Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community

Jangwoo Lee, Nicole Acosta, Barbara J. Waddell, Kristine Du, Kevin Xiang, Jennifer Van Doorn, Kashtin Low, Maria A. Bautista, Janine McCalder, Xiaotian Dai, Xuewen Lu, Thierry Chekouo, Puja Pradhan, Navid Sedaghat, Chloe Papparis, Alexander Buchner Beaudet, Jianwei Chen, Leslie Chan, Laura Vivas, Paul WestlundSrijak Bhatnagar, September Stefani, Gail Visser, Jason Cabaj, Stefania Bertazzon, Shahrzad Sarabi, Gopal Achari, Rhonda G. Clark, Steve E. Hrudey, Bonita E. Lee, Xiaoli Pang, Brendan Webster, William Amin Ghali, Andre Gerald Buret, Tyler Williamson, Danielle A. Southern, Jon Meddings, Kevin Frankowski, Casey R.J. Hubert, Michael D. Parkins

Research output: Contribution to journalJournal Articlepeer-review

2 Citations (Scopus)

Abstract

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites – regardless of several normalization strategies – with certain catchments consistently demonstrating values 1–2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

Original languageEnglish
Article number120469
JournalWater Research
Volume244
DOIs
Publication statusPublished - 1 Oct. 2023

Keywords

  • Dormitories
  • Epidemiology
  • Nodal monitoring
  • Residences
  • Wastewater treatment plant
  • Wastewater-based epidemiology
  • Worksite

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