Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Targeting a free viral fraction enhances the early alert potential of wastewater surveillance for Sars-CoV-2

A methods comparison spanning the transition between delta and omicron variants in a large urban center

Bibliographic Data

ID22070523
AuthorsLiang Zhao (0000-0002-7679-5087, Michigan State University), Qiudi Geng (0000-0003-0150-4975, University of Windsor), Ryland Corchis-Scott (0000-0003-2525-1730, University of Windsor), Robert Michael McKay, R Michael L McKay (0000-0003-2723-5371, Bowling Green State University), John Norton (0000-0003-2606-6967, Great Lakes Water Authority), Irene Xagoraraki (0000-0002-8173-430X, Michigan State University, corresponding author)
Year2023
Volume11
Pages1140441-1140441
Publication date2023-07-20
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1140441
PMID37546328
OpenAlexW4385067379
LanguageEN
Citations received1
References cited86

Introduction: Wastewater surveillance has proven to be a valuable approach to monitoring the spread of SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19). Recognizing the benefits of wastewater surveillance as a tool to support public health in tracking SARS-CoV-2 and other respiratory pathogens, numerous wastewater virus sampling and concentration methods have been tested for appropriate applications as well as their significance for actionability by public health practices. Methods: Here, we present a 34-week long wastewater surveillance study that covers nearly 4 million residents of the Detroit (MI, United States) metropolitan area. Three primary concentration methods were compared with respect to recovery of SARS-CoV-2 from wastewater: Virus Adsorption-Elution (VIRADEL), polyethylene glycol precipitation (PEG), and polysulfone (PES) filtration. Wastewater viral concentrations were normalized using various parameters (flow rate, population, total suspended solids) to account for variations in flow. Three analytical approaches were implemented to compare wastewater viral concentrations across the three primary concentration methods to COVID-19 clinical data for both normalized and non-normalized data: Pearson and Spearman correlations, Dynamic Time Warping (DTW), and Time Lagged Cross Correlation (TLCC) and peak synchrony. Results: It was found that VIRADEL, which captures free and suspended virus from supernatant wastewater, was a leading indicator of COVID-19 cases within the region, whereas PEG and PES filtration, which target particle-associated virus, each lagged behind the early alert potential of VIRADEL. PEG and PES methods may potentially capture previously shed and accumulated SARS-CoV-2 resuspended from sediments in the interceptors. Discussion: These results indicate that the VIRADEL method can be used to enhance the early-warning potential of wastewater surveillance applications although drawbacks include the need to process large volumes of wastewater to concentrate sufficiently free and suspended virus for detection. While lagging the VIRADEL method for early-alert potential, both PEG and PES filtration can be used for routine COVID-19 wastewater monitoring since they allow a large number of samples to be processed concurrently while being more cost-effective and with rapid turn-around yielding results same day as collection

Environmental health · Population · Sewage treatment · Wastewater · COVID-19 epidemiological studies · Environmental Science · Fecal contamination and water quality · Medicine · SARS-CoV-2 detection and testing · Environmental Engineering

  • Community case study

    Open Access•Irene Xagoraraki, Liang Zhao et al.•Frontiers in Public Health•2025

  • Stability of Sars-CoV-2 in different environmental conditions

    Open Access•Alex W H Chin, Julie T S Chu et al.•The Lancet Microbe•2020

  • Temporal dynamics in viral shedding and transmissibility of Covid-19

    Open Access•Xi He, Eric Hy Lau et al.•Nature Medicine•2020

Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae