Tracking the Initial Diffusion of SARS-CoV-2 Omicron Variant in Italy by RT-PCR and Comparison with Alpha and Delta Variants Spreading.

COVID-19 RT-PCR SARS-CoV-2 VOC molecular diagnosis naso-oropharyngeal swabs omicron variant rapid screening spreading

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
11 Feb 2022
Historique:
received: 11 01 2022
revised: 08 02 2022
accepted: 10 02 2022
entrez: 25 2 2022
pubmed: 26 2 2022
medline: 26 2 2022
Statut: epublish

Résumé

The emergence of the Omicron SARS-CoV-2 variant caused public health concerns worldwide, raising the need for the improvement of rapid monitoring strategies. The present manuscript aimed at providing evidence of the utility of a diagnostic kit for the routine testing of SARS-CoV-2 infection as a cost-effective method for tracking the Omicron variant in Italy. The study was conducted on patients' naso-oropharyngeal-swab-derived RNA samples. These samples were subjected to RT-PCR using the TaqPath COVID-19 RT PCR CE IVD kit. Nonparametric testing and polynomial models fitting were used to compare the spreading of Alpha, Delta and Omicron variants. The samples of interest were correctly amplified and displayed the presence of S gene-target failure, suggesting that these patients carry the Omicron variant. The trend of diffusion was found to be significantly different and more rapid compared with that of the Alpha and Delta variants in our cohorts. Overall, these results highlight that the S gene target failure was a very useful tool for the immediate and inexpensive tracking of Omicron variant in the three weeks from the first detection. Thus, our approach could be used as a first-line screening to reduce the time and costs of monitoring strategies, facilitating the management of preventive and counteracting measures against COVID-19.

Identifiants

pubmed: 35204558
pii: diagnostics12020467
doi: 10.3390/diagnostics12020467
pmc: PMC8870788
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Valerio Caputo (V)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Department of Biomedicine and Prevention, Tor Vergata University, 00133 Rome, Italy.

Giulia Calvino (G)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Claudia Strafella (C)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Department of Biomedicine and Prevention, Tor Vergata University, 00133 Rome, Italy.

Andrea Termine (A)

Data Science Unit, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Carlo Fabrizio (C)

Data Science Unit, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Giulia Trastulli (G)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Arcangela Ingrascì (A)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Cristina Peconi (C)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Silvia Bardini (S)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Angelo Rossini (A)

Medical Services, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Antonino Salvia (A)

Medical Services, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Giovanna Borsellino (G)

Neuroimmunology Unit, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Luca Battistini (L)

Neuroimmunology Unit, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Carlo Caltagirone (C)

Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.

Raffaella Cascella (R)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Department of Biomedicine and Prevention, Tor Vergata University, 00133 Rome, Italy.

Emiliano Giardina (E)

Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Department of Biomedicine and Prevention, Tor Vergata University, 00133 Rome, Italy.

Classifications MeSH