Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) levels in the communities since the coronavirus disease 2019 (COVID-19) outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater is critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (PMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated and validated for their utility in normalizing the SARS-CoV-2 loads through two normalizing approaches using the data from 64 wastewater treatment plants (WWTPs) in Missouri. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performing candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuating population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population of the given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p < 0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker complements the current normalization scheme recommended by CDC and helps us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

Sequencing Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) from wastewater has become a useful tool in monitoring the spread of viral variants. Approaches to this task have been varied, relying on differing sequencing methods and computational analyses. We used a novel computation workflow based on amplicon sequencing of SARS-CoV-2 spike domains in order to track viral populations in wastewater. As part of this workflow, we developed a program, SAM Refiner, that has a variety of outputs, including novel variant reporting as well as functions designed to remove polymerase chain reaction (PCR) generated chimeric sequences. With these methods, we were able to track viral population dynamics over time. We report here on the emergence of two variants of concern, B.1.1.7 (Alpha) and P.1 (Gamma), and their displacement of the D614G B.1 variant in a Missouri sewershed.