, including S. haematobium-S. mansoni co-infection. The predicted risk of schistosomiasis was utilized to estimate the number of children that need preventive chemotherapy with praziquantel according to World Health Organization guidelines. Principal Findings We estimated that 8.9% of school-aged children in Côte d'Ivoire are affected by schistosomiasis; 5.3% with S. haematobium and 3.8% with S. mansoni. Approximately 2 million annualized praziquantel treatments would be required for preventive chemotherapy at health districts level. The distinct spatial patterns of S. haematobium and S. mansoni imply that co-infection is of little importance across the country. Conclusions/Significance We provide a comprehensive analysis of the spatial distribution of schistosomiasis risk among school-aged children in Côte d'Ivoire and a strong empirical basis for a rational targeting of control interventions.</description><identifier>ISSN: 1935-2727</identifier><identifier>EISSN: 1935-2735</identifier><identifier>DOI: 10.1371/journal.pntd.0003407</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Chemotherapy ; Estimates ; Infections ; Mollusks ; Morbidity ; Parasites ; Public health ; Studies ; Tropical diseases</subject><ispartof>PLoS neglected tropical diseases, 2014-12, Vol.8 (12)</ispartof><rights>2014 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Co-distribution in Côte d?Ivoire. PLoS Negl Trop Dis 8(12): e3407. doi:10.1371/journal.pntd.0003407</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,861,27905,27906</link.rule.ids></links><search><creatorcontrib>Chammartin, Frédérique</creatorcontrib><creatorcontrib>Houngbedji, Clarisse A</creatorcontrib><creatorcontrib>Hürlimann, Eveline</creatorcontrib><creatorcontrib>Yapi, Richard B</creatorcontrib><creatorcontrib>Silué, Kigbafori D</creatorcontrib><creatorcontrib>Soro, Gotianwa</creatorcontrib><creatorcontrib>Kouamé, Ferdinand N</creatorcontrib><creatorcontrib>N'Goran, Eliézer K</creatorcontrib><creatorcontrib>Utzinger, Jürg</creatorcontrib><creatorcontrib>Raso, Giovanna</creatorcontrib><creatorcontrib>Vounatsou, Penelope</creatorcontrib><title>Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium - Schistosoma mansoni Co-distribution in Côte d'Ivoire: e3407</title><title>PLoS neglected tropical diseases</title><description>Background Schistosoma haematobium and Schistosoma mansoni are blood flukes that cause urogenital and intestinal schistosomiasis, respectively. In Côte d'Ivoire, both species are endemic and control efforts are being scaled up. Accurate knowledge of the geographical distribution, including delineation of high-risk areas, is a central feature for spatial targeting of interventions. Thus far, model-based predictive risk mapping of schistosomiasis has relied on historical data of separate parasite species. Methodology We analyzed data pertaining to Schistosoma infection among school-aged children obtained from a national, cross-sectional survey conducted between November 2011 and February 2012. More than 5,000 children in 92 schools across Côte d'Ivoire participated. Bayesian geostatistical multinomial models were developed to assess infection risk, including S. haematobium-S. mansoni co-infection. The predicted risk of schistosomiasis was utilized to estimate the number of children that need preventive chemotherapy with praziquantel according to World Health Organization guidelines. Principal Findings We estimated that 8.9% of school-aged children in Côte d'Ivoire are affected by schistosomiasis; 5.3% with S. haematobium and 3.8% with S. mansoni. Approximately 2 million annualized praziquantel treatments would be required for preventive chemotherapy at health districts level. The distinct spatial patterns of S. haematobium and S. mansoni imply that co-infection is of little importance across the country. 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In Côte d'Ivoire, both species are endemic and control efforts are being scaled up. Accurate knowledge of the geographical distribution, including delineation of high-risk areas, is a central feature for spatial targeting of interventions. Thus far, model-based predictive risk mapping of schistosomiasis has relied on historical data of separate parasite species. Methodology We analyzed data pertaining to Schistosoma infection among school-aged children obtained from a national, cross-sectional survey conducted between November 2011 and February 2012. More than 5,000 children in 92 schools across Côte d'Ivoire participated. Bayesian geostatistical multinomial models were developed to assess infection risk, including S. haematobium-S. mansoni co-infection. The predicted risk of schistosomiasis was utilized to estimate the number of children that need preventive chemotherapy with praziquantel according to World Health Organization guidelines. Principal Findings We estimated that 8.9% of school-aged children in Côte d'Ivoire are affected by schistosomiasis; 5.3% with S. haematobium and 3.8% with S. mansoni. Approximately 2 million annualized praziquantel treatments would be required for preventive chemotherapy at health districts level. The distinct spatial patterns of S. haematobium and S. mansoni imply that co-infection is of little importance across the country. Conclusions/Significance We provide a comprehensive analysis of the spatial distribution of schistosomiasis risk among school-aged children in Côte d'Ivoire and a strong empirical basis for a rational targeting of control interventions.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><doi>10.1371/journal.pntd.0003407</doi><oa>free_for_read</oa></addata></record> |
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subjects | Chemotherapy Estimates Infections Mollusks Morbidity Parasites Public health Studies Tropical diseases |
title | Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium - Schistosoma mansoni Co-distribution in Côte d'Ivoire: e3407 |
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