Evidence map›Paper›PMID 35469858›Full record

ArticleThe Science of the total environment2022

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

Claire M Welling, David R Singleton, Steven B Haase, Christian H Browning, Brian R Stoner, Claudia K Gunsch, Sonia Grego

Abstract read
In one paragraph

Article in The Science of the total environment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Claire M WellingCenter 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 SingletonDepartment of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America.
Steven B HaaseDepartments of Biology and Medicine, Duke University, Durham, NC, United States of America.
Christian H BrowningOffice of Information Technology, Duke University, Durham, NC, United States of America.
Brian R StonerCenter 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 GunschDepartment of Civil and Environmental Engineering, Duke University, Durham, NC, United States of America.
Sonia GregoCenter 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.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19SARS-CoV-2HumansUniversitiesWastewaterWastewater-Based Epidemiological MonitoringWastewaterAsymptomatic surveillanceClinical casePositive predictive valueResidence hall

Identifiers

PMID35469858
PMCPMC9026951

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.