Wastewater SARS-CoV-2 Concentration and Loading Variability from Grab and 24-Hour Composite Samples

Curtis, K.; Keeling, D.; Yetka, K.; Larson, A.; Gonzalez, R.

The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires a significant, coordinated public health response. Assessing case density and spread of infection is critical and relies largely on clinical testing data. However, clinical testing suffers from known limitations, including test availability and a bias towards enumerating only symptomatic individuals. Wastewater-based epidemiology (WBE) has gained widespread support as a potential complement to clinical testing for assessing COVID-19 infections at the community scale. The efficacy of WBE hinges on the ability to accurately characterize SARS-CoV-2 concentrations in wastewater. To date, a variety of sampling schemes have been used without consensus around the appropriateness of grab or composite sampling. Here we address a key WBE knowledge gap by examining the variability of SARS-CoV-2 concentrations in wastewater grab samples collected every 2 hours for 72 hours compared with corresponding 24-hour flow-weighted composite samples. Results show relatively low variability (mean for all assays = 741 copies 100 mL-1, standard deviation = 508 copies 100 mL-1) for grab sample concentrations, and good agreement between most grab samples and their respective composite (mean deviation from composite = 159 copies 100 mL-1). When SARS-CoV-2 concentrations are used to calculate viral load, the discrepancy between grabs (log10 difference = 12.0) or a grab and its associated composite (log10 difference = 11.8) are amplified. A similar effect is seen when estimating carrier prevalence in a catchment population with median estimates based on grabs ranging 62-1853 carriers. Findings suggest that grab samples may be sufficient to characterize SARS-CoV-2 concentrations, but additional calculations using these data may be sensitive to grab sample variability and warrant the use of flow-weighted composite sampling. These data inform future WBE work by helping determine the most appropriate sampling scheme and facilitate sharing of datasets between studies via consistent methodology.