About: Rapid implementation of real-time SARS-CoV-2 sequencing to investigate healthcare-associated COVID-19 infections

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Rapid implementation of real-time SARS-CoV-2 sequencing to investigate healthcare-associated COVID-19 infections Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Rapid implementation of real-time SARS-CoV-2 sequencing to investigate healthcare-associated COVID-19 infections
Creator	Goodfellow, Ian Parmar, Surendra Hosmillo, Myra Baker, Stephen Dougan, Gordon Caddy, Sarah Yakovleva, Anna Curran, Martin Hall, Grant Peacock, Sharon Weekes, Michael Houldcroft, Charlotte Meredith, Luke Brown, Nicholas Caller, Laura Estée Török #$, M Feltwell, Theresa Forrest, Sally Gouliouris, Theodore Hamilton, William Jahun, Aminu Khokhar, Fahad Moore, Elinor Popay, Ashley Reacher, Mark Roddick, Iain Sridhar, Sushmita Warne, Ben
source	MedRxiv
abstract	Background The burden and impact of healthcare-associated COVID-19 infections is unknown. We aimed to examine the utility of rapid sequencing of SARS-CoV-2 combined with detailed epidemiological analysis to investigate healthcare-associated COVID-19 infections and to inform infection control measures. Methods We set up rapid viral sequencing of SARS-CoV-2 from PCR-positive diagnostic samples using nanopore sequencing, enabling sample-to-sequence in less than 24 hours. We established a rapid review and reporting system with integration of genomic and epidemiological data to investigate suspected cases of healthcare-associated COVID-19. Results Between 13 March and 24 April 2020 we collected clinical data and samples from 5191 COVID-19 patients in the East of England. We sequenced 1000 samples, producing 747 complete viral genomes. We conducted combined epidemiological and genomic analysis of 299 patients at our hospital and identified 26 genomic clusters involving 114 patients. 66 cases (57.9%) had a strong epidemiological link and 15 cases (13.2%) had a plausible epidemiological link. These results were fed back clinical, infection control and hospital management teams, resulting in infection control interventions and informing patient safety reporting. Conclusions We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and demonstrated the benefit of combined genomic and epidemiological analysis for the investigation of healthcare-associated COVID-19 infections. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection control interventions to reduce further healthcare-associated infections.
has issue date	2020-05-14(xsd:dateTime)
bibo:doi	10.1101/2020.05.08.20095687
has license	medrxiv
sha1sum (hex)	4d36064ba1c0826232da3009195d60bc87a17130
schema:url	https://doi.org/10.1101/2020.05.08.20095687
resource representing a document's title	Rapid implementation of real-time SARS-CoV-2 sequencing to investigate healthcare-associated COVID-19 infections
resource representing a document's body	covid:4d36064ba1c0826232da3009195d60bc87a17130#body_text
is schema:about of	named entity 'impact' named entity 'utility' named entity 'infections' named entity 'SARS-CoV-2' named entity 'healthcare-associated' named entity 'infections' named entity 'infection control' named entity 'healthcare-associated' named entity 'epidemiological analysis' named entity 'SARS-CoV-2' named entity 'medRxiv' named entity 'internal control' named entity 'healthcare providers' named entity 'infection control' named entity 'healthcare workers' named entity 'genome' named entity 'community-acquired' named entity 'Healthcare worker' named entity 'SARS-CoV-2' named entity 'paramedics' named entity 'China' named entity 'mutation rate' named entity 'RNA' named entity 'Genomic analysis' named entity 'care home' named entity 'PPE' named entity 'COVID19' named entity 'MS2 bacteriophage' named entity 'COVID' named entity 'infection control' named entity 'HCAI' named entity 'clinical data' named entity 'outpatient' named entity 'base pairs' named entity 'SNP' named entity 'SNP' named entity 'hospital-acquired infections' named entity 'healthcare-associated infections' named entity 'care home' named entity 'infection control' named entity 'care homes' named entity 'COVID' named entity 'CUH' named entity 'virus' named entity 'de-duplication' named entity 'genomes sequenced' named entity 'epidemiological' named entity 'epidemiological data' named entity 'viral genomes' named entity 'Colindale' named entity 'SNPs' named entity 'Phylogenetic trees' named entity 'CUH' named entity 'Verona' named entity 'SNPs' named entity 'peer review' named entity 'CUH' named entity 'patient isolation'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software