Genomic Epidemiology of SARS-CoV-2 in Norfolk, UK, March 2020 – December 2022
Authors: Hayles Eleanor H. , Page Andrew J. , Kingsley Robert A. , Guitian Javier ,   The COVID-19 Genomics UK Consortium, Langridge Gemma C. 
Published: September 2024

AbstractBackgroundIn the UK, the COVID-19 Genomics UK Consortium (COG-UK) established a real time national genomic surveillance system during the COVID-19 pandemic, producing centralised data for monitoring SARS-CoV-2. As a COG-UK partner, Quadram Institute Bioscience (QIB) in Norfolk sequenced over 87,000 SARS-CoV-2 genomes, 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.Methods29,406 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, and subsequent lineage analysis carried out in R using RStudio and related packages, including graphical analysis using ggplot2.Results401 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 (VOC) accounted for 8.6%, 34.9% and 48.5% of sequences respectively. These formed four regional epidemic waves alongside the remaining lineages which appeared 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.ConclusionThis 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 – 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.Data summaryThe COG-UK collection of SARS-CoV-2 sequences and metadata are available for public download on their archive website under the ‘Latest sequence data’ heading <https://webarchive.nationalarchives.gov.uk/ukgwa/20230507102210/https://www.cogconsortium.uk/priority-areas/data-linkage-analysis/public-data-analysis/>. Sequence names for all sequences used from this dataset alongside GISAID accession numbers where present are available inSupplementary Table 1.Impact statementWe extracted 29,406 regional Norfolk based SARS-CoV-2 sequences from the COG-UK SARS-CoV-2 dataset and revealed significant regional diversity and dynamic emergence of variant of concern (VOC) epidemic waves – spanning Alpha, Delta and Omicron lineages. We also applied statistical modelling to complement genomic methodology, with temporal clustering of significant first lineage emergences chronologically matching VOC waves and subwaves. The study highlights the importance of integration of genomic epidemiology into public health strategies for pandemic response, and the utility of using this data for retrospective research.