Evidence map›Paper›PMID 39458310›Full record

ArticleMicroorganisms2024

Real-Time Monitoring of SARS-CoV-2 Variants in Oklahoma Wastewater through Allele-Specific RT-qPCR.

Kristen Shelton, Gargi N Deshpande, Gilson J Sanchez, Jason R Vogel, A Caitlin Miller, Gabriel Florea, Erin R Jeffries, Kara B De Leόn, Bradley Stevenson, Katrin Gaardbo Kuhn

Abstract read
In one paragraph

Article in Microorganisms, 2024. 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

10 authors.

Kristen SheltonSchool of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA.ORCID 0009-0005-8221-7805
Gargi N DeshpandeDepartment of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA.
Gilson J SanchezSchool of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA.
Jason R VogelSchool of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA.
A Caitlin MillerSchool of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73071, USA.ORCID 0009-0009-8377-5779
Gabriel FloreaOklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA.
Erin R JeffriesSchool of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA.ORCID 0000-0002-9028-5390
Kara B De LeόnSchool of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA.
Bradley StevensonSchool of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA.ORCID 0000-0001-9432-9744
Katrin Gaardbo KuhnDepartment of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA.

Funding

City of Oklahoma City N.ACity of Tulsa N.APresbyterian Health Foundation N.ARockefeller Foundation N.A
6 · The paper itself

Abstract

During the COVID-19 pandemic, wastewater surveillance was used to monitor community transmission of SARS-CoV-2. As new genetic variants emerged, the need for timely identification of these variants in wastewater became an important focus. In response to increased reports of Omicron transmission across the United States, the Oklahoma Wastewater Surveillance team utilized allele-specific RT-qPCR assays to detect and differentiate variants, such as Omicron, from other variants found in wastewater in Oklahoma. The PCR assays showed presence of the Omicron variant in Oklahoma on average two weeks before official reports, which was confirmed through genomic sequencing of selected wastewater samples. Through continued surveillance from November 2021 to January 2022, we also demonstrated the transition from prevalence of the Delta variant to prevalence of the Omicron variant in local communities. We further assessed how this transition correlated with certain demographic factors characterizing each community. Our results highlight RT-qPCR assays as a rapid, simple, and cost-effective method for monitoring the community spread of SARS-CoV-2 genetic variants in wastewater. Additionally, they demonstrate that specific demographic factors such as ethnic composition and household income can correlate with the timing of SARS-CoV-2 variant introduction and spread.

Indexed as

early warningOmicronRT-qPCRSARS-CoV-2sequencingvariantwastewater surveillance

Identifiers

PMID39458310
PMCPMC11509313

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.