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结合公共测序数据库理解医学中心中早期大流行严重急性呼吸综合征冠状病毒 2 传播,以减轻偏倚。

Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias.

机构信息

National Emerging Infectious Diseases Laboratories, Boston University, Boston, Massachusetts, USA.

Bioinformatics Program, Boston University, Boston, Massachusetts, USA.

出版信息

J Infect Dis. 2022 Nov 11;226(10):1704-1711. doi: 10.1093/infdis/jiac348.

Abstract

BACKGROUND

Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare workers (HCWs) have faced risk of infection from within the workplace via patients and staff as well as from the outside community, complicating our ability to resolve transmission chains in order to inform hospital infection control policy. Here we show how the incorporation of sequences from public genomic databases aided genomic surveillance early in the pandemic when circulating viral diversity was limited.

METHODS

We sequenced a subset of discarded, diagnostic SARS-CoV-2 isolates between March and May 2020 from Boston Medical Center HCWs and combined this data set with publicly available sequences from the surrounding community deposited in GISAID with the goal of inferring specific transmission routes.

RESULTS

Contextualizing our data with publicly available sequences reveals that 73% (95% confidence interval, 63%-84%) of coronavirus disease 2019 cases in HCWs are likely novel introductions rather than nosocomial spread.

CONCLUSIONS

We argue that introductions of SARS-CoV-2 into the hospital environment are frequent and that expanding public genomic surveillance can better aid infection control when determining routes of transmission.

摘要

背景

在严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2)大流行期间,医护人员(HCWs)面临着来自患者和工作人员内部以及来自外部社区的感染风险,这使得我们难以确定传播链,从而为医院感染控制政策提供信息。在这里,我们展示了在病毒多样性有限的大流行早期,如何将公共基因组数据库中的序列纳入基因组监测。

方法

我们对 2020 年 3 月至 5 月期间来自波士顿医疗中心 HCWs 的部分废弃的诊断性 SARS-CoV-2 分离物进行了测序,并将该数据集与在 GISAID 中存储的周边社区的公开序列相结合,旨在推断特定的传播途径。

结果

用公开序列对我们的数据进行上下文分析表明,HCWs 中 73%(95%置信区间,63%-84%)的 2019 年冠状病毒病病例可能是新的传入病例,而不是医院内传播。

结论

我们认为,SARS-CoV-2 引入医院环境的情况很常见,扩大公共基因组监测可以更好地帮助确定传播途径,从而进行感染控制。

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