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Supplementary Information from Lineage replacement and evolution captured by 3 years of the United Kingdom COVID infection survey

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posted on 2023-09-15, 14:51 authored by Katrina Lythgoe, Tanya Golubchik, Matthew Hall, Thomas House, Roberto Cahuantzi, George MacIntyre-Cockett, Helen Fryer, Laura Thomson, Anel Nurtay, Mahan Ghafani, David Buck, Angie Green, Amy Trebes, Paolo Piazza, Lorne J Lonie, Ruth Studley, Emma Rourke, Darren Smith, Matthew Bashton, Andrew Nelson, Matthew Crown, Clare McCann, Gregory R. Young, Rui Andre Nunes dos Santos, Zack Richards, Adnan Tariq, Christophe Fraser, Ian Diamond, Jeff Barrett, Ann Sarah Walker, David Bonsall
The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.


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    Proceedings of the Royal Society B: Biological Sciences