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Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital
BACKGROUND: Studying the genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may help determine outbreak clusters and virus transmission advantages to aid public health efforts during the pandemic. Thus, we tracked the evolution of SARS-CoV-2 by variant epidemiology, br...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747229/ https://www.ncbi.nlm.nih.gov/pubmed/36543031 http://dx.doi.org/10.1016/j.jiph.2022.12.007 |
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author | Obeid, D. Al-Qahtani, A. Almaghrabi, R. Alghamdi, S. Alsanea, M. Alahideb, B. Almutairi, S. Alsuwairi, F. Al-Abdulkareem, M. Asiri, M. Alshukairi, A. Alkahtany, J. Altamimi, S. Mutabagani, M. Althawadi, S. Alanzi, F. Alhamlan, F. |
author_facet | Obeid, D. Al-Qahtani, A. Almaghrabi, R. Alghamdi, S. Alsanea, M. Alahideb, B. Almutairi, S. Alsuwairi, F. Al-Abdulkareem, M. Asiri, M. Alshukairi, A. Alkahtany, J. Altamimi, S. Mutabagani, M. Althawadi, S. Alanzi, F. Alhamlan, F. |
author_sort | Obeid, D. |
collection | PubMed |
description | BACKGROUND: Studying the genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may help determine outbreak clusters and virus transmission advantages to aid public health efforts during the pandemic. Thus, we tracked the evolution of SARS-CoV-2 by variant epidemiology, breakthrough infection, and patient characteristics as the virus spread during the Delta and Omicron waves. We also conducted phylogenetic analyses to assess modes of transmission. METHODS: Nasopharyngeal samples were collected from a cohort of 900 patients with positive polymerase chain reaction (PCR) test results confirming COVID-19 disease. Samples underwent real-time PCR detection using TaqPath assays. Sequencing was performed with Ion GeneStudio using the Ion AmpliSeq™ SARS-CoV-2 panel. Variant calling was performed with Torrent Suite™ on the Torrent Server. For phylogenetic analyses, the MAFFT tool was used for alignment and the maximum likelihood method with the IQ-TREE tool to build the phylogenetic tree. Data were analyzed using SAS statistical software. Analysis of variance or t tests were used to assess continuous variables, and χ(2) tests were used to assess categorical variables. Univariate and multivariate logistic regression analyses were preformed to estimate odds ratios (ORs). RESULTS: The predominant variants in our cohort of 900 patients were non–variants of concern (11.1 %), followed by Alpha (4.1 %), Beta (5.6 %), Delta (21.2 %), and Omicron (58 %). The Delta wave had more male than female cases (112 vs. 78), whereas the Omicron wave had more female than male cases (311 vs. 208). The oldest patients (mean age, 43.4 years) were infected with non–variants of concern; the youngest (mean age, 33.7 years), with Omicron. Younger patients were mostly unvaccinated, whereas elderly patients were mostly vaccinated, a statistically significant difference. The highest risk for breakthrough infection by age was for patients aged 30–39 years (OR = 12.4, CI 95 %: 6.6–23.2), followed by patients aged 40–49 years (OR = 11.2, CI 95 %: 6.1–23.1) and then 20–29 years (OR = 8.2, CI 95 %: 4.4–15.4). Phylogenetic analyses suggested the interaction of multiple cases related to outbreaks for breakthrough infections, healthcare workers, and intensive care unit admission. CONCLUSION: The findings of this study highlighted several major public health ramifications, including the distribution of variants over a wide range of demographic and clinical variables and by vaccination status. |
format | Online Article Text |
id | pubmed-9747229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97472292022-12-14 Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital Obeid, D. Al-Qahtani, A. Almaghrabi, R. Alghamdi, S. Alsanea, M. Alahideb, B. Almutairi, S. Alsuwairi, F. Al-Abdulkareem, M. Asiri, M. Alshukairi, A. Alkahtany, J. Altamimi, S. Mutabagani, M. Althawadi, S. Alanzi, F. Alhamlan, F. J Infect Public Health Original Article BACKGROUND: Studying the genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may help determine outbreak clusters and virus transmission advantages to aid public health efforts during the pandemic. Thus, we tracked the evolution of SARS-CoV-2 by variant epidemiology, breakthrough infection, and patient characteristics as the virus spread during the Delta and Omicron waves. We also conducted phylogenetic analyses to assess modes of transmission. METHODS: Nasopharyngeal samples were collected from a cohort of 900 patients with positive polymerase chain reaction (PCR) test results confirming COVID-19 disease. Samples underwent real-time PCR detection using TaqPath assays. Sequencing was performed with Ion GeneStudio using the Ion AmpliSeq™ SARS-CoV-2 panel. Variant calling was performed with Torrent Suite™ on the Torrent Server. For phylogenetic analyses, the MAFFT tool was used for alignment and the maximum likelihood method with the IQ-TREE tool to build the phylogenetic tree. Data were analyzed using SAS statistical software. Analysis of variance or t tests were used to assess continuous variables, and χ(2) tests were used to assess categorical variables. Univariate and multivariate logistic regression analyses were preformed to estimate odds ratios (ORs). RESULTS: The predominant variants in our cohort of 900 patients were non–variants of concern (11.1 %), followed by Alpha (4.1 %), Beta (5.6 %), Delta (21.2 %), and Omicron (58 %). The Delta wave had more male than female cases (112 vs. 78), whereas the Omicron wave had more female than male cases (311 vs. 208). The oldest patients (mean age, 43.4 years) were infected with non–variants of concern; the youngest (mean age, 33.7 years), with Omicron. Younger patients were mostly unvaccinated, whereas elderly patients were mostly vaccinated, a statistically significant difference. The highest risk for breakthrough infection by age was for patients aged 30–39 years (OR = 12.4, CI 95 %: 6.6–23.2), followed by patients aged 40–49 years (OR = 11.2, CI 95 %: 6.1–23.1) and then 20–29 years (OR = 8.2, CI 95 %: 4.4–15.4). Phylogenetic analyses suggested the interaction of multiple cases related to outbreaks for breakthrough infections, healthcare workers, and intensive care unit admission. CONCLUSION: The findings of this study highlighted several major public health ramifications, including the distribution of variants over a wide range of demographic and clinical variables and by vaccination status. The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2023-02 2022-12-14 /pmc/articles/PMC9747229/ /pubmed/36543031 http://dx.doi.org/10.1016/j.jiph.2022.12.007 Text en © 2022 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Article Obeid, D. Al-Qahtani, A. Almaghrabi, R. Alghamdi, S. Alsanea, M. Alahideb, B. Almutairi, S. Alsuwairi, F. Al-Abdulkareem, M. Asiri, M. Alshukairi, A. Alkahtany, J. Altamimi, S. Mutabagani, M. Althawadi, S. Alanzi, F. Alhamlan, F. Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital |
title | Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital |
title_full | Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital |
title_fullStr | Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital |
title_full_unstemmed | Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital |
title_short | Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital |
title_sort | analysis of sars-cov-2 genomic surveillance data during the delta and omicron waves at a saudi tertiary referral hospital |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747229/ https://www.ncbi.nlm.nih.gov/pubmed/36543031 http://dx.doi.org/10.1016/j.jiph.2022.12.007 |
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