Subsewershed SARS-CoV-2 Wastewater Surveillance and COVID-19 Epidemiology Using Building-Specific Occupancy and Case Data

To evaluate the use of wastewater-based surveillance and epidemiology to monitor predict SARS-CoV-2 virus trends, over 2020–2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech’s main campus. We used data external door swipe card readers student isolation/quarantine status estimate building-specific occupancy COVID-19 case counts at a daily resolution. After analyzing 673 using reverse transcription quantitative polymerase chain reaction (RT-qPCR), reanalyzed 329 isolation nonisolation dormitories campus sewage outflow digital droplet (RT-ddPCR). Population-adjusted viral copy means dormitory were 48% 66% higher than unadjusted for N E genes (1846/100 mL 2733/100 mL/100 people 2312/100 3828/100 people, respectively; n = 46). Prespecified analyses with random-effects Poisson regression dormitory/cluster-robust standard errors showed that detection associated increases 85% 99% in likelihood cases 8 days later (incident–rate ratio (IRR) 1.845, p 0.013 IRR 1.994, 0.007, 215), one-log normalized copies (copies/100 people) 21% 27% observing following sample collection (IRR 1.206, < 0.001, 211 N; 1.265, E). One-log also 40% 43% 5 after 1.403, 0.002, 212 1.426, Our findings highlight add evidence potential trends subsewershed scales.