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Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments

As decentralized water reuse continues to gain popularity, risk-based treatment guidance is increasingly sought for the protection of public health. However, effort s to evaluate pathogen risks and log-reduction requirements have been hindered by an incomplete understanding of pathogen occurrence an...

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Autores principales: Jahne, Michael A., Schoen, Mary E., Garland, Jay L., Ashbolt, Nicholas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104838/
https://www.ncbi.nlm.nih.gov/pubmed/30148198
http://dx.doi.org/10.1016/j.mran.2016.11.001
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author Jahne, Michael A.
Schoen, Mary E.
Garland, Jay L.
Ashbolt, Nicholas J.
author_facet Jahne, Michael A.
Schoen, Mary E.
Garland, Jay L.
Ashbolt, Nicholas J.
author_sort Jahne, Michael A.
collection PubMed
description As decentralized water reuse continues to gain popularity, risk-based treatment guidance is increasingly sought for the protection of public health. However, effort s to evaluate pathogen risks and log-reduction requirements have been hindered by an incomplete understanding of pathogen occurrence and densities in locally-collected wastewaters (i.e., from decentralized collection systems). Of particular interest is the potentially high enteric pathogen concentration in small systems with an active infected excreter, but generally lower frequency of pathogen occurrences in smaller systems compared to those with several hundred contributors. Such variability, coupled with low concentrations in many source streams (e.g., sink, shower/bath, and laundry waters), has limited direct measurement of pathogens. This study presents an approach to modeling pathogen concentrations in variously sized greywater and combined wastewater collection systems based on epidemiological pathogen incidence rates, user population size, and fecal loadings to various residential wastewater sources. Pathogen infections were modeled within various population sizes (5-, 100-, and 1,000-person) for seven reference pathogens (viruses: adenoviruses, Norovirus, and Rotavirus; bacteria: Campylobacter and Salmonella spp.; and protozoa: Cryptosporidium and Giardia spp.) on each day of 10,000 possible years, accounting for intermittent infection and overlap of infection periods within the population. Fecal contamination of fresh greywaters from bathroom sinks, showers/baths, and laundry, as well as combined greywater and local combined wastewater (i.e., including toilets), was modeled based on reported fecal indicators in the various sources. Simulated daily infections and models of fecal contamination were coupled with pathogen shedding characteristics to generate distributions of pathogen densities in the various waters. The predicted frequency of pathogen occurrences in local wastewaters was generally low due to low infection incidence within small cohort groups, but increased with collection scale (population size) and infection incidence rate (e.g., Norovirus). When pathogens did occur, a decrease in concentrations from 5- to 100- and from 100- to 1,000-person systems was observed; nonetheless, overall mean concentrations (i.e., including non-occurrences) remained the same due to the increased number of occurrences. This highlights value of the model for characterizing scaling effects over averaging methods, which overestimate the frequency of pathogen occurrence in small systems while underestimating concentration peaks that likely drive risk periods. Results of this work will inform development of risk-based pathogen reduction requirements for decentralized water reuse.
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spelling pubmed-61048382018-08-22 Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments Jahne, Michael A. Schoen, Mary E. Garland, Jay L. Ashbolt, Nicholas J. Microb Risk Anal Article As decentralized water reuse continues to gain popularity, risk-based treatment guidance is increasingly sought for the protection of public health. However, effort s to evaluate pathogen risks and log-reduction requirements have been hindered by an incomplete understanding of pathogen occurrence and densities in locally-collected wastewaters (i.e., from decentralized collection systems). Of particular interest is the potentially high enteric pathogen concentration in small systems with an active infected excreter, but generally lower frequency of pathogen occurrences in smaller systems compared to those with several hundred contributors. Such variability, coupled with low concentrations in many source streams (e.g., sink, shower/bath, and laundry waters), has limited direct measurement of pathogens. This study presents an approach to modeling pathogen concentrations in variously sized greywater and combined wastewater collection systems based on epidemiological pathogen incidence rates, user population size, and fecal loadings to various residential wastewater sources. Pathogen infections were modeled within various population sizes (5-, 100-, and 1,000-person) for seven reference pathogens (viruses: adenoviruses, Norovirus, and Rotavirus; bacteria: Campylobacter and Salmonella spp.; and protozoa: Cryptosporidium and Giardia spp.) on each day of 10,000 possible years, accounting for intermittent infection and overlap of infection periods within the population. Fecal contamination of fresh greywaters from bathroom sinks, showers/baths, and laundry, as well as combined greywater and local combined wastewater (i.e., including toilets), was modeled based on reported fecal indicators in the various sources. Simulated daily infections and models of fecal contamination were coupled with pathogen shedding characteristics to generate distributions of pathogen densities in the various waters. The predicted frequency of pathogen occurrences in local wastewaters was generally low due to low infection incidence within small cohort groups, but increased with collection scale (population size) and infection incidence rate (e.g., Norovirus). When pathogens did occur, a decrease in concentrations from 5- to 100- and from 100- to 1,000-person systems was observed; nonetheless, overall mean concentrations (i.e., including non-occurrences) remained the same due to the increased number of occurrences. This highlights value of the model for characterizing scaling effects over averaging methods, which overestimate the frequency of pathogen occurrence in small systems while underestimating concentration peaks that likely drive risk periods. Results of this work will inform development of risk-based pathogen reduction requirements for decentralized water reuse. 2017-04 /pmc/articles/PMC6104838/ /pubmed/30148198 http://dx.doi.org/10.1016/j.mran.2016.11.001 Text en http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)
spellingShingle Article
Jahne, Michael A.
Schoen, Mary E.
Garland, Jay L.
Ashbolt, Nicholas J.
Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments
title Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments
title_full Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments
title_fullStr Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments
title_full_unstemmed Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments
title_short Simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments
title_sort simulation of enteric pathogen concentrations in locally-collected greywater and wastewater for microbial risk assessments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104838/
https://www.ncbi.nlm.nih.gov/pubmed/30148198
http://dx.doi.org/10.1016/j.mran.2016.11.001
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