Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU München, Munich, Germany.
German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.
Euro Surveill. 2021 Oct;26(43). doi: 10.2807/1560-7917.ES.2021.26.43.2002066.
BackgroundIn the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.AimWe applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.MethodsWe investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.ResultsWe identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.ConclusionsEarly spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.
背景
在 SARS-CoV-2 大流行期间,病毒基因组的获取速度前所未有,但由于基因组序列采样存在时空偏差,如果没有额外的背景数据,就无法进行系统地理学推断。
目的
我们应用基因组流行病学来追踪 SARS-CoV-2 在国际、国家和地方层面的传播,通过整合序列数据和时空元数据,说明如何将传播链解析到单个事件和个人的水平。
方法
我们调查了德国慕尼黑一家大学医院 2020 年 2 月 29 日至 5 月 27 日期间的 289 例 COVID-19 病例。使用 ARTIC 方案,我们从 174 份 SARS-CoV-2 阳性呼吸道样本中获得了近乎全长的病毒基因组。使用 Auspice 软件进行系统发育分析,并结合患者和医护人员的旅行史、人际接触和感知的高风险暴露的病历报告,来描述集群暴发,并建立可能的传播情景和时间线。
结果
我们在第一次大流行浪潮的最初几周在慕尼黑大都市区发现了多个独立的传入,主要是由从阿尔卑斯山流行的滑雪区返回的旅行者引起的。在这些早期的几周里,患者(分别为 9.6%和 54%)和特别是医护人员(分别为 9.6%和 54%)中假定的医院获得性感染率很高,我们说明了如何通过结合病毒序列和人际互动的时空网络,以高分辨率解析传播链。
结论
SARS-CoV-2 在欧洲的早期传播是由冬季假期期间的超级传播事件和区域热点催化的。基因组流行病学可用于追踪病毒传播,并为有效的遏制策略提供信息。