Evidence map›Paper›PMID 39998239›Full record

ArticleMicrobiology spectrum2025

Simplifying SARS-CoV-2 wastewater-based surveillance using an automated FDA EUA assay.

Shivaprasad H Sathyanarayana, Ashlee A Robins, Diana M Toledo, Torrey L Gallagher, Gregory J Tsongalis, Jacqueline A Hubbard, Joel A Lefferts, Isabella W Martin

Abstract read
In one paragraph

Article in Microbiology spectrum, 2025. 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

8 authors.

Shivaprasad H SathyanarayanaDepartment of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, New Hampshire, USA.
Ashlee A RobinsDepartment of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, New Hampshire, USA.
Diana M ToledoThe Broad Institute at MIT and Harvard, Cambridge, Massachusetts, USA.
Torrey L GallagherDepartment of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, New Hampshire, USA.
Gregory J TsongalisDepartment of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, New Hampshire, USA.
Jacqueline A HubbardHubbard Lab Consulting, Coraopolis, Pennsylvania, USA.
Joel A LeffertsDepartment of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, New Hampshire, USA.ORCID 0000-0002-5083-7867
Isabella W MartinDepartment of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, New Hampshire, USA.ORCID 0000-0001-7974-9767

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater-based surveillance (WBS) can track the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in communities. Laboratory methods for this testing involve labor-intensive, multi-step processes. This study assessed the feasibility of performing WBS with an off-label use of an automated commercial SARS-CoV-2 assay that had received Emergency Use Authorization for human diagnostic testing from the United States Food and Drug Administration (FDA EUA). Twenty-four-hour composite samples of primary influent wastewater from seven municipalities in New Hampshire and Vermont were collected between September 2020 and February 2021, and were centrifuged upon receipt. An aliquot of fresh supernatant was immediately tested with the Abbott

Indexed as

COVID-19SARS-CoV-2WastewaterWastewater-Based Epidemiological MonitoringHumansNew HampshireRNA, ViralUnited StatesUnited States Food and Drug AdministrationVermontRNA, ViralWastewaterCOVID-19laboratory automationSARS-CoV-2wastewater

Identifiers

PMID39998239
PMCPMC11960137

What OpenQuestion holds

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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.