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Comparison of SARS-CoV-2 Variant Screening and Whole Genome Sequencing at an Indonesian Tertiary Hospitals

1Department of Clinical Microbiology, Faculty of Medicine, Universitas Diponegoro, Indonesia

2Microbiology Laboratory, Diponegoro National Hospital, Indonesia

3Microbiology Laboratory, KRMT Wongsonegoro Hospital, Indonesia

4 Department of Clinical Microbiology, Kariadi Hospital, Indonesia

5 Department of Microbiology, Faculty of Medicine, Universitas Jendral Soedirman, Indonesia

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Received: 3 Jul 2023; Revised: 14 Oct 2023; Accepted: 31 Oct 2023; Available online: 31 Dec 2023; Published: 31 Dec 2023.
Open Access Copyright (c) 2023 Journal of Biomedicine and Translational Research
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Background: The global COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), experienced a surge in cases with the emergence of the Omicron variant. Despite increasing vaccination coverage, Indonesia witnessed peaks in COVID-19 cases. Variant screening and whole genome sequencing (WGS) play a crucial role in identifying SARS-CoV-2 variants and monitoring their spread.

Objective: The objective of this study was to compare variant screening results with WGS data, assess the prevalence of subvariants, and analyze their correlation with demographic and cycle threshold (CT) values.

Methods: Between November 7th and 18th, 2022, variant screening and WGS were conducted on samples with CT values below 30. Variant screening utilized the mBioCov-19+ VarScreen assay, while WGS was performed on the Oxford Nanopore Technologies (ONT) platform. Bioinformatics analysis was performed using epi2melabs. Demographic data and CT values were analyzed. 

Results: Out of 89 subjects, all tested positive for the Omicron variant through variant screening. The variant screening identified two subvariants: Omicron BA.2 (64%) and Omicron B.1.1.529.1 (36%). WGS revealed that the XBB subvariant was the most dominant (52.8%), followed by BQ.1 (22.5%) and BA.5 (13.5%). When VarScreen indicated BA.2, the majority of WGS results showed XBB (82.5%), while for B.1.1.529.1, the majority of WGS results were BQ.1 (59.4%), followed by BA.5 (37.5%). XBB was the most prevalent variant in both females and males, while BQ.1 was more dominant in females (80%). No infections were detected among children aged 1-5 years. All variants had CT values below 24.

Conclusion: Variant screening provides accurate and quick results for detecting the Omicron variant in laboratories without WGS capacity. However, it is important to continuously update the screening methodology based on the prevailing circulating variants. During the study period, XBB emerged as the predominant subvariant of the Omicron variant.

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Keywords: Variant screening; Whole Genome Sequencing; Omicron; XBB

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