Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study

Luke W Meredith; William L Hamilton; Ben Warne; Charlotte J Houldcroft; Myra Hosmillo; Aminu S Jahun; Martin D Curran; Surendra Parmar; Laura G Caller; Sarah L Caddy; Fahad A Khokhar; Anna Yakovleva; Grant Hall; Theresa Feltwell; Sally Forrest; Sushmita Sridhar; Michael P Weekes; Stephen Baker; Nicholas Brown; Elinor Moore; Ashley Popay; Iain Roddick; Mark Reacher; Theodore Gouliouris; Sharon J Peacock; Gordon Dougan; M Estée Török; Ian Goodfellow

doi:10.1016/S1473-3099(20)30562-4

Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study

Lancet Infect Dis. 2020 Nov;20(11):1263-1272. doi: 10.1016/S1473-3099(20)30562-4. Epub 2020 Jul 14.

Authors

Luke W Meredith¹, William L Hamilton², Ben Warne², Charlotte J Houldcroft³, Myra Hosmillo¹, Aminu S Jahun¹, Martin D Curran⁴, Surendra Parmar⁴, Laura G Caller⁵, Sarah L Caddy⁶, Fahad A Khokhar⁶, Anna Yakovleva¹, Grant Hall¹, Theresa Feltwell³, Sally Forrest⁶, Sushmita Sridhar⁷, Michael P Weekes⁶, Stephen Baker⁶, Nicholas Brown⁴, Elinor Moore⁸, Ashley Popay⁹, Iain Roddick⁹, Mark Reacher⁹, Theodore Gouliouris¹⁰, Sharon J Peacock¹¹, Gordon Dougan⁶, M Estée Török¹², Ian Goodfellow¹³

Affiliations

¹ Department of Pathology, University of Cambridge, Cambridge, UK.
² Department of Medicine, University of Cambridge, Cambridge, UK; Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, UK.
³ Department of Medicine, University of Cambridge, Cambridge, UK.
⁴ Public Health England Clinical Microbiology and Public Health Laboratory, Cambridge, UK.
⁵ Department of Pathology, University of Cambridge, Cambridge, UK; Francis Crick Institute, London, UK.
⁶ Department of Medicine, University of Cambridge, Cambridge, UK; Cambridge Institute for Therapeutic Immunology and Infectious Disease, Cambridge, UK.
⁷ Department of Medicine, University of Cambridge, Cambridge, UK; Cambridge Institute for Therapeutic Immunology and Infectious Disease, Cambridge, UK; Wellcome Sanger Institute, Hinxton, UK.
⁸ Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, UK.
⁹ Field Epidemiology, Field Service, National Infection Service, Public Health England, Cambridge, UK.
¹⁰ Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, UK; Public Health England Clinical Microbiology and Public Health Laboratory, Cambridge, UK.
¹¹ Department of Medicine, University of Cambridge, Cambridge, UK; National Infection Service, Public Health England, London, UK.
¹² Department of Medicine, University of Cambridge, Cambridge, UK; Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, UK. Electronic address: et317@cam.ac.uk.
¹³ Department of Pathology, University of Cambridge, Cambridge, UK. Electronic address: ig299@cam.ac.uk.

Abstract

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adolescent
Adult
Aged
Aged, 80 and over
Betacoronavirus / genetics*
COVID-19
Child
Child, Preschool
Coronavirus Infections / epidemiology*
Coronavirus Infections / prevention & control*
Coronavirus Infections / virology
Cross Infection / epidemiology*
Cross Infection / prevention & control*
Cross Infection / virology
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*
Pneumonia, Viral / prevention & control*
Pneumonia, Viral / virology
Polymerase Chain Reaction / methods
Polymorphism, Single Nucleotide
Prospective Studies
SARS-CoV-2
Whole Genome Sequencing / methods
Young Adult

Abstract

Publication types

MeSH terms

Grants and funding