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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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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. |
format | Online Article Text |
id | pubmed-4270510 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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