Open AccessGenomic and healthcare dynamics of nosocomial SARS-CoV-2 transmission
Author(s) -
Jamie M Ellingford,
Ryan George,
John H McDermott,
Shazaad Ahmad,
Jonathan J Edgerley,
David Gokhale,
William G. Newman,
Stephen Ball,
Nicholas Machin,
Graeme C M Black
Publication year - 2021
Publication title -
elife
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.879
H-Index - 139
ISSN - 2050-084X
DOI - 10.7554/elife.65453
Subject(s) - genome , transmission (telecommunications) , covid-19 , health care , outbreak , computational biology , infection control , genomics , biology , medicine , genetics , virology , disease , computer science , gene , infectious disease (medical specialty) , intensive care medicine , pathology , telecommunications , economics , economic growth
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.