Estimating virus occurrence using Bayesian modeling in multiple drinking water systems of the United States

• Published in: The Science of the total environment 2018-04, Vol.619-620, p.1330-1339
• Main Authors: Varughese, Eunice A., Brinkman, Nichole E., Anneken, Emily M., Cashdollar, Jennifer L., Fout, G. Shay, Furlong, Edward T., Kolpin, Dana W., Glassmeyer, Susan T., Keely, Scott P.
• Format: Article
• Language: English
• Subjects: Adenovirus; Bayes Theorem; Bayesian statistics; Drinking Water - virology; Drinking water treatment; Enteric viruses; Enterovirus; Environmental Monitoring; Models, Statistical; Norovirus; United States; Water Microbiology; Water Pollution - statistics & numerical data; Water Purification - statistics & numerical data
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2017.10.267

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. [Display omitted] •This study uses a unique approach to study the presence of viruses in source and treated waters from 25 sites across the US•Bayesian analysis was used to estimate virus loads in source and treated waters•PCR count data for each virus, recovery efficiency, and inhibition were parameters integrated into the Bayesian model.•Five virus groups were studied (adenovirus, enterovirus, norovirus GI, norovirus GII, & polyomavirus)•Virus was found in many of the source waters and a few treated waters.•This study allowed for better determination of viral quantities for the purpose of tracking and removal in wa