Evidence map›Paper›PMID 41925345›Full record

ArticlemSphere2026

Rapid identification of COVID wastewater surges in the absence of case data.

Victoria I Verhoeve, Joshua Lambert, Amy Jones, Timothy Driscoll

Abstract read
In one paragraph

Article in mSphere, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Victoria I VerhoeveDepartment of Biology, West Virginia University, Morgantown, West Virginia, USA.
Joshua LambertDepartment of Biology, West Virginia University, Morgantown, West Virginia, USA.
Amy JonesDepartment of Biology, West Virginia University, Morgantown, West Virginia, USA.
Timothy DriscollDepartment of Biology, West Virginia University, Morgantown, West Virginia, USA.ORCID 0000-0002-5119-0372

Funding

State of West Virginia | West Virginia Department of Health and Human Resources (DHHR) G210999
6 · The paper itself

Abstract

Genetic testing of community wastewater (wastewater surveillance) is a valuable tool for following trends in the abundance of SARS-CoV-2 and other infectious disease pathogens over time. Wastewater surveillance is increasingly important in the absence of corresponding epidemiological data, particularly for infectious diseases with limited timely data on clinical case incidences. Due to the inherent noise in wastewater data, a single sample is not sufficient to identify a sustained trend in the abundance of a target. This challenge is magnified in resource-limited settings where samples may be collected only once or twice per week. In this work, we collected 24-h composite samples of wastewater daily from a single facility for nearly 4 years. We use this high-frequency data set to describe a method for identifying trends in SARS-CoV-2 abundance in wastewater based on a variety of collection frequencies. Our results indicate that collecting two 24-h composites per week for 2 weeks is sufficient to accurately identify a SARS-CoV-2 surge. We conclude that low-frequency wastewater sampling performs reasonably well in identifying trends in a timely fashion.IMPORTANCEWastewater surveillance is increasingly being used to track trends in infectious disease targets such as SARS-CoV-2, often in the absence of widespread clinical data. In order to interpret the results of wastewater surveillance appropriately in these contexts, it is important to understand how to identify a surge in abundance in time to provoke appropriate downstream responses. This information can be used to adjust collection strategies to optimize target surveillance, particularly in resource-limited settings.

Indexed as

COVID-19SARS-CoV-2WastewaterWastewater-Based Epidemiological MonitoringHumansWastewaterbioinformaticsinfectious diseaseSARS-CoV-2wastewater testing

Identifiers

PMID41925345
PMCPMC13123706

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.