Back to Search
Start Over
SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2
- Source :
- 1471-233, BMC infectious diseases
- Publication Year :
- 2022
- Publisher :
- BioMed Central, 2022.
-
Abstract
- Background Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.
- Subjects :
- Delta variant
Science & Technology
SARS-CoV-2
COVID-19
1103 Clinical Sciences
C500
Microbiology
Genetic diversity
B900
Infectious Diseases
England
COVID-19 Genomics UK (COG-UK) Consortium
1108 Medical Microbiology
Mutation
Humans
Transmission advantage
Life Sciences & Biomedicine
Phylogeny
0605 Microbiology
Subjects
Details
- ISSN :
- 14712334
- Database :
- OpenAIRE
- Journal :
- 1471-233, BMC infectious diseases
- Accession number :
- edsair.doi.dedup.....30139e4e840bd988c0b91755bedc8f1d