Evaluation of intra- and inter-lab variability in quantifying SARS-CoV-2 in a state-wide wastewater monitoring network. Issue 4 (6th March 2023)

• Record Type: Journal Article
• Authors: Davis, Angela; Keely, Scott P.; Brinkman, Nichole E.; Bohrer, Zuzana; Ai, Yuehan; Mou, Xiaozhen; Chattopadhyay, Saurabh; Hershey, Olivia; Senko, John; Hull, Natalie; Lytmer, Eva; Quintero, Anda; Lee, Jiyoung
• Is Part Of: Environmental science. Volume 9:Issue 4(2023)
• Page Start: 1053
• Page End: 1068
• Publication Date: 2023-03-06
• Subjects: Water-supply -- Periodicals; Water security -- Periodicals; Water resources development -- Periodicals; Water chemistry -- Periodicals; 553.705
• DOI: 10.1039/d2ew00737a
• Languages: English
• ISSNs: 2053-1400

Abstract

Abstract : Wastewater-based SARS-CoV-2 monitoring is an effective tool for rapid management of the pandemic. Evaluating methodologies during the height of this crisis strengthens the field to ensure reproducibility across states, nations, and the globe. Abstract : In December 2019, SARS-CoV-2, the virus that causes coronavirus disease 2019, was first reported and subsequently triggered a global pandemic. Wastewater monitoring, a strategy for quantifying viral gene concentrations from wastewater influents within a community, has served as an early warning and management tool for the spread of SARS-CoV-2 in a community. Ohio built a collaborative statewide wastewater monitoring network that is supported by eight labs (university, government, and commercial laboratories) with unique sample processing workflows. Consequently, we sought to characterize the variability in wastewater monitoring results for network labs. Across seven trials between October 2020 and November 2021, eight participating labs successfully quantified two SARS-CoV-2 RNA targets and human fecal indicator virus targets in wastewater sample aliquots with reproducible results, although recovery efficiencies of spiked surrogates ranged from 3 to 75%. When SARS-CoV-2 gene fragment concentrations were adjusted for recovery efficiency and flow, the proportion of variance between laboratories was minimized, serving as the best model to account for between-lab variance. Another adjustment factor (alone and in different combinations with the above factors) considered to account for sample and measurement variability includes fecal marker normalization. Genetic quantification variability can be attributed to many factors, including the methods, individual samples, and water quality parameters. In addition, statistically significant correlations were observed between SARS-CoV-2 RNA and COVID-19 case numbers, supporting the notion that wastewater surveillance continues to serve as an effective monitoring tool. This study serves as a real-time example of multi-laboratory collaboration for public health preparedness for infectious diseases.