1874. Comprehensive, longitudinal wastewater surveillance for SARS-CoV-2 across a university campus, demonstrates low levels of SARS-CoV-2 activity relative to the surrounding community
Authors: Lee Jangwoo , Acosta Nicole , Doorn Jennifer Van , Low Kashtin , Westlund Paul , Chavarriaga Maria Bautista , M. Waddell Barbara Jean , Du Kristine , McCalder Janine , Pradhan Puja , Sedaghat Navid , Papparis Chloe , Chen Jianwei , Xiang Kevin , Chan Leslie , Vivas Laura , Ruecker Norma J , Webster Brendan , Meddings Jon , Achari Gopal , Cathryn Ryan M , Clark Rhonda , Frankowski Kevin , Hubert Casey R J , Parkins Michael 
Published: December 2022

Abstract

Background
Universities are interactive communities where frequent contacts between individuals occur, increasing the risk of outbreaks of COVID-19. We embarked upon a real-time wastewater (WW) monitoring program across the University of Calgary (UofC) campus measuring WW SARS-CoV-2 burden relative to levels of disease in the broader surrounding community. Figure 1
The colour scheme shows 6 sewer sub-catchments at the University of Calgary. Autosamplers were deployed at 4 sampling nodes within sub-catchments CR and YA (both residence halls), and UCE and UCS (catchments that include several campus buildings). Figure 2
Log10-transformed abundance (i.e., copies per mL) of nucleocapsid gene (i.e., N1) for SARS-CoV-2 for each sampling location during October 2021 – April 2022. Locations denoted by the same letters (A, B, or C) show no statistical difference (p &gt; 0.05) according to the Wilcoxon rank-sum test. The WWTP sample corresponds to a catchment area covering most of Calgary including the university campus, for which sampling locations CR, UCE, UCS, and UCW are defined in Fig. 1.

Methods
From October 2021 – April 2022, WW was collected thrice weekly across UofC campus through 4 individual sewer sampling nodes (Fig. 1) using autosamplers (C.E.C. Analytics, CA). Results from these 4 nodes were compared with community monitoring at Calgary’s largest WW treatment plant (WWTP), which received WW from surrounding neighborhoods, and also from UofC. Nucleic acid was extracted from WW for RTqPCR quantification of the N1 nucleocapside gene from SARS-CoV-2 genomic RNA. Qualitative (positive samples defined if cycle threshold &lt; 40) and quantitative statistical analyses were performed using R.

Results
Levels of SARS-CoV-2 in WW were significantly lower at all campus monitoring sites relative to the WWTP (Wilcoxon rank-sum test p &lt; 0.05; Fig. 2). The proportion of WW samples that were positive for SARS-CoV-2 was significantly higher for WWTP than at least two campus locations (p &lt; 0.05 for Crowsnest Hall and UCE - University way and campus drive) according to Fischer’s exact 2-sided test. The proportion of WW samples with positive WW signals were still higher for WWTP than the other two locations, but statistically not significant (p = 0.216). Among campus locations, the buildings in UCE catchment showed much lower N1 signals than other catchments, likely owing to buildings in this catchment primarily being administration and classroom environments, with lower human-to-human contact and less defecation compared to the other 3 catchments, which include residence hall, a dining area, and/or laboratory spaces.

Conclusion
Our results show that SARS-CoV-2 RNA shedding in WW at the UofC is significantly lower than the city-wide signal associated with surrounding neighborhoods. Furthermore, we demonstrate that WW testing at well-defined nodes is a sampling strategy for potentially locating specific places where high transmission of infectious disease occurs.

Disclosures
All Authors: No reported disclosures.