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

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dc.contributor.authorCohen, Alasdairen
dc.contributor.authorMaile-Moskowitz, Ayellaen
dc.contributor.authorGrubb, Christopheren
dc.contributor.authorGonzalez, Raul A.en
dc.contributor.authorCeci, Alessandroen
dc.contributor.authorDarling, Amandaen
dc.contributor.authorHungerford, Laura L.en
dc.contributor.authorFricker, Ronald D. Jr.en
dc.contributor.authorFinkielstein, Carla V.en
dc.contributor.authorPruden, Amyen
dc.contributor.authorVikesland, Peter J.en
dc.date.accessioned2022-10-03T12:26:04Zen
dc.date.available2022-10-03T12:26:04Zen
dc.date.issued2022-05-01en
dc.date.updated2022-10-02T23:14:51Zen
dc.description.abstractTo evaluate the use of wastewater-based surveillance and epidemiology to monitor and predict SARS-CoV-2 virus trends, over the 2020-2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech's main campus. We used data from external door swipe card readers and student isolation/quarantine status to estimate building-specific occupancy and COVID-19 case counts at a daily resolution. After analyzing 673 wastewater samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), we reanalyzed 329 samples from isolation and nonisolation dormitories and the campus sewage outflow using reverse transcription digital droplet polymerase chain reaction (RT-ddPCR). Population-adjusted viral copy means from isolation dormitory wastewater were 48% and 66% higher than unadjusted viral copy means for N and E genes (1846/100 mL to 2733/100 mL/100 people and 2312/100 mL to 3828/100 mL/100 people, respectively; n = 46). Prespecified analyses with random-effects Poisson regression and dormitory/cluster-robust standard errors showed that the detection of N and E genes were associated with increases of 85% and 99% in the likelihood of COVID-19 cases 8 days later (incident-rate ratio (IRR) = 1.845, p = 0.013 and IRR = 1.994, p = 0.007, respectively; n = 215), and one-log increases in swipe card normalized viral copies (copies/100 mL/100 people) for N and E were associated with increases of 21% and 27% in the likelihood of observing COVID-19 cases 8 days following sample collection (IRR = 1.206, p < 0.001, n = 211 for N; IRR = 1.265, p < 0.001, n = 211 for E). One-log increases in swipe normalized copies were also associated with 40% and 43% increases in the likelihood of observing COVID-19 cases 5 days after sample collection (IRR = 1.403, p = 0.002, n = 212 for N; IRR = 1.426, p < 0.001, n = 212 for E). Our findings highlight the use of building-specific occupancy data and add to the evidence for the potential of wastewater-based epidemiology to predict COVID-19 trends at subsewershed scales.en
dc.description.versionAccepted versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1021/acsestwater.2c00059en
dc.identifier.eissn2690-0637en
dc.identifier.issn2690-0637en
dc.identifier.orcidPruden-Bagchi, Amy [0000-0002-3191-6244]en
dc.identifier.orcidVikesland, Peter [0000-0003-2654-5132]en
dc.identifier.orcidCohen, Alasdair [0000-0002-9917-8647]en
dc.identifier.orcidFinkielstein, Carla [0000-0002-8417-4643]en
dc.identifier.otherPMC9128018en
dc.identifier.urihttp://hdl.handle.net/10919/112041en
dc.language.isoenen
dc.publisherAmerican Chemical Societyen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleSubsewershed SARS-CoV-2 Wastewater Surveillance and COVID-19 Epidemiology Using Building-Specific Occupancy and Case Dataen
dc.title.serialACS Environmental Science and Technology Wateren
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherJournal Articleen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/Biological Sciencesen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Civil & Environmental Engineeringen
pubs.organisational-group/Virginia Tech/Veterinary Medicineen
pubs.organisational-group/Virginia Tech/Veterinary Medicine/Population Health Sciencesen
pubs.organisational-group/Virginia Tech/University Research Institutesen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciencesen
pubs.organisational-group/Virginia Tech/Faculty of Health Sciencesen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen
pubs.organisational-group/Virginia Tech/Veterinary Medicine/CVM T&R Facultyen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciences/Durelle Scotten
pubs.organisational-group/Virginia Tech/VT Carilion School of Medicineen
pubs.organisational-group/Virginia Tech/VT Carilion School of Medicine/Psychiatry and Behavioral Medicineen
pubs.organisational-group/Virginia Tech/VT Carilion School of Medicine/Psychiatry and Behavioral Medicine/Secondary Appointment-Psychiatry and Behavioral Medicineen

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