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Modeling Biphasic Environmental Decay of Pathogens and Implications for Risk Analysis
[Image: see text] As the appreciation for the importance of the environment in infectious disease transmission has grown, so too has interest in pathogen fate and transport. Fate has been traditionally described by simple exponential decay, but there is increasing recognition that some pathogens dem...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical Society
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789392/ https://www.ncbi.nlm.nih.gov/pubmed/28112914 http://dx.doi.org/10.1021/acs.est.6b04030 |
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author | Brouwer, Andrew F. Eisenberg, Marisa C. Remais, Justin V. Collender, Philip A. Meza, Rafael Eisenberg, Joseph N. S. |
author_facet | Brouwer, Andrew F. Eisenberg, Marisa C. Remais, Justin V. Collender, Philip A. Meza, Rafael Eisenberg, Joseph N. S. |
author_sort | Brouwer, Andrew F. |
collection | PubMed |
description | [Image: see text] As the appreciation for the importance of the environment in infectious disease transmission has grown, so too has interest in pathogen fate and transport. Fate has been traditionally described by simple exponential decay, but there is increasing recognition that some pathogens demonstrate a biphasic pattern of decay—fast followed by slow. While many have attributed this behavior to population heterogeneity, we demonstrate that biphasic dynamics can arise through a number of plausible mechanisms. We examine the identifiability of a general model encompassing three such mechanisms: population heterogeneity, hardening off, and the existence of viable-but-not-culturable states. Although the models are not fully identifiable from longitudinal sampling studies of pathogen concentrations, we use a differential algebra approach to determine identifiable parameter combinations. Through case studies using Cryptosporidium and Escherichia coli, we show that failure to consider biphasic pathogen dynamics can lead to substantial under- or overestimation of disease risks and pathogen concentrations, depending on the context. More reliable models for environmental hazards and human health risks are possible with an improved understanding of the conditions in which biphasic die-off is expected. Understanding the mechanisms of pathogen decay will ultimately enhance our control efforts to mitigate exposure to environmental contamination. |
format | Online Article Text |
id | pubmed-5789392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | American
Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-57893922018-01-31 Modeling Biphasic Environmental Decay of Pathogens and Implications for Risk Analysis Brouwer, Andrew F. Eisenberg, Marisa C. Remais, Justin V. Collender, Philip A. Meza, Rafael Eisenberg, Joseph N. S. Environ Sci Technol [Image: see text] As the appreciation for the importance of the environment in infectious disease transmission has grown, so too has interest in pathogen fate and transport. Fate has been traditionally described by simple exponential decay, but there is increasing recognition that some pathogens demonstrate a biphasic pattern of decay—fast followed by slow. While many have attributed this behavior to population heterogeneity, we demonstrate that biphasic dynamics can arise through a number of plausible mechanisms. We examine the identifiability of a general model encompassing three such mechanisms: population heterogeneity, hardening off, and the existence of viable-but-not-culturable states. Although the models are not fully identifiable from longitudinal sampling studies of pathogen concentrations, we use a differential algebra approach to determine identifiable parameter combinations. Through case studies using Cryptosporidium and Escherichia coli, we show that failure to consider biphasic pathogen dynamics can lead to substantial under- or overestimation of disease risks and pathogen concentrations, depending on the context. More reliable models for environmental hazards and human health risks are possible with an improved understanding of the conditions in which biphasic die-off is expected. Understanding the mechanisms of pathogen decay will ultimately enhance our control efforts to mitigate exposure to environmental contamination. American Chemical Society 2017-01-23 2017-02-21 /pmc/articles/PMC5789392/ /pubmed/28112914 http://dx.doi.org/10.1021/acs.est.6b04030 Text en Copyright © 2017 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Brouwer, Andrew F. Eisenberg, Marisa C. Remais, Justin V. Collender, Philip A. Meza, Rafael Eisenberg, Joseph N. S. Modeling Biphasic Environmental Decay of Pathogens and Implications for Risk Analysis |
title | Modeling
Biphasic Environmental Decay of Pathogens
and Implications for Risk Analysis |
title_full | Modeling
Biphasic Environmental Decay of Pathogens
and Implications for Risk Analysis |
title_fullStr | Modeling
Biphasic Environmental Decay of Pathogens
and Implications for Risk Analysis |
title_full_unstemmed | Modeling
Biphasic Environmental Decay of Pathogens
and Implications for Risk Analysis |
title_short | Modeling
Biphasic Environmental Decay of Pathogens
and Implications for Risk Analysis |
title_sort | modeling
biphasic environmental decay of pathogens
and implications for risk analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789392/ https://www.ncbi.nlm.nih.gov/pubmed/28112914 http://dx.doi.org/10.1021/acs.est.6b04030 |
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