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Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment

In recent decades, quantitative microbial risk assessment (QMRA) has been widely used to assess exposure to fecal microbes and associated health risks. In this study, a multipathway exposure assessment model was developed to evaluate exposure to fecal microbes for children under 5 in highly contamin...

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Autores principales: Wang, Yuke, Moe, Christine L., Teunis, Peter F. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282741/
https://www.ncbi.nlm.nih.gov/pubmed/30053314
http://dx.doi.org/10.1111/risa.13146
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author Wang, Yuke
Moe, Christine L.
Teunis, Peter F. M.
author_facet Wang, Yuke
Moe, Christine L.
Teunis, Peter F. M.
author_sort Wang, Yuke
collection PubMed
description In recent decades, quantitative microbial risk assessment (QMRA) has been widely used to assess exposure to fecal microbes and associated health risks. In this study, a multipathway exposure assessment model was developed to evaluate exposure to fecal microbes for children under 5 in highly contaminated urban environments. Children had contact with various environmental compartments. The contamination levels of these compartments were estimated from fecal indicator counts in the environmental samples. Structured observations of child behavior (including activities, locations, and time) were used to model behavioral sequences as a dynamic network. The exposure model combines behavior sequences with environmental contamination, using additional exposure factors when needed, to estimate the number of fecal microbes transferred from environmental sources to human oral ingestion. As fecal exposure in a highly contaminated urban environment consists of contributions from multiple pathways, it is imperative to study their relative importance. The model helps us better understand the characteristics of the exposure pathways that may be driven by variation in contamination and by variable behavior, like hygiene and high‐risk activities. Importantly, the model also allows prediction of the quantitative effects of an intervention—the expected reduction in exposure due to infrastructural or behavioral changes—by means of scenario studies. Based on experience with this exposure model, we make specific recommendations for additional studies of child behavior and exposure factors in order to fill critical information gaps and improve the model structure and assumptions.
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spelling pubmed-62827412018-12-11 Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment Wang, Yuke Moe, Christine L. Teunis, Peter F. M. Risk Anal Original Research Articles In recent decades, quantitative microbial risk assessment (QMRA) has been widely used to assess exposure to fecal microbes and associated health risks. In this study, a multipathway exposure assessment model was developed to evaluate exposure to fecal microbes for children under 5 in highly contaminated urban environments. Children had contact with various environmental compartments. The contamination levels of these compartments were estimated from fecal indicator counts in the environmental samples. Structured observations of child behavior (including activities, locations, and time) were used to model behavioral sequences as a dynamic network. The exposure model combines behavior sequences with environmental contamination, using additional exposure factors when needed, to estimate the number of fecal microbes transferred from environmental sources to human oral ingestion. As fecal exposure in a highly contaminated urban environment consists of contributions from multiple pathways, it is imperative to study their relative importance. The model helps us better understand the characteristics of the exposure pathways that may be driven by variation in contamination and by variable behavior, like hygiene and high‐risk activities. Importantly, the model also allows prediction of the quantitative effects of an intervention—the expected reduction in exposure due to infrastructural or behavioral changes—by means of scenario studies. Based on experience with this exposure model, we make specific recommendations for additional studies of child behavior and exposure factors in order to fill critical information gaps and improve the model structure and assumptions. John Wiley and Sons Inc. 2018-07-27 2018-11 /pmc/articles/PMC6282741/ /pubmed/30053314 http://dx.doi.org/10.1111/risa.13146 Text en © 2017 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research Articles
Wang, Yuke
Moe, Christine L.
Teunis, Peter F. M.
Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment
title Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment
title_full Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment
title_fullStr Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment
title_full_unstemmed Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment
title_short Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment
title_sort children are exposed to fecal contamination via multiple interconnected pathways: a network model for exposure assessment
topic Original Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282741/
https://www.ncbi.nlm.nih.gov/pubmed/30053314
http://dx.doi.org/10.1111/risa.13146
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