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. 2023 Feb;16(2):171-181.
doi: 10.1016/j.jiph.2022.12.007. Epub 2022 Dec 14.

Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital

Affiliations

Analysis of SARS-CoV-2 genomic surveillance data during the Delta and Omicron waves at a Saudi tertiary referral hospital

D Obeid et al. J Infect Public Health. 2023 Feb.

Abstract

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 χ2 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.

Keywords: Breakthrough infections (BTI); COVID-19; Delta; Omicron; SARS-CoV-2 genomic surveillance; Variant of concern (VOC).

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Conflict of interest statement

Competing interests The authors declare that the research was conducted in the absence of any potential conflict of interest.

Figures

Fig. 1
Fig. 1
Distribution of SARS-CoV-2 variants over time, by age and by vaccination dose. A) Density plot showing the percentage of samples with each variant over time: the first cases detected were non-VOCs; Delta dominated from November to the end of December; and Omicron began dominating in January. B) Distribution of variants by age group. C) Distribution of variants by vaccination status and dose.
Fig. 2
Fig. 2
Heatmap showing spike variants by patient demographic and clinical characteristics. Heatmap columns represent detected variants, and rows represent the indicated characteristic. The frequency of each variant is shown in each square according to the color gradient given in the key, with purple being the lowest frequency and yellow being the highest.
Fig. 3
Fig. 3
Phylogenetic analysis of transmission in a single center. The sequences shown in the figure are annotated to reflect patient data: sample ID, variant, month of infection, vaccinated (V) or unvaccinated (UV), healthcare worker (HCW) or not (N), and intensive care unit (ICU) or (R) regular case. Overall, there were 8 main clusters using the TIM2 + F + I model.
Fig. 4
Fig. 4
Phylogenetic analysis for outbreaks including ICU patients. The sequences shown in the figure were annotated to reflect patient data: sample ID, variant, month of infection, vaccinated (V) or unvaccinated (UV), healthcare worker (HCW) or not (N), and intensive care unit (ICU) or (R) regular case. Overall, there were 21 patients, and the estimated tree was constructed using the TIM2 + F + I model. The estimated branch length is shown in each node.

References

    1. Zhou P., Yang X.-L., Wang X.-G., Hu B., Zhang L., Zhang W., et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;579:270–273. doi: 10.1038/s41586-020-2012-7. - DOI - PMC - PubMed
    1. Ritchie Hannah, Ortiz-Ospina Esteban, Beltekian Diana, Mathieu Edouard, Hasell Joe, Macdonald Bobbie, et al. COVID-19 data explorer. OurworldindataOrg; 2022. 〈https://ourworldindata.org〉, [Accessed 14 July 2022].
    1. Domingo E., Holland J.J. RNA virus mutations and fitness for survival. Annu Rev Microbiol. 1997;51:151–178. doi: 10.1146/annurev.micro.51.1.151. - DOI - PubMed
    1. Planas D., Veyer D., Baidaliuk A., Staropoli I., Guivel-Benhassine F., Rajah M.M., et al. Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization. Nature. 2021;596:276–280. doi: 10.1038/s41586-021-03777-9. - DOI - PubMed
    1. WHO. Tracking SARS-CoV-2 variants; 2022. 〈https://www.who.int/en/activities/tracking-SARS-CoV-2-variants/〉, [Accessed 14 July 2022].