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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/16458


    Title: Genomic surveillance of SARS-CoV-2 in taiwan: A perspective on evolutionary data interpretation and sequencing issues
    Authors: Gong, YN;Kuo, NY;Yeh, TS;Shih, SR;Chen, GW
    Contributors: National Institute of Infectious Diseases and Vaccinology
    Abstract: This review presents a comprehensive perspective on the genomic surveillance of SARS-CoV-2 in Taiwan, with a focus on next-generation sequencing and phylogenetic interpretation. This article aimed to explore how Taiwan has utilized genomic sequencing technologies and surveillance to monitor and mitigate the spread of COVID-19. We examined databases and sources of genomic sequences and highlighted the role of data science methodologies in the explanation and analyses of evolutionary data. This review addressed the challenges and limitations inherent in genomic surveillance, such as concerns regarding data quality and the necessity for interdisciplinary expertise for accurate data interpretation. Special attention was given to the unique challenges faced by Taiwan, including its high population density and major transit destination for international travelers. We underscored the far-reaching implications of genomic surveillance data for public health policy, particularly in influencing decisions regarding travel restrictions, vaccine administration, and public health decision-making. Studies were examined to demonstrate the effectiveness of using genomic data to implement public health measures. Future research should prioritize the integration of methodologies and technologies in evolutionary data science, particularly focusing on phylodynamic analytics. This integration is crucial to enhance the precision and applicability of genomic data. Overall, we have provided an overview of the significance of genomic surveillance in tracking SARS-CoV-2 variants globally and the pivotal role of data science methodologies in interpreting these data for effective public health interventions.
    Date: 2024-11-26
    Relation: Biomedical Journal. 2024 Nov 26;Article number 100820.
    Link to: http://dx.doi.org/10.1016/j.bj.2024.100820
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=&DestApp=IC2JCR
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