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Large scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management
Andrew J Page; Alison E Mather; Thanh Le Viet; Emma J Meader; Nabil-Fareed J Alikhan; Gemma L Kay; Leonardo de Oliveira Martins; Alp Aydin; David J Baker; Alexander J. Trotter; Steven Rudder; Ana P Tedim; Anastasia Kolyva; Rachael Stanley; Maria Diaz; Will Potter; Claire Stuart; Lizzie Meadows; Andrew Bell; Ana Victoria Gutierrez; Nicholas M Thomson; Evelien M Adriaenssens; Tracey Swingler; Rachel AJ Gilroy; Luke Griffith; Dheeraj K Sethi; Dinesh Aggarwal; Colin S Brown; Rose K Davidson; Robert A Kingsley; Luke Bedford; Lindsay J Coupland; Ian G Charles; Ngozi Elumogo; John Wain; Reenesh Prakash; Mark A Webber; SJ Louise Smith; Meera Chand; Samir Dervisevic; Justin O'Grady; - The COVID-19 Genomics UK (COG-UK) consortium.
Affiliation
  • Andrew J Page; Quadram Institute Bioscience
  • Alison E Mather; Quadram Institute Bioscience
  • Thanh Le Viet; Quadram Institute Bioscience
  • Emma J Meader; Norfolk and Norwich University Hospital
  • Nabil-Fareed J Alikhan; Quadram Institute Bioscience
  • Gemma L Kay; Quadram Institute Bioscience
  • Leonardo de Oliveira Martins; Quadram Institute Bioscience
  • Alp Aydin; Quadram Institute Bioscience
  • David J Baker; Quadram Institute Bioscience
  • Alexander J. Trotter; Quadram Institute Bioscience
  • Steven Rudder; Quadram Institute Bioscience
  • Ana P Tedim; Quadram Institute Bioscience
  • Anastasia Kolyva; Norfolk and Norwich University Hospital
  • Rachael Stanley; Norfolk and Norwich University Hospital
  • Maria Diaz; Quadram Institute Bioscience
  • Will Potter; Norfolk and Norwich University Hospital
  • Claire Stuart; Norfolk and Norwich University Hospital
  • Lizzie Meadows; Quadram Institute Bioscience
  • Andrew Bell; Quadram Institute Bioscience
  • Ana Victoria Gutierrez; Quadram Institute Bioscience
  • Nicholas M Thomson; Quadram Institute Bioscience
  • Evelien M Adriaenssens; Quadram Institute Bioscience
  • Tracey Swingler; Quadram Institute Bioscience
  • Rachel AJ Gilroy; Quadram Institute Bioscience
  • Luke Griffith; University of East Anglia
  • Dheeraj K Sethi; Norfolk and Norwich University Hospital
  • Dinesh Aggarwal; Public Health England
  • Colin S Brown; Public Health England
  • Rose K Davidson; University of East Anglia
  • Robert A Kingsley; Quadram Institute Bioscience
  • Luke Bedford; Ipswich Hospital
  • Lindsay J Coupland; Norfolk and Norwich University Hospital
  • Ian G Charles; Quadrum Institute Bioscience
  • Ngozi Elumogo; Norfolk and Norwich University Hospital
  • John Wain; Quadram Institute Bioscience
  • Reenesh Prakash; Norfolk and Norwich University Hospital
  • Mark A Webber; Quadram Institute Bioscience
  • SJ Louise Smith; Norfolk County Council
  • Meera Chand; Public Health England
  • Samir Dervisevic; Norfolk and Norwich University Hospital
  • Justin O'Grady; Quadram Institute Bioscience
  • - The COVID-19 Genomics UK (COG-UK) consortium;
Preprint in English | medRxiv | ID: ppmedrxiv-20201475
ABSTRACT
The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3,200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organisations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1,565 positive samples (172 per 100,000 population) from 1,376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6% of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. 1,035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically-distinct UK lineages were detected demonstrating local evolution, at a rate of [~]2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our

analysis:

identified a sublineage associated with 6 care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients indicating infection control measures were effective; found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves. Major pointsIn Norfolk and surrounding regions O_LI100 distinct UK lineages were identified. C_LIO_LI16 UK lineages found in key workers were not observed in patients or in community care. C_LIO_LI172 genomes from SARS-CoV-2 positive samples sequenced per 100,000 population representing 42.6% of all positive cases. C_LIO_LISARS-CoV-2 genomes from 1035 cases sequenced to a high quality. C_LIO_LIOnly 5 countries, out of 103, have sequenced more SARS-CoV-2 genomes than have been sequenced in Norfolk for this paper. C_LIO_LISamples covered the entire first wave, March to August 2020. C_LIO_LIStable evolutionary rate of 2 SNPs per month. C_LIO_LID614G mutation is the dominant genotype and associated with increased transmission. C_LIO_LINo evidence of reinfection in 42 cases with longitudinal samples. C_LIO_LIWGS identified a sublineage associated with care facilities. C_LIO_LIWGS ruled out nosocomial outbreaks. C_LIO_LIRapid WGS confirmed the relatedness of cases from an outbreak at a food processing facility. C_LI
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
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