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Fielding-Miller R, Karthikeyan S, Gaines T, Garfein RS, Salido RA, Cantu VJ, Kohn L, Martin NK, Wynn A, Wijaya C, Flores M, Omaleki V, Majnoonian A, Gonzalez-Zuniga P, Nguyen M, Vo AV, Le T, Duong D, Hassani A, Tweeten S, Jepsen K, Henson B, Hakim A, Birmingham A, De Hoff P, Mark AM, Nasamran CA, Rosenthal SB, Moshiri N, Fisch KM, Humphrey G, Farmer S, Tubb HM, Valles T, Morris J, Kang J, Khaleghi B, Young C, Akel AD, Eilert S, Eno J, Curewitz K, Laurent LC, Rosing T, Knight R. Wastewater and surface monitoring to detect COVID-19 in elementary school settings: The Safer at School Early Alert project. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2021.10.19.21265226. [PMID: 34704096 PMCID: PMC8547528 DOI: 10.1101/2021.10.19.21265226] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
Background Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. Methods The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 - March 2021. Findings In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88% - 98%); 67% were associated with a positive wastewater sample (95% CI: 57% - 77%), and 40% were associated with a positive surface sample (95% CI: 29% - 52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Interpretation Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. Funding County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.
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Affiliation(s)
- Rebecca Fielding-Miller
- University of California San Diego, School of Medicine, Division of Infectious Disease and Global Public Health
| | | | - Tommi Gaines
- University of California San Diego, School of Medicine, Division of Infectious Disease and Global Public Health
| | - Richard S. Garfein
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | | | - Victor J. Cantu
- University of California San Diego, Department of Bioengineering
| | | | - Natasha K Martin
- University of California San Diego, School of Medicine, Division of Infectious Disease and Global Public Health
| | - Adriane Wynn
- University of California San Diego, School of Medicine, Division of Infectious Disease and Global Public Health
| | - Carrissa Wijaya
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | - Marlene Flores
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | - Vinton Omaleki
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | - Araz Majnoonian
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
- University of California San Diego and San Diego State University Joint Doctoral Program in Public Health
| | - Patricia Gonzalez-Zuniga
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | - Megan Nguyen
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
- Johns Hopkins University Bloomberg School of Public Health, International Health Social and Behavioral Interventions
| | - Anh V Vo
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
- Johns Hopkins University Bloomberg School of Public Health, International Health Social and Behavioral Interventions
| | - Tina Le
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | - Dawn Duong
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | - Ashkan Hassani
- University of California San Diego, Herbert Wertheim School of Public Health and Human Longevity Science
| | | | - Kristen Jepsen
- University of California San Diego, Institute for Genomic Medicine
| | - Benjamin Henson
- University of California San Diego, Institute for Genomic Medicine
| | - Abbas Hakim
- University of California San Diego, Department of Obstetrics Gynecology and Reproductive Sciences
| | - Amanda Birmingham
- University of California San Diego, Center for Computational Biology & Bioinformatics
| | - Peter De Hoff
- University of California San Diego, Department of Pediatrics
| | - Adam M. Mark
- University of California San Diego, Center for Computational Biology & Bioinformatics
| | - Chanond A Nasamran
- University of California San Diego, Center for Computational Biology & Bioinformatics
| | - Sara Brin Rosenthal
- University of California San Diego, Center for Computational Biology & Bioinformatics
| | - Niema Moshiri
- University of California San Diego, Department of Computer Science & Engineering
| | - Kathleen M. Fisch
- University of California San Diego, Department of Obstetrics Gynecology and Reproductive Sciences
- University of California San Diego, Center for Computational Biology & Bioinformatics
| | - Greg Humphrey
- University of California San Diego, Department of Pediatrics
| | - Sawyer Farmer
- University of California San Diego, Department of Pediatrics
| | - Helena M. Tubb
- University of California San Diego, Department of Pediatrics
| | - Tommy Valles
- University of California San Diego, Department of Pediatrics
| | - Justin Morris
- University of California San Diego, Department of Computer Science & Engineering
- San Diego State University, Department of Electrical and Computer Engineering
| | - Jaeyoung Kang
- University of California San Diego, Department of Electrical and Computer Engineering
| | - Behnam Khaleghi
- University of California San Diego, Department of Computer Science & Engineering
| | - Colin Young
- University of California San Diego, Department of Computer Science & Engineering
| | | | | | | | | | - Louise C Laurent
- University of California San Diego and San Diego State University Joint Doctoral Program in Public Health
| | - Tajana Rosing
- University of California San Diego, Department of Computer Science & Engineering
| | - Rob Knight
- University of California San Diego, Department of Pediatrics
- University of California San Diego, Department of Bioengineering
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