Evidence map›Paper›PMID 36428863›Full record

ArticleDiagnostics (Basel, Switzerland)2022

Efficient Tracing of the SARS-CoV-2 Omicron Variants in Santa Barbara County Using a Rapid Quantitative Reverse Transcription PCR Assay.

Zach Aralis, Stewart Comer, Henning Ansorg, Carl Palmer, Jennifer Smith, Stuart C Feinstein, Lynn N Fitzgibbons, Carolina Arias

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Zach AralisDepartment of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA 93106, USA.ORCID 0000-0002-1292-5540
Stewart ComerSanta Barbara County Public Health Department, Santa Barbara, CA 93106, USA.
Henning AnsorgSanta Barbara County Public Health Department, Santa Barbara, CA 93106, USA.
Carl PalmerLegacyWorks Group, Santa Barbara, CA 93106, USA.
Jennifer SmithCalifornia NanoSystems Institute, University of California, Santa Barbara, CA 93106, USA.
Stuart C FeinsteinDepartment of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA 93106, USA.
Lynn N FitzgibbonsDepartment of Medical Education, Division of Infectious Diseases, Santa Barbara Cottage Hospital, Santa Barbara, CA 93106, USA.
Carolina AriasDepartment of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA 93106, USA.ORCID 0000-0002-4445-0826

Funding

Cottage Health KKGF-KK83-8-447636-47735University of California, Santa Barbara AC-ACM01Z-8-403749-19900
6 · The paper itself

Abstract

The emergence of the SARS-CoV-2 Omicron variant in 2021 is associated with a global surge of cases in late 2021 and early 2022. Identifying the introduction of novel SARS-CoV-2 variants to a population is imperative to inform decisions by clinicians and public health officials. Here, we describe a quantitative reverse transcription PCR-based assay (RT-qPCR) targeting unique mutations in the Omicron BA.1/BA1.1 and BA.2 viral genomes. This assay accurately and precisely detect the presence of these Omicron variants in patient samples in less than four hours. Using this assay, we tested 270 clinical samples and detected the introduction of Omicron BA.1/BA1.1 and BA.2 in the Santa Barbara County (SBC) population in December 2021 and February 2022, respectively. Identifying Omicron variants using this RT-qPCR assay showed complete concordance with whole viral genome sequencing; both assays indicated that Omicron was the dominant variant in SB County. Our data substantiate that RT-qPCR-based virus detection assays offer a fast and inexpensive alternative to NGS for virus variant-specific detection approach, which allows streamlining the detection of Omicron variants in patient samples.

Indexed as

epidemiologymolecular assayNGSomicronpublic healthqPCRSARS-CoV-2

Identifiers

PMID36428863
PMCPMC9689663

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.