Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study.
Adolescent
Adult
Aged
Aged, 80 and over
Betacoronavirus
/ genetics
COVID-19
Child
Child, Preschool
Coronavirus Infections
/ epidemiology
Cross Infection
/ epidemiology
England
/ epidemiology
Female
Genome, Viral
/ genetics
Hospitals, University
Humans
Infant
Infant, Newborn
Infection Control
/ methods
Male
Middle Aged
Pandemics
/ prevention & control
Patient Safety
Phylogeny
Pneumonia, Viral
/ epidemiology
Polymerase Chain Reaction
/ methods
Polymorphism, Single Nucleotide
Prospective Studies
SARS-CoV-2
Whole Genome Sequencing
/ methods
Young Adult
Journal
The Lancet. Infectious diseases
ISSN: 1474-4457
Titre abrégé: Lancet Infect Dis
Pays: United States
ID NLM: 101130150
Informations de publication
Date de publication:
11 2020
11 2020
Historique:
received:
15
05
2020
revised:
16
06
2020
accepted:
22
06
2020
pubmed:
18
7
2020
medline:
11
11
2020
entrez:
18
7
2020
Statut:
ppublish
Résumé
The burden and influence of health-care associated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unknown. We aimed to examine the use of rapid SARS-CoV-2 sequencing combined with detailed epidemiological analysis to investigate health-care associated SARS-CoV-2 infections and inform infection control measures. In this prospective surveillance study, we set up rapid SARS-CoV-2 nanopore sequencing from PCR-positive diagnostic samples collected from our hospital (Cambridge, UK) and a random selection from hospitals in the East of England, enabling sample-to-sequence in less than 24 h. We established a weekly review and reporting system with integration of genomic and epidemiological data to investigate suspected health-care associated COVID-19 cases. Between March 13 and April 24, 2020, we collected clinical data and samples from 5613 patients with COVID-19 from across the East of England. We sequenced 1000 samples producing 747 high-quality genomes. We combined epidemiological and genomic analysis of the 299 patients from our hospital and identified 35 clusters of identical viruses involving 159 patients. 92 (58%) of 159 patients had strong epidemiological links and 32 (20%) patients had plausible epidemiological links. These results were fed back to clinical, infection control, and hospital management teams, leading to infection-control interventions and informing patient safety reporting. We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and showed the benefit of combined genomic and epidemiological analysis for the investigation of health-care associated COVID-19. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection-control interventions to further reduce health-care associated infections. Our findings have important implications for national public health policy as they enable rapid tracking and investigation of infections in hospital and community settings. COVID-19 Genomics UK funded by the Department of Health and Social Care, UK Research and Innovation, and the Wellcome Sanger Institute.
Sections du résumé
BACKGROUND
The burden and influence of health-care associated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unknown. We aimed to examine the use of rapid SARS-CoV-2 sequencing combined with detailed epidemiological analysis to investigate health-care associated SARS-CoV-2 infections and inform infection control measures.
METHODS
In this prospective surveillance study, we set up rapid SARS-CoV-2 nanopore sequencing from PCR-positive diagnostic samples collected from our hospital (Cambridge, UK) and a random selection from hospitals in the East of England, enabling sample-to-sequence in less than 24 h. We established a weekly review and reporting system with integration of genomic and epidemiological data to investigate suspected health-care associated COVID-19 cases.
FINDINGS
Between March 13 and April 24, 2020, we collected clinical data and samples from 5613 patients with COVID-19 from across the East of England. We sequenced 1000 samples producing 747 high-quality genomes. We combined epidemiological and genomic analysis of the 299 patients from our hospital and identified 35 clusters of identical viruses involving 159 patients. 92 (58%) of 159 patients had strong epidemiological links and 32 (20%) patients had plausible epidemiological links. These results were fed back to clinical, infection control, and hospital management teams, leading to infection-control interventions and informing patient safety reporting.
INTERPRETATION
We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and showed the benefit of combined genomic and epidemiological analysis for the investigation of health-care associated COVID-19. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection-control interventions to further reduce health-care associated infections. Our findings have important implications for national public health policy as they enable rapid tracking and investigation of infections in hospital and community settings.
FUNDING
COVID-19 Genomics UK funded by the Department of Health and Social Care, UK Research and Innovation, and the Wellcome Sanger Institute.
Identifiants
pubmed: 32679081
pii: S1473-3099(20)30562-4
doi: 10.1016/S1473-3099(20)30562-4
pmc: PMC7806511
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1263-1272Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 204870/Z/16/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/N029399/1
Pays : United Kingdom
Commentaires et corrections
Type : CommentIn
Type : ErratumIn
Type : ErratumIn
Type : CommentIn
Informations de copyright
Copyright © 2020 Elsevier Ltd. All rights reserved.
Références
Nature. 2020 Mar;579(7798):270-273
pubmed: 32015507
Virus Evol. 2016 Jun 22;2(1):vew016
pubmed: 28694998
Nat Med. 2020 Apr;26(4):450-452
pubmed: 32284615
J Infect Dis. 2018 Sep 8;218(8):1261-1271
pubmed: 29917114
Elife. 2020 May 11;9:
pubmed: 32392129
Nat Rev Microbiol. 2017 Mar;15(3):183-192
pubmed: 28090077
J Infect Dis. 2015 Nov 15;212(10):1574-8
pubmed: 26153409
Virus Evol. 2020 Aug 19;6(2):veaa061
pubmed: 33235813
Emerg Infect Dis. 2018 Mar;24(3):492-497
pubmed: 29460729
Microb Genom. 2016 Nov 30;2(11):e000093
pubmed: 28348833
Nat Microbiol. 2020 Nov;5(11):1403-1407
pubmed: 32669681
JAMA. 2020 Mar 17;323(11):1061-1069
pubmed: 32031570
Mol Biol Evol. 2013 Apr;30(4):772-80
pubmed: 23329690
Nature. 2017 Apr 20;544(7650):309-315
pubmed: 28405027
Nat Protoc. 2017 Jun;12(6):1261-1276
pubmed: 28538739
Lancet Infect Dis. 2013 Feb;13(2):130-6
pubmed: 23158674
Sci Transl Med. 2017 Oct 25;9(413):
pubmed: 29070701
Nat Microbiol. 2019 Jan;4(1):10-19
pubmed: 30546099
N Engl J Med. 2012 Jun 14;366(24):2267-75
pubmed: 22693998
Mol Biol Evol. 2015 Jan;32(1):268-74
pubmed: 25371430
Nature. 2016 Feb 11;530(7589):228-232
pubmed: 26840485
Nature. 2017 Jun 15;546(7658):401-405
pubmed: 28538723
Nat Rev Genet. 2018 Jan;19(1):9-20
pubmed: 29129921