New research published in the Proceedings of the Royal Society B uses data from the Office for National Statistics COVID-19 Infection Survey (ONS-CIS) to explain how the COVID-19 pandemic unfolded in the UK during the first three years of the pandemic.
As well as telling the story of how different variants evolved and spread, the work will help governments and organisations design the best surveillance strategies for future respiratory pathogens.
The work was jointly carried out by Professor Katrina Lythgoe, Pandemic Sciences Institute, Investigator and researcher at the Big Data Institute/Nuffield Department of Medicine and Department of Biology and Dr Tanya Golubchik former BDI/NDM researcher. Other University of Oxford colleagues involved include Professor David Bonsall (NDM), Dr Matthew Hall (BDI/NDM), Professor Sarah Walker (NDM) and Professor Thomas House (University of Manchester).
The project was delivered in collaboration with the COVID-19 Genomics UK Consortium (COG-UK) and other partners.
As part of the group generating and analysing data for the Office for National Statistics COVID-19 Infection Survey, the researchers identified patterns of virus spread as well as variants that might pose a particular risk, feeding into government decision-making on a weekly basis.
Professor Lythgoe and colleagues have now reviewed these data to tell the story of the pandemic. Their work launches a new phase in how ONS-CIS data will be used.
How COVID-19 variants evolved and spread
The group analysed over 125,000 high quality SARS-CoV-2 sequences collected over the first three years of ONS-CIS. From these, they reconstructed how different variants of the SARS-CoV-2 virus emerged, spread and evolved as they swept through the UK population.
In their paper, they showed that each major lineage of virus that emerged could spread substantially faster than the other variants circulating at the time.
As each lineage spread, the virus gradually evolved and became more diverse, but each time a major new lineage emerged there was a step increase in how much the virus had evolved, compared to the original virus circulating in Wuhan, China. This distinctive pattern of sequence evolution happened again and again during the three-year period.
Lessons for future disease surveillance
The UK’s SARS-CoV-2 genomic sequencing effort was huge, with over 3 million sequences collected as part of COG-UK.
Professor Lythgoe and colleagues were able to reconstruct key information about how the virus spread through the UK population and how its sequence evolved using the only very small percentage of sequences obtained as part of the ONS-CIS.
Professor Katrina Lythgoe said: “We have shown in this study that we can reconstruct what happened during the COVID-19 pandemic with a fraction of the sampling we did in the UK.
“This demonstrates that we can start to think much more intelligently about how much sampling we need to do when designing surveillance studies for future disease outbreaks, both in the UK and in other countries.”
The ONS-CIS dataset will provide a springboard for future studies to help understand COVID-19 and other respiratory pathogens better. DPhil student Charu Sharma is embarking on this work in Professor Lythgoe’s lab at PSI, supported by a Moh Family Foundation Scholarship.
Read the full paper here.