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Method Optimization and Investigation of SARS-CoV-2 Monitoring in Wastewater using Viral Genetic Markers and Environmental Factors
AuthorMazurowski, Lauren Alicia
Civil and Environmental Engineering
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The pandemic caused by coronavirus disease 2019 (COVID-19) has led researchers from interdisciplinary fields to utilize wastewater-based epidemiology (WBE) as a complementary testing resource in understanding SARS-CoV-2 infection prevalence among communities and large populations groups. This study aimed to use WBE to successfully monitor three water reclamation facilities (WRFs) in Washoe County for SARS-CoV-2 genetic markers, provide greater knowledge on the concentration of the SARS-CoV-2 virus in wastewater, evaluate the influence of environmental factors on SARS-CoV-2 RNA fragments in wastewater, and provide a predictive model that estimates daily case numbers based on viral concentration data and environmental factors. In this study, the optimized method utilized a grab sampling protocol, followed by a modified centrifugal ultrafiltration method for virus concentration, and a reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) method for virus quantification of the N1 and N2 viral RNA gene markers. Originally, a polyethylene glycol precipitation method was used for virus concentration, but was later changed to a modified centrifugal ultrafiltration method to improve laboratory processing times. A virus recovery study utilizing the centrifugal ultrafiltration method revealed SARS-CoV-2 recovery values from wastewater during this study. A principal component analysis (PCA) was conducted to reveal relationships between environmental factors monitored during the study period and daily new cases reported by health authorities. Lastly, a multiple linear regressions model created using the least squares method estimated the amount of predicted daily new cases. Similar overall trends between COVID-19 incidence data from clinical testing and SARS-CoV-2 viral loading rates in wastewater were observed. In PCA, service population, flowrate, daily new cases (with a seven-day lag time), pH, and ammonia were strongly clustered together. Viral loading rate also clustered with temperature, total dissolved solids (TDS), and dissolved organic carbon (DOC), indicating that dissolved constituents and temperature of wastewater were correlated to the presence of SARS-CoV-2 levels in the liquid phase of wastewater. The optimal model (R2 = 0.89), which includes viral loading rate, service population, temperature, and DOC as predictor variables, reflected a seven-day advance prediction of likely cases, which provided more robust results than any other lag period, when lag period values ranged from 0-14 days. As the first study to monitor untreated wastewater of the Reno-Sparks metropolitan area, Nevada, USA, for SARS-CoV-2 viral RNA, environmental surveillance has shown to aid local decision makers in developing strategies to manage COVID-19 in the region.