Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
Molecular Immunity Unit, Department of Medicine, University of Cambridge, Cambridge, UK; Department of Veterinary Medicine, University of Cambridge, Cambridge, UK.
Trends Parasitol. 2021 Dec;37(12):1038-1049. doi: 10.1016/j.pt.2021.08.007. Epub 2021 Oct 4.
Genomic epidemiology, which links pathogen genomes with associated metadata to understand disease transmission, has become a key component of outbreak response. Decreasing costs of genome sequencing and increasing computational power provide opportunities to generate and analyse large viral genomic datasets that aim to uncover the spatial scales of transmission, the demographics contributing to transmission patterns, and to forecast epidemic trends. Emerging sources of genomic data and associated metadata provide new opportunities to further unravel transmission patterns. Key challenges include how to integrate genomic data with metadata from multiple sources, how to generate efficient computational algorithms to cope with large datasets, and how to establish sampling frameworks to enable robust conclusions.
基因组流行病学将病原体基因组与相关元数据联系起来,以了解疾病传播,已成为疫情应对的一个关键组成部分。测序成本的降低和计算能力的提高为生成和分析大型病毒基因组数据集提供了机会,这些数据集旨在揭示传播的空间尺度、导致传播模式的人口统计学因素,并预测流行趋势。新兴的基因组数据来源和相关元数据提供了进一步揭示传播模式的新机会。主要挑战包括如何将基因组数据与来自多个来源的元数据整合,如何生成有效的计算算法来处理大型数据集,以及如何建立采样框架以得出可靠的结论。