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Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire

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 delineat...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4270510/
https://www.ncbi.nlm.nih.gov/pubmed/25522007
http://dx.doi.org/10.1371/journal.pntd.0003407
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author 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
author_facet 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
author_sort Chammartin, Frédérique
collection PubMed
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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spelling pubmed-42705102014-12-26 Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire 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 PLoS Negl Trop Dis Research Article 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. Public Library of Science 2014-12-18 /pmc/articles/PMC4270510/ /pubmed/25522007 http://dx.doi.org/10.1371/journal.pntd.0003407 Text en © 2014 Chammartin et al http://creativecommons.org/licenses/by/4.0/ 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 properly credited.
spellingShingle Research Article
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
Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire
title Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire
title_full Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire
title_fullStr Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire
title_full_unstemmed Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire
title_short Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium–Schistosoma mansoni Co-distribution in Côte d′Ivoire
title_sort bayesian risk mapping and model-based estimation of schistosoma haematobium–schistosoma mansoni co-distribution in côte d′ivoire
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4270510/
https://www.ncbi.nlm.nih.gov/pubmed/25522007
http://dx.doi.org/10.1371/journal.pntd.0003407
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