Evidence map›Paper›PMID 36629447›Full record

ArticleMicrobiology spectrum2023

Rapid Assessment of SARS-CoV-2 Variant-Associated Mutations in Wastewater Using Real-Time RT-PCR.

Kata Farkas, Cameron Pellett, Rachel Williams, Natasha Alex-Sanders, Irene Bassano, Mathew R Brown, Hubert Denise, Jasmine M S Grimsley, Jessica L Kevill, Mohammad S Khalifa and 5 more

Abstract read
In one paragraph

Article in Microbiology spectrum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

15 authors.

Kata FarkasCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.ORCID 0000-0002-7068-3228
Cameron PellettCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.
Rachel WilliamsCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.
Natasha Alex-SandersCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.
Irene BassanoUK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom.
Mathew R BrownUK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom.
Hubert DeniseUK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom.
Jasmine M S GrimsleyUK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom.
Jessica L KevillCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.
Mohammad S KhalifaUK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom.
Igor PânteaCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.
Rich StoryUK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom.
Matthew J WadeUK Health Security Agency, Environmental Monitoring for Health Protection, London, United Kingdom.
Nick WoodhallCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.
Davey L JonesCentre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, Gwynedd, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Within months of the COVID-19 pandemic being declared on March 20, 2020, novel, more infectious variants of SARS-CoV-2 began to be detected in geospatially distinct regions of the world. With international travel being a lead cause of spread of the disease, the importance of rapidly identifying variants entering a country is critical. In this study, we utilized wastewater-based epidemiology (WBE) to monitor the presence of variants in wastewater generated in managed COVID-19 quarantine facilities for international air passengers entering the United Kingdom. Specifically, we developed multiplex reverse transcription quantitative PCR (RT-qPCR) assays for the identification of defining mutations associated with Beta (K417N), Gamma (K417T), Delta (156/157DEL), and Kappa (E154K) variants which were globally prevalent at the time of sampling (April to July 2021). The assays sporadically detected mutations associated with the Beta, Gamma, and Kappa variants in 0.7%, 2.3%, and 0.4% of all samples, respectively. The Delta variant was identified in 13.3% of samples, with peak detection rates and concentrations observed in May 2021 (24%), concurrent with its emergence in the United Kingdom. The RT-qPCR results correlated well with those from sequencing, suggesting that PCR-based detection is a good predictor for variant presence; although, inadequate probe binding may lead to false positive or negative results. Our findings suggest that WBE coupled with RT-qPCR may be used as a rapid, initial assessment to identify emerging variants at international borders and mass quarantining facilities.

Indexed as

COVID-19SARS-CoV-2WastewaterCOVID-19 TestingHumansMutationPandemicsReal-Time Polymerase Chain ReactionReverse Transcriptase Polymerase Chain ReactionRNARNAWastewaterairport sewage surveillancedigital PCRhuman health riskquarantine hotel monitoringsingle nucleotide polymorphismvariant of concern

Identifiers

PMID36629447
PMCPMC9927140

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.