A novel passive sampling approach for SARS-CoV-2 in wastewater in a Canadian province with low prevalence of COVID-19

The overall objective of this work was to develop a simple and effective passive sampling protocol for the detection of SARS-CoV-2 in sewer catchments at targeted institutional-level sampling sites in a region of low COVID-19 prevalence. We developed a new 3D-printed sampling cage and assessed four commercially-available materials (cotton gauze, cotton cheesecloth, cellulose sponges, and electronegative filters) for RNA adsorption in the cage. We determined that cheesecloth and electronegative filters provided an effective approach for collecting and measuring SARS-CoV-2 in wastewater. We also compared the performance of three elution mixtures (a commercially-available lysis buffer, a Tween®20-based buffer, and a 1:1 acetonitrile:water mixture) for detection of heat-inactivated SARS-CoV-2 reference material (HI-SCV-2) spiked into municipal wastewater at 1.0 × 103 genomic units per millilitre (GU mL−1). The highest mean RNA concentrations were achieved using the cheesecloth (7.0 × 104 ± 3.7 × 104 GU per eluate) and electronegative filters (2.3 × 104 ± 2.5 × 104 GU per eluate) in combination with the Tween®20-based buffer with positive detections in all three biological replicates for both material types. We deployed passive samplers at two sewer catchments (locations A and B) to compare the performance of each passive sampler material type in the field. Over 15 sampling events at each site, we demonstrated that both cheesecloth (location A) and electronegative filters (location B) coupled with a Tween®20-based elution technique could be utilized for the reliable detection of SARS-CoV-2. These results have demonstrated a quick and effective passive sampling approach for SARS-CoV-2 detection in targeted locations in wastewater collection systems, which may have long-term applicability as global vaccination programs evolve.