Predictive values of time-dense SARS-CoV-2 wastewater analysis in university campus buildings.


Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
20 Aug 2022
Historique:
received: 06 02 2022
revised: 15 04 2022
accepted: 16 04 2022
pubmed: 27 4 2022
medline: 9 6 2022
entrez: 26 4 2022
Statut: ppublish

Résumé

Wastewater-based SARS-CoV-2 surveillance on college campuses has the ability to detect individual clinical COVID-19 cases at the building-level. High concordance of wastewater results and clinical cases has been observed when calculated over a time window of four days or longer and in settings with high incidence of infection. At Duke University, twice a week clinical surveillance of all resident undergraduates was carried out in the spring 2021 semester. We conducted simultaneous wastewater surveillance with daily frequency on selected residence halls to assess wastewater as an early warning tool during times of low transmission with the hope of scaling down clinical test frequency. We evaluated the temporal relationship of the two time-dense data sets, wastewater and clinical, and sought a strategy to achieve the highest wastewater predictive values using the shortest time window to enable timely intervention. There were 11 days with clinical cases in the residence halls (80-120 occupants) under wastewater surveillance with 5 instances of a single clinical case and 3 instances of two clinical cases which also corresponded to a positive wastewater SARS-CoV-2 signal. While the majority (71%) of our wastewater samples were negative for SARS-CoV-2, 29% resulted in at least one positive PCR signal, some of which did not correlate with an identified clinical case. Using a criteria of two consecutive days of positive wastewater signals, we obtained a positive predictive value (PPV) of 75% and a negative predictive value of 87% using a short 2 day time window for agreement. A conventional concordance over a much longer 4 day time window resulted in PPV of only 60%. Our data indicated that daily wastewater collection and using a criteria of two consecutive days of positive wastewater signals was the most predictive approach to timely early warning of COVID-19 cases at the building level.

Identifiants

pubmed: 35469858
pii: S0048-9697(22)02494-9
doi: 10.1016/j.scitotenv.2022.155401
pmc: PMC9026951
pii:
doi:

Substances chimiques

Waste Water 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

155401

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Claire M Welling (CM)

Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America.

David R Singleton (DR)

Department of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America.

Steven B Haase (SB)

Departments of Biology and Medicine, Duke University, Durham, NC, United States of America.

Christian H Browning (CH)

Office of Information Technology, Duke University, Durham, NC, United States of America.

Brian R Stoner (BR)

Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America.

Claudia K Gunsch (CK)

Department of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America.

Sonia Grego (S)

Center for Water, Sanitation, Hygiene and Infectious Disease (WASH-AID), Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America. Electronic address: sonia.grego@duke.edu.

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