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High Sensitivity and Specificity of Dormitory-Level Wastewater Surveillance for COVID-19 during Fall Semester 2020 at Syracuse University, New York

Author

Listed:
  • Alex Godinez

    (David B. Falk College of Sports and Human Dynamics, Syracuse University, Syracuse, NY 13244, USA)

  • Dustin Hill

    (David B. Falk College of Sports and Human Dynamics, Syracuse University, Syracuse, NY 13244, USA)

  • Bryan Dandaraw

    (Department of Environmental Sciences, College of Environmental Sciences and Forestry, State University of New York, Syracuse, NY 13210, USA)

  • Hyatt Green

    (Department of Environmental Biology, College of Environmental Sciences and Forestry, State University of New York, Syracuse, NY 13210, USA)

  • Pruthvi Kilaru

    (David B. Falk College of Sports and Human Dynamics, Syracuse University, Syracuse, NY 13244, USA
    College of Osteopathic Medicine, Des Moines University, Des Moines, IA 50312, USA)

  • Frank Middleton

    (Department of Biochemistry and Molecular Biology, SUNY Upstate Medical University, Syracuse, NY 13210, USA)

  • Sythong Run

    (David B. Falk College of Sports and Human Dynamics, Syracuse University, Syracuse, NY 13244, USA)

  • Brittany L. Kmush

    (David B. Falk College of Sports and Human Dynamics, Syracuse University, Syracuse, NY 13244, USA)

  • David A. Larsen

    (David B. Falk College of Sports and Human Dynamics, Syracuse University, Syracuse, NY 13244, USA)

Abstract

A residential building’s wastewater presents a potential non-invasive method of surveilling numerous infectious diseases, including SARS-CoV-2. We analyzed wastewater from 16 different residential locations at Syracuse University (Syracuse, NY, USA) during fall semester 2020, testing for SARS-CoV-2 RNA twice weekly and compared the presence of clinical COVID-19 cases to detection of the viral RNA in wastewater. The sensitivity of wastewater surveillance to correctly identify dormitories with a case of COVID-19 ranged from 95% (95% confidence interval [CI] = 76–100%) on the same day as the case was diagnosed to 73% (95% CI = 53–92%), with 7 days lead time of wastewater. The positive predictive value ranged from 20% (95% CI = 13–30%) on the same day as the case was diagnosed to 50% (95% CI = 40–60%) with 7 days lead time. The specificity of wastewater surveillance to correctly identify dormitories without a case of COVID-19 ranged from 60% (95% CI = 52–67%) on the day of the wastewater sample to 67% (95% CI = 58–74%) with 7 days lead time. The negative predictive value ranged from 99% (95% CI = 95–100%) on the day of the wastewater sample to 84% (95% CI = 77–91%) with 7 days lead time. Wastewater surveillance for SARS-CoV-2 at the building level is highly accurate in determining if residents have a COVID-19 infection. Particular benefit is derived from negative wastewater results that can confirm a building is COVID-19 free.

Suggested Citation

  • Alex Godinez & Dustin Hill & Bryan Dandaraw & Hyatt Green & Pruthvi Kilaru & Frank Middleton & Sythong Run & Brittany L. Kmush & David A. Larsen, 2022. "High Sensitivity and Specificity of Dormitory-Level Wastewater Surveillance for COVID-19 during Fall Semester 2020 at Syracuse University, New York," IJERPH, MDPI, vol. 19(8), pages 1-13, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4851-:d:795430
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    References listed on IDEAS

    as
    1. Sasha Harris-Lovett & Kara L. Nelson & Paloma Beamer & Heather N. Bischel & Aaron Bivins & Andrea Bruder & Caitlyn Butler & Todd D. Camenisch & Susan K. De Long & Smruthi Karthikeyan & David A. Larsen, 2021. "Wastewater Surveillance for SARS-CoV-2 on College Campuses: Initial Efforts, Lessons Learned, and Research Needs," IJERPH, MDPI, vol. 18(9), pages 1-20, April.
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