Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom.
Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, United Kingdom.
Elife. 2021 Mar 17;10:e65453. doi: 10.7554/eLife.65453.
Understanding the effectiveness of infection control methods in reducing and preventing SARS-CoV-2 transmission in healthcare settings is of high importance. We sequenced SARS-CoV-2 genomes for patients and healthcare workers (HCWs) across multiple geographically distinct UK hospitals, obtaining 173 high-quality SARS-CoV-2 genomes. We integrated patient movement and staff location data into the analysis of viral genome data to understand spatial and temporal dynamics of SARS-CoV-2 transmission. We identified eight patient contact clusters (PCC) with significantly increased similarity in genomic variants compared to non-clustered samples. Incorporation of HCW location further increased the number of individuals within PCCs and identified additional links in SARS-CoV-2 transmission pathways. Patients within PCCs carried viruses more genetically identical to HCWs in the same ward location. SARS-CoV-2 genome sequencing integrated with patient and HCW movement data increases identification of outbreak clusters. This dynamic approach can support infection control management strategies within the healthcare setting.
了解感染控制方法在减少和预防医疗机构中 SARS-CoV-2 传播的有效性非常重要。我们对英国多家地理位置不同的医院的患者和医护人员(HCW)的 SARS-CoV-2 基因组进行了测序,获得了 173 个高质量的 SARS-CoV-2 基因组。我们将患者的移动和员工位置数据整合到病毒基因组数据分析中,以了解 SARS-CoV-2 传播的时空动态。我们确定了八个具有显著更高基因组变异相似性的患者接触簇(PCC),与非聚类样本相比。将 HCW 位置纳入分析进一步增加了 PCC 内的个体数量,并确定了 SARS-CoV-2 传播途径中的其他联系。PCC 内的患者携带的病毒与同一病房位置的 HCW 更加基因相同。将 SARS-CoV-2 基因组测序与患者和 HCW 移动数据相结合,可增加对暴发簇的识别。这种动态方法可以支持医疗机构内的感染控制管理策略。