Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology

Authors: HSU, SHU-YU - University Of Missouri; BAYATI, MOHAMED - University Of Missouri; LI, CHENHUI - University Of Missouri; HSIEH, HSIN-YEH - University Of Missouri; BELENCHIA, ANTHONY - Bureau Of Environmental Epidemiology; KLUTTS, JESSICA - Missouri Department Of Natural Resources; ZEMMER, SALLY - Missouri Department Of Natural Resources; REYNOLDS, MELISSA - Bureau Of Environmental Epidemiology; SEMKIW, ELIZABETH - Bureau Of Environmental Epidemiology; JOHNSON, HWEI-YIING - Bureau Of Environmental Epidemiology; FOLEY, TREVOR - Missouri Department Of Corrections; WIEBERG, CHRIS - Missouri Department Of Natural Resources; WENZEL, JEFF - Bureau Of Environmental Epidemiology; JOHNSON, MARC - University Of Missouri; LIN, CHUNG-HO - University Of Missouri

Submitted to: Water Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/13/2022
Publication Date: 8/15/2022
Citation: Hsu, S., Bayati, M., Li, C., Hsieh, H., Belenchia, A., Klutts, J., Zemmer, S.A., Reynolds, M., Semkiw, E., Johnson, H., Foley, T., Wieberg, C.G., Wenzel, J., Johnson, M.C., Lin, C. 2022. Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology. Water Research. 223. Article 118985. https://doi.org/10.1016/j.watres.2022.118985.
DOI: https://doi.org/10.1016/j.watres.2022.118985

Interpretive Summary: Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the 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. The reliable population chemical biomarkers, paraxanthine (metabolite of the caffeine), identified in this study offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

Technical Abstract: 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 SARSCoV- 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.