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Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors

BACKGROUND: Active trachoma is not uniformly distributed in endemic areas, and local environmental factors influencing its prevalence are not yet adequately understood. Determining whether clustering is a consistent phenomenon may help predict likely modes of transmission and help to determine the a...

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Autores principales: Hägi, Mathieu, Schémann, Jean-François, Mauny, Frédéric, Momo, Germain, Sacko, Doulaye, Traoré, Lamine, Malvy, Denis, Viel, Jean-François
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2799671/
https://www.ncbi.nlm.nih.gov/pubmed/20087414
http://dx.doi.org/10.1371/journal.pntd.0000583
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author Hägi, Mathieu
Schémann, Jean-François
Mauny, Frédéric
Momo, Germain
Sacko, Doulaye
Traoré, Lamine
Malvy, Denis
Viel, Jean-François
author_facet Hägi, Mathieu
Schémann, Jean-François
Mauny, Frédéric
Momo, Germain
Sacko, Doulaye
Traoré, Lamine
Malvy, Denis
Viel, Jean-François
author_sort Hägi, Mathieu
collection PubMed
description BACKGROUND: Active trachoma is not uniformly distributed in endemic areas, and local environmental factors influencing its prevalence are not yet adequately understood. Determining whether clustering is a consistent phenomenon may help predict likely modes of transmission and help to determine the appropriate level at which to target control interventions. The aims of this study were, therefore, to disentangle the relative importance of clustering at different levels and to assess the respective role of individual, socio-demographic, and environmental factors on active trachoma prevalence among children in Mali. METHODOLOGY/PRINCIPAL FINDINGS: We used anonymous data collected during the Mali national trachoma survey (1996–1997) at different levels of the traditional social structure (14,627 children under 10 years of age, 6,251 caretakers, 2,269 households, 203 villages). Besides field-collected data, environmental variables were retrieved later from various databases at the village level. Bayesian hierarchical logistic models were fit to these prevalence and exposure data. Clustering revealed significant results at four hierarchical levels. The higher proportion of the variation in the occurrence of active trachoma was attributable to the village level (36.7%), followed by household (25.3%), and child (24.7%) levels. Beyond some well-established individual risk factors (age between 3 and 5, dirty face, and flies on the face), we showed that caretaker-level (wiping after body washing), household-level (common ownership of radio, and motorbike), and village-level (presence of a women's association, average monthly maximal temperature and sunshine fraction, average annual mean temperature, presence of rainy days) features were associated with reduced active trachoma prevalence. CONCLUSIONS/SIGNIFICANCE: This study clearly indicates the importance of directing control efforts both at children with active trachoma as well as those with close contact, and at communities. The results support facial cleanliness and environmental improvements (the SAFE strategy) as population-health initiatives to combat blinding trachoma.
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spelling pubmed-27996712010-01-19 Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors Hägi, Mathieu Schémann, Jean-François Mauny, Frédéric Momo, Germain Sacko, Doulaye Traoré, Lamine Malvy, Denis Viel, Jean-François PLoS Negl Trop Dis Research Article BACKGROUND: Active trachoma is not uniformly distributed in endemic areas, and local environmental factors influencing its prevalence are not yet adequately understood. Determining whether clustering is a consistent phenomenon may help predict likely modes of transmission and help to determine the appropriate level at which to target control interventions. The aims of this study were, therefore, to disentangle the relative importance of clustering at different levels and to assess the respective role of individual, socio-demographic, and environmental factors on active trachoma prevalence among children in Mali. METHODOLOGY/PRINCIPAL FINDINGS: We used anonymous data collected during the Mali national trachoma survey (1996–1997) at different levels of the traditional social structure (14,627 children under 10 years of age, 6,251 caretakers, 2,269 households, 203 villages). Besides field-collected data, environmental variables were retrieved later from various databases at the village level. Bayesian hierarchical logistic models were fit to these prevalence and exposure data. Clustering revealed significant results at four hierarchical levels. The higher proportion of the variation in the occurrence of active trachoma was attributable to the village level (36.7%), followed by household (25.3%), and child (24.7%) levels. Beyond some well-established individual risk factors (age between 3 and 5, dirty face, and flies on the face), we showed that caretaker-level (wiping after body washing), household-level (common ownership of radio, and motorbike), and village-level (presence of a women's association, average monthly maximal temperature and sunshine fraction, average annual mean temperature, presence of rainy days) features were associated with reduced active trachoma prevalence. CONCLUSIONS/SIGNIFICANCE: This study clearly indicates the importance of directing control efforts both at children with active trachoma as well as those with close contact, and at communities. The results support facial cleanliness and environmental improvements (the SAFE strategy) as population-health initiatives to combat blinding trachoma. Public Library of Science 2010-01-19 /pmc/articles/PMC2799671/ /pubmed/20087414 http://dx.doi.org/10.1371/journal.pntd.0000583 Text en Hägi 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
Hägi, Mathieu
Schémann, Jean-François
Mauny, Frédéric
Momo, Germain
Sacko, Doulaye
Traoré, Lamine
Malvy, Denis
Viel, Jean-François
Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors
title Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors
title_full Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors
title_fullStr Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors
title_full_unstemmed Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors
title_short Active Trachoma among Children in Mali: Clustering and Environmental Risk Factors
title_sort active trachoma among children in mali: clustering and environmental risk factors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2799671/
https://www.ncbi.nlm.nih.gov/pubmed/20087414
http://dx.doi.org/10.1371/journal.pntd.0000583
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