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dc.contributor.authorFrancis, Rodric V
dc.contributor.authorBillam, Harriet
dc.contributor.authorClarke, Mitch
dc.contributor.authorYates, Carl
dc.contributor.authorTsoleridis, Theocharis
dc.contributor.authorBerry, Louise
dc.contributor.authorMahida, Nikunj
dc.contributor.authorIrving, William L
dc.contributor.authorMoore, Christopher
dc.contributor.authorHolmes, Nadine
dc.contributor.authorBall, Jonathan K
dc.contributor.authorLoose, Matthew
dc.contributor.authorMcClure, C Patrick
dc.contributor.authorCOVID-19 Genomics UK (COG-UK) consortium
dc.date.accessioned2021-12-14T00:30:21Z
dc.date.available2021-12-14T00:30:21Z
dc.date.issued2022-01-05
dc.identifier.issn0022-1899
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/331367
dc.description.abstractNosocomial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have severely affected bed capacity and patient flow. We utilized whole-genome sequencing (WGS) to identify outbreaks and focus infection control resources and intervention during the United Kingdom's second pandemic wave in late 2020. Phylogenetic analysis of WGS and epidemiological data pinpointed an initial transmission event to an admission ward, with immediate prior community infection linkage documented. High incidence of asymptomatic staff infection with genetically identical viral sequences was also observed, which may have contributed to the propagation of the outbreak. WGS allowed timely nosocomial transmission intervention measures, including admissions ward point-of-care testing and introduction of portable HEPA14 filters. Conversely, WGS excluded nosocomial transmission in 2 instances with temporospatial linkage, conserving time and resources. In summary, WGS significantly enhanced understanding of SARS-CoV-2 clusters in a hospital setting, both identifying high-risk areas and conversely validating existing control measures in other units, maintaining clinical service overall.
dc.format.mediumPrint-Electronic
dc.publisherOxford University Press (OUP)
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSARS-CoV-2
dc.subjectWhole genome sequencing: COVID-19
dc.subjectcluster
dc.subjectgenetic epidemiology
dc.subjectinfection control
dc.subjectnosocomial transmission
dc.subjectoutbreak
dc.subjectvirus
dc.titleThe Impact of Real-Time Whole-Genome Sequencing in Controlling Healthcare-Associated SARS-CoV-2 Outbreaks.
dc.typeArticle
dc.date.updated2021-12-09T15:11:38Z
prism.publicationDate2021
prism.publicationNameJ Infect Dis
prism.startingPagejiab483-
dc.identifier.doi10.17863/CAM.78818
dcterms.dateAccepted2021-09-20
rioxxterms.versionofrecord10.1093/infdis/jiab483
rioxxterms.versionVoR
dc.contributor.orcidMcClure, C Patrick [0000-0002-1710-1049]
dc.identifier.eissn1537-6613
rioxxterms.typeJournal Article/Review
pubs.funder-project-idMRC (MC_PC_19027)
cam.issuedOnline2021-09-23
cam.orpheus.success2021-12-13 - Embargo set during processing via Fast-track
cam.depositDate2021-12-09
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
rioxxterms.freetoread.startdate2100-01-01


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International