Predicting COVID-19 cases across a large university campus using complementary built environment and wastewater surveillance approaches

Abstract

BackgroundEnvironmental surveillance of SARS-CoV-2 via wastewater has become an invaluable tool for population-level surveillance. Built environment sampling may provide complementary spatially-refined detection for viral surveillance in congregate settings such as universities.MethodsWe conducted a prospective environmental surveillance study at the University of Ottawa between September 2021 and April 2022. Floor surface samples were collected twice weekly from six university buildings. Samples were analyzed for the presence of SARS-CoV-2 using RT-qPCR. A Poisson regression was used to model the campus-wide COVID-19 cases predicted from the fraction of floor swabs positive for SARS-CoV-2 RNA, building CO2levels, Wi-Fi usage, and SARS-CoV-2 RNA levels in regional wastewater. We used a mixed-effects Poisson regression analysis to model building-level cases using viral copies detected in floor samples as a predictor. A random intercepts logistic regression model tested whether floor samples collected in high-traffic areas were more likely to have SARS-CoV-2 present than low-traffic areas.ResultsOver the 32-week study period, we collected 554 floor swabs at six university buildings. Overall, 13% of swabs were PCR-positive for SARS-CoV-2, with positivity ranging between 4.8% and 32.7% among university buildings. Both floor swab positivity (Spearman r = 0.74, 95% CI: 0.53-0.87) and regional wastewater signal (Spearman r = 0.50, 95% CI: 0.18-0.73) were positively correlated with on-campus COVID-19 cases. In addition, built environment detection was a predictor of cases linked to individual university buildings (IRlog10(copies) + 1= 17, 95% CI: 7-44). There was no significant difference in detection between floors sampled in high-traffic versus low-traffic areas (OR = 1.3, 95% CI: 0.8-2.1).ConclusionsDetection of SARS-CoV-2 RNA on floors and viral RNA levels found in wastewater were strongly associated with the incidence of COVID-19 cases on a university campus. These data suggest a potential role for institutional built environment sampling, used together with wastewater surveillance, for predicting COVID-19 cases at both campus-wide and building level scales.