Work

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

Year: 2025

Type: article

Abstract: • Genomic surveillance revealed health care outbreaks clusters. • Following standard operating procedures strictly helps prevent interhospital transmission of COVID-19. • Integration of whole genome sequencing and epidemiologic data links cases and tracks virus evolution. • Variant monitoring guides public health infection control measures. 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. 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. 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. 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.

Source: IJID Regions

DOI: 10.1016/j.ijregi.2025.100604

Authors: Norazimah Tajudin, Seok Mui Wang, Mariam Mohamad, Siti Farah Alwani Mohd Nawi, Mohd Nur Fakhruzzaman Noorizhab

Institutions: Universiti Teknologi MARA System, Universiti Teknologi MARA

Language: English

Topic: SARS-CoV-2 and COVID-19 Research

Subfield: Infectious Diseases

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,380