Predicting COVID-19 Cases Across a Large University Campus Using Built Environment Surveillance

Area of Science:

• Environmental science
• Epidemiology
• Public Health

Background:

• Wastewater surveillance is key for population-level SARS-CoV-2 monitoring.
• Built environment sampling offers spatially refined viral detection in congregate settings like universities.

Purpose of the Study:

• To assess the utility of environmental surveillance of SARS-CoV-2 on university building floors.
• To determine if built environment sampling can predict COVID-19 cases on campus and at the building level.

Main Methods:

• Prospective study at the University of Ottawa (Sept 2021-Apr 2022).
• Collected 554 floor surface swabs from six buildings twice weekly.
• Analyzed swabs for SARS-CoV-2 RNA using quantitative PCR.
• Used Poisson regression to model campus-wide and building-level COVID-19 cases based on floor swab positivity, CO2 levels, Wi-Fi usage, and city wastewater data.

Main Results:

• 13% of floor swabs tested positive for SARS-CoV-2 RNA.
• Floor swab positivity correlated strongly with on-campus COVID-19 cases (Spearman r = 0.74).
• City wastewater SARS-CoV-2 signal also correlated with on-campus cases (Spearman r = 0.50).
• Built environment detection predicted individual building-level COVID-19 cases.

Conclusions:

• SARS-CoV-2 RNA detection on floors is strongly associated with COVID-19 incidence on a university campus.
• Institutional built environment sampling, combined with wastewater surveillance, can predict COVID-19 cases at campus-wide and building-level scales.