Genomic epidemiology of SARS-CoV-2 in Norfolk, UK, March 2020–December 2022

Eleanor Hayles, Andrew Page, Robert Kingsley, Javier Guitian, Gemma Langridge

Research output: Contribution to journalArticlepeer-review

Abstract

In the UK, the COVID-19 Genomics UK Consortium (COG-UK) established a real-time national genomic surveillance system during the COVID-19 pandemic, producing centralized data for monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As a COG-UK partner, Quadram Institute Bioscience in Norfolk sequenced over 87,000 SARS-CoV-2 genomes as part of the national effort, contributing to the region becoming densely sequenced. Retrospective analysis of SARS-CoV-2 lineage dynamics in this region may contribute to preparedness for future pandemics. In total, 29,406 SARS-CoV-2 whole genome sequences and corresponding metadata from Norfolk were extracted from the COG-UK dataset, sampled between March 2020 and December 2022, representing 9.9% of regional COVID-19 cases. Sequences were lineage typed using Pangolin, with subsequent lineage analysis carried out in R using RStudio and related packages, including graphical analysis using ggplot2. In total, 401 global lineages were identified, with 69.8% appearing more than once and 31.2% over ten times. Temporal clustering identified six lineage communities based on first lineage emergence. Alpha, Delta and Omicron variants of concern (VOCs) accounted for 8.6, 34.9 and 48.5% of sequences, respectively. These formed four regional epidemic waves alongside the remaining lineages which were observed in the early pandemic prior to VOC designation and were termed ‘pre-VOC’ lineages. Regional comparison highlighted variability in VOC epidemic wave dates dependent on location. This study is the first to assess SARS-CoV-2 diversity in Norfolk across a large timescale within the COVID-19 pandemic. SARS-CoV-2 was both highly diverse and dynamic throughout the Norfolk region between March 2020 and December 2022, with a strong VOC presence within the latter two-thirds of the study period. The study also displays the utility of incorporating genomic epidemiological methods into pandemic response.
Original languageEnglish
Article number001435
JournalMicrobial Genomics
Volume11
Issue number7
DOIs
Publication statusPublished - 15 Jul 2025

Keywords

  • COVID-19 Genomics UK Consortium (COG-UK)
  • genomic epidemiology
  • Norfolk
  • severe acute respiratory syndrome coronavirus 2
  • SARS-CoV-2
  • variant of concern
  • COVID-19

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