Genomic surveillance reveals COVID-19 outbreak clusters in a tertiary center in Malaysia: A cross-sectional study

• 發表在: IJID REGIONS
• Main Authors: Tajudin, Norazimah; Wang, Seok Mui; Mohamad, Mariam; Nawi, Siti Farah Alwani Mohd; Noorizhab, Mohd Nur Fakhruzzaman
• 格式: Article
• 語言: English
• 出版: ELSEVIER 2025
• 主題: Infectious Diseases
• 在線閱讀: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001443693900001

Background: Genomic surveillance activity is a useful tool in epidemiologic investigations and monitoring of virus evolution. This study aimed to describe the COVID-19 outbreaks through SARS-CoV-2 virus genomic surveillance by whole genome sequencing. Methods: A cross-sectional study was conducted using archived clinical samples of confirmed laboratory-positive COVID-19 from June 2021 to June 2022 from a tertiary center in Malaysia. The samples were subjected to whole genome sequencing. A phylogenetic tree was constructed using the maximum likelihood method in MEGA 11 software. The clinical data were obtained through paper, electronic, and hospital information systems. Results: A total of 86 clinical samples were successfully sequenced. The phylogenetic tree revealed seven clusters, consisting of 24 cases. Three clusters were associated with health care workers and health care-associated individuals. The SARS-CoV-2 Delta variants were observed in the first three clusters and subsequently replaced with the Omicron variants. Conclusions: Whole genome sequencing is robust and reliable, enhancing epidemiologic investigations, leading to the identification of clusters and preventing the spreading of COVID-19 among health care workers. Monitoring of the SARS-CoV-2 variants is necessary to study the viral dynamics and maintain the effectiveness of public health interventions.