Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Sydney, New South Wales, Australia.
Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia.
Nat Med. 2020 Sep;26(9):1398-1404. doi: 10.1038/s41591-020-1000-7. Epub 2020 Jul 9.
In January 2020, a novel betacoronavirus (family Coronaviridae), named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the etiological agent of a cluster of pneumonia cases occurring in Wuhan City, Hubei Province, China. The disease arising from SARS-CoV-2 infection, coronavirus disease 2019 (COVID-19), subsequently spread rapidly causing a worldwide pandemic. Here we examine the added value of near real-time genome sequencing of SARS-CoV-2 in a subpopulation of infected patients during the first 10 weeks of COVID-19 containment in Australia and compare findings from genomic surveillance with predictions of a computational agent-based model (ABM). Using the Australian census data, the ABM generates over 24 million software agents representing the population of Australia, each with demographic attributes of an anonymous individual. It then simulates transmission of the disease over time, spreading from specific infection sources, using contact rates of individuals within different social contexts. We report that the prospective sequencing of SARS-CoV-2 clarified the probable source of infection in cases where epidemiological links could not be determined, significantly decreased the proportion of COVID-19 cases with contentious links, documented genomically similar cases associated with concurrent transmission in several institutions and identified previously unsuspected links. Only a quarter of sequenced cases appeared to be locally acquired and were concordant with predictions from the ABM. These high-resolution genomic data are crucial to track cases with locally acquired COVID-19 and for timely recognition of independent importations once border restrictions are lifted and trade and travel resume.
2020 年 1 月,一种新型贝塔冠状病毒(科冠状病毒科),命名为严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2),被鉴定为中国湖北省武汉市发生的一组肺炎病例的病原体。由 SARS-CoV-2 感染引起的疾病,即 2019 年冠状病毒病(COVID-19),随后迅速传播,造成了全球大流行。在这里,我们研究了在澳大利亚 COVID-19 遏制的前 10 周内对感染患者亚群进行 SARS-CoV-2 近实时基因组测序的附加价值,并将基因组监测结果与基于计算代理的模型(ABM)的预测进行了比较。使用澳大利亚人口普查数据,ABM 生成了超过 2400 万个代表澳大利亚人口的软件代理,每个代理都具有匿名个体的人口统计学属性。然后,它模拟疾病随时间的传播,从特定的感染源开始,使用不同社会环境中个体的接触率进行传播。我们报告说,前瞻性 SARS-CoV-2 测序澄清了在无法确定流行病学联系的情况下感染的可能来源,大大降低了有争议联系的 COVID-19 病例比例,记录了与多个机构同时传播相关的基因组相似病例,并确定了以前未怀疑的联系。只有四分之一的测序病例似乎是本地获得的,并且与 ABM 的预测一致。这些高分辨率基因组数据对于追踪本地获得的 COVID-19 病例以及在边境限制解除、贸易和旅行恢复后及时识别独立输入病例至关重要。