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DOI10.1016/j.scitotenv.2017.10.267
Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States
Varughese, Eunice A.1; Brinkman, Nichole E.1; Anneken, Emily M.1; Cashdollar, Jennifer L.1; Fout, G. Shay1; Furlong, Edward T.2; Kolpin, Dana W.3; Glassmeyer, Susan T.1; Keely, Scott P.1
发表日期2018-04-01
ISSN0048-9697
卷号619页码:1330-1339
英文摘要

Drinking water treatment plants rely on purification of contaminated source waters to provide communities with potable water. One group of possible contaminants are enteric viruses. Measurement of viral quantities in environmental water systems are often performed using polymerase chain reaction (PCR) or quantitative PCR (qPCR). However, true values may be underestimated due to challenges involved in a multi-step viral concentration process and due to PCR inhibition. In this study, water samples were concentrated from 25 drinking water treatment plants (DWTPs) across the US to study the occurrence of enteric viruses in source water and removal after treatment. The five different types of viruses studied were adenovirus, norovirus GI, norovirus GII, enterovirus, and polyomavirus. Quantitative PCR was performed on all samples to determine presence or absence of these viruses in each sample. Ten DWTPs showed presence of one or more viruses in source water, with four DWTPs having treated drinking water testing positive. Furthermore, PCR inhibition was assessed for each sample using an exogenous amplification control, which indicated that all of the DWTP samples, including source and treated water samples, had some level of inhibition, confirming that inhibition plays an important role in PCR-based assessments of environmental samples. PCR inhibition measurements, viral recovery, and other assessments were incorporated into a Bayesian model to more accurately determine viral load in both source and treated water. Results of the Bayesian model indicated that viruses are present in source water and treated water. By using a Bayesian framework that incorporates inhibition, as well as many other parameters that affect viral detection, this study offers an approach for more accurately estimating the occurrence of viral pathogens in environmental waters. Published by Elsevier B.V.


英文关键词Bayesian statistics;Enteric viruses;Drinking water treatment;Norovirus;Enterovirus;Adenovirus
语种英语
WOS记录号WOS:000424144200133
来源期刊SCIENCE OF THE TOTAL ENVIRONMENT
来源机构美国环保署
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/58370
作者单位1.US EPA, Off Res & Dev, Natl Exposure Res Lab, 26 W Martin Luther King Dr, Cincinnati, OH 45268 USA;
2.USGS, Natl Water Qual Lab, Denver Fed Ctr, Bldg 95, Denver, CO 80225 USA;
3.USGS, 400 S Clinton St,Rm 269,Fed Bldg, Iowa City, IA 52240 USA
推荐引用方式
GB/T 7714
Varughese, Eunice A.,Brinkman, Nichole E.,Anneken, Emily M.,et al. Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States[J]. 美国环保署,2018,619:1330-1339.
APA Varughese, Eunice A..,Brinkman, Nichole E..,Anneken, Emily M..,Cashdollar, Jennifer L..,Fout, G. Shay.,...&Keely, Scott P..(2018).Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States.SCIENCE OF THE TOTAL ENVIRONMENT,619,1330-1339.
MLA Varughese, Eunice A.,et al."Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States".SCIENCE OF THE TOTAL ENVIRONMENT 619(2018):1330-1339.
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