Informing water distribution line rehabilitation through quantitative microbial risk assessment.

Bayesian statistics Distribution system Drinking water quality Quantitative microbial risk assessment Waterborne pathogens

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
15 Oct 2020
Historique:
received: 27 04 2020
revised: 01 06 2020
accepted: 04 06 2020
pubmed: 8 8 2020
medline: 25 8 2020
entrez: 8 8 2020
Statut: ppublish

Résumé

Poor urban water quality has been linked to diminished source water quality, poorly functioning water treatment systems and infiltration into distribution lines after treatment resulting in microbiological contamination. With limited funding to rehabilitate distribution lines, developing nations need tools to identify the areas of greatest concern to human health so as to target cost effective remediation approaches. Herein, a case study of Hyderabad, Pakistan was used to demonstrate the efficacy of combining quantitative microbial risk assessment (QMRA) for multiple pathogens with spatial distribution system modeling to identify areas for pipe rehabilitation. Abundance of Escherichia coli, Enterococcus (enterococci), Salmonella spp., Shigella spp., Giardia intestinalis, Vibrio cholera, norovirus GI and adenovirus 40/41, were determined in 85 locations including the source water, treatment plant effluent and the city distribution lines. Bayesian statistics and Monte Carlo simulations were used in the QMRA to account for left-censored microbial abundance distributions. Bacterial and viral abundances in the distribution system samples decreased as follows: 9400 ± 19,800 norovirus gene copies/100 mL (average ± standard deviation, 100% of samples positive); 340 ± 2200 enterococci CFU/100 mL (94%), 71 ± 97 Shigella sp. CFU/100 mL (97%), 60 ± 360 E. coli CFU/100 mL (89%), 35 ± 79 adenovirus gene copies/100 mL (100%), and 21 ± 46 Salmonella sp. CFU/100 mL (76%). The QMRA revealed unacceptable probabilities of illness (>1 in 10,000 illness level) from the four exposure routes considered (drinking water, or only showering, tooth brushing, and rinsing vegetables consumed raw). Disease severity indices based on the QMRA combined with mapping the distribution system revealed areas for targeted rehabilitation. The combined intensive sampling, risk assessment and mapping can be used in low- and middle-income countries to target distribution system rehabilitation efforts and improve health outcomes.

Identifiants

pubmed: 32758946
pii: S0048-9697(20)33541-5
doi: 10.1016/j.scitotenv.2020.140021
pii:
doi:

Substances chimiques

Water 059QF0KO0R

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

140021

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Rubayat Jamal (R)

Civil and Environmental Engineering, University of Utah, 110 Central Campus Drive Suite 2000, Salt Lake City, UT 84112, USA.

Shaista Mubarak (S)

US Pakistan Center for Advanced Studies in Water, Mehran University of Engineering and Technology, Jamshoro, 76062, Sindh, Pakistan.

Sierra Q Sahulka (SQ)

Civil and Environmental Engineering, University of Utah, 110 Central Campus Drive Suite 2000, Salt Lake City, UT 84112, USA.

Junaid A Kori (JA)

US Pakistan Center for Advanced Studies in Water, Mehran University of Engineering and Technology, Jamshoro, 76062, Sindh, Pakistan.

Ayesha Tajammul (A)

US Pakistan Center for Advanced Studies in Water, Mehran University of Engineering and Technology, Jamshoro, 76062, Sindh, Pakistan.

Jamil Ahmed (J)

US Pakistan Center for Advanced Studies in Water, Mehran University of Engineering and Technology, Jamshoro, 76062, Sindh, Pakistan.

Rasool B Mahar (RB)

US Pakistan Center for Advanced Studies in Water, Mehran University of Engineering and Technology, Jamshoro, 76062, Sindh, Pakistan.

McKinley Snyder Olsen (MS)

Geosyntec Consultants, Inc., 1111 Broadway, Oakland, CA 94607, USA.

Ramesh Goel (R)

Civil and Environmental Engineering, University of Utah, 110 Central Campus Drive Suite 2000, Salt Lake City, UT 84112, USA.

Jennifer Weidhaas (J)

Civil and Environmental Engineering, University of Utah, 110 Central Campus Drive Suite 2000, Salt Lake City, UT 84112, USA. Electronic address: jennifer.weidhaas@utah.edu.

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Classifications MeSH