Within- and between-Day Variability of SARS-CoV-2 RNA in Municipal Wastewater during Periods of Varying COVID-19 Prevalence and Positivity

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is being used to monitor Coronavirus Disease 2019 (COVID-19) trends in communities; however, within- and between-day variation of SARS-CoV-2 RNA concentration in primary influent remains largely uncharacterized. In the current study, grab sampling of primary influent was performed every 2 h over two 24-h periods at two wastewater treatment plants (WWTPs) in northern Indiana, USA. The recovery efficiency of endogenous SARS-CoV-2 RNA in wastewater was confirmed to be similar to the recovery efficiency of the process control, bovine respiratory syncytial virus (BRSV). Recovery-corrected SARS-CoV-2 RNA concentrations in primary influent indicate diurnal loading patterns and confirm monitoring dependent on grab samples should target daytime periods with high fecal loading. Importantly, manual compositing performed at the WWTP resulted in concentrations that were consistently lower than grab sample averages indicating potential bias. Uncorrected, recovery-corrected, and pepper mild mottle virus (PMMoV)-normalized SARS-CoV-2 RNA concentrations demonstrated an ordinal agreement with increasing clinical COVID-19 positivity but not COVID-19 cases. In areas where geolocated COVID-19 case data are not available, the COVID-19 positivity rate could provide a useful county-level metric for comparison with wastewater. Nonetheless, large variation both within- and between-days may preclude robust quantitative analyses beyond correlation.

Automated summary

Wastewater surveillance using grab samples every 2 hours over 24-hour periods revealed diurnal loading patterns of SARS-CoV-2 RNA, suggesting monitoring efforts should focus on daytime periods with high fecal loading. Manual compositing may introduce bias, and concentrations in wastewater demonstrated a correlation with clinical COVID-19 positivity rather than case numbers. Large variation within and between days may limit robust quantitative analyses.