Differentiation of SARS-CoV-2 Variants Using RT-qPCRs by Targeting Recurrent Mutation Sites: A Diagnostic Laboratory Experience from Multi-Center Regional Study, August 2020–December 2021, Poland

Author:

Wegrzynska KarolinaORCID,Komiazyk MagdalenaORCID,Walory JaroslawORCID,Kozinska AleksandraORCID,Wasko IzabelaORCID,Baraniak AnnaORCID

Abstract

Rapid identification of SARS-CoV-2 variants is essential for epidemiological surveillance. RT-qPCR-based variant differentiation tests can be used to quickly screen large sets of samples for relevant variants of concern/interest; this study was conducted on specimens collected at 11 centers located in Poland during routine SARS-CoV-2 diagnostics between August 2020 and December 2021. A total of 1096 samples (with CT < 30) were screened for Alpha, Beta, Delta, Kappa and Omicron variants using commercial assays targeting repeat mutation sites. Variants were assigned to 434 (39.6%) specimens; the remaining 662 (60.4%) samples were not classified (no tested mutations detected). Alpha (n = 289; 66.59%), Delta (n = 115; 26.5%), Kappa (n = 30; 6.91%) and Omicron (n = 2; 0.46%) variants were identified and their distribution changed over time. The first Alpha variant appeared in October 2020, and it began to gradually increase its proportion of the virus population by June 2021. In July 2021, it was replaced by the Delta variant, which already dominated by the end of the year. The first Kappa was detected in October 2021, while Omicron was found in December 2021. The screening of samples allowed the determination of epidemiological trends over a time interval reflecting the national COVID-19 waves.

Funder

Narodowy Instytut Leków

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

Reference45 articles.

1. Coronavirus Disease 2019;World Health Organization

2. A Novel Coronavirus from Patients with Pneumonia in China, 2019

3. WHO Coronavirus (COVID-19) Dashboard;World Health Organization

4. Global Economic Effects of COVID-19: Overview—CRS Reports

5. Munich: Global Initiative on Sharing All Influenza Data. c2008–2022 https://www.gisaid.org

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