1887

Abstract

Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy and will be a high priority for public health for the foreseeable future. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained using a variety of methods all of which are known to contain biases. As a case study, using an approach which is largely free of biases, we here describe lineage dynamics and phylogenetic relationships of the Alpha and Beta variant in England during the first 3 months of 2021 using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the Alpha variant (first identified in Kent) becoming predominant, driven by a reproduction number 0.3 higher than for the prior wild-type. During January, positive samples were more likely to be Alpha in those aged 18 to 54 years old. Although individuals infected with the Alpha variant were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild-type, they were more likely to be antibody-positive 6 weeks after infection. Further, viral load was higher in those infected with the Alpha variant as measured by cycle threshold (Ct) values. The presence of infections with non-imported Beta variant (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing. These results highlight how sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance during periods of lineage diversity.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000887
2023-02-06
2024-05-14
Loading full text...

Full text loading...

/deliver/fulltext/mgen/9/2/mgen000887.html?itemId=/content/journal/mgen/10.1099/mgen.0.000887&mimeType=html&fmt=ahah

References

  1. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese center for disease control and prevention. JAMA 2020; 323:1239–1242 [View Article] [PubMed]
    [Google Scholar]
  2. Dimonte S, Babakir-Mina M, Hama-Soor T, Ali S. Genetic variation and evolution of the 2019 novel coronavirus. Public Health Genomics 2021; 24:54–66 [View Article] [PubMed]
    [Google Scholar]
  3. Zhao S, Lou J, Cao L, Zheng H, Chong MKC et al. Quantifying the transmission advantage associated with N501Y substitution of SARS-CoV-2 in the UK: an early data-driven analysis. J Travel Med 2021; 28:taab011 [View Article]
    [Google Scholar]
  4. Wang P, Nair MS, Liu L, Iketani S, Luo Y et al. Antibody resistance of SARS-CoV-2 variants B.1.351 and B.1.1.7. Nature 2021; 593:130–135 [View Article] [PubMed]
    [Google Scholar]
  5. van Dorp L, Acman M, Richard D, Shaw LP, Ford CE et al. Emergence of genomic diversity and recurrent mutations in SARS-CoV-2. Infect Genet Evol 2020; 83:104351 [View Article] [PubMed]
    [Google Scholar]
  6. Sabino EC, Buss LF, Carvalho MPS, Prete CA Jr, Crispim MAE et al. Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence. Lancet 2021; 397:452–455 [View Article] [PubMed]
    [Google Scholar]
  7. Tegally H, Wilkinson E, Giovanetti M, Iranzadeh A, Fonseca V et al. Detection of a SARS-CoV-2 variant of concern in South Africa. Nature 2021; 592:438–443 [View Article] [PubMed]
    [Google Scholar]
  8. Volz E, Mishra S, Chand M, Barrett JC, Johnson R et al. Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England. Nature 2021; 593:266–269 [View Article]
    [Google Scholar]
  9. Rambaut A, Holmes EC, O’Toole Á, Hill V, McCrone JT et al. A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat Microbiol 2020; 5:1403–1407 [View Article] [PubMed]
    [Google Scholar]
  10. Kraemer MUG, Hill V, Ruis C, Dellicour S, Bajaj S et al. Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence. Science 2021; 373:889–895 [View Article] [PubMed]
    [Google Scholar]
  11. Lineage B.1.1.7. [cited 21 Mar 2021]; 2021 https://cov-lineages.org/global_report_B.1.1.7.html
  12. Elliott P, Haw D, Wang H, Eales O, Walters CE et al. Exponential growth, high prevalence of SARS-CoV-2, and vaccine effectiveness associated with the Delta variant. Science 2021; 374:eabl9551 [View Article]
    [Google Scholar]
  13. Davies NG, Abbott S, Barnard RC, Jarvis CI, Kucharski AJ et al. Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England. Science 2021; 372:eabg3055 [View Article]
    [Google Scholar]
  14. Lineage B.1.351. [cited 21 Mar 2021]; 2021 https://cov-lineages.org/global_report_B.1.351.html
  15. Chen RE, Zhang X, Case JB, Winkler ES, Liu Y et al. Resistance of SARS-CoV-2 variants to neutralization by monoclonal and serum-derived polyclonal antibodies. Nat Med 2021; 27:717–726 [View Article] [PubMed]
    [Google Scholar]
  16. Public Health England PHE statement on variant of concern and new variant under investigation. In: GOV.UK [Internet]. 10 Feb 2021 [cited 5 Mar 2021]; 2021 https://www.gov.uk/government/news/phe-statement-on-variant-of-concern-and-new-variant-under-investigation
  17. Bugembe DL, Phan MVT, Ssewanyana I, Semanda P, Nansumba H et al. Emergence and spread of A SARS-CoV-2 lineage a variant (A.23.1) with altered spike protein in Uganda. Nat Microbiol 2021; 6:1094–1101 [View Article]
    [Google Scholar]
  18. Lineage A.23.1. [cited 21 Mar 2021]; 2021 https://cov-lineages.org/global_report_A.23.1.html
  19. Lineage B.1.525. [cited 21 Mar 2021]; 2021 https://cov-lineages.org/global_report_B.1.525.html
  20. COVID-19 Genomics UK (COG-UK) [email protected] An integrated national scale SARS-CoV-2 genomic surveillance network. Lancet Microbe 2020; 1:e99–e100 [View Article]
    [Google Scholar]
  21. COVID-19 Genomics UK Consortium Summary report: COG-UK geographic coverage of SARS-CoV-2 sample sequencing, week commencing 29 March 2021. COG-UK; 2021 Apr. Report No.: Report on the week commencing on 29 March 2021 (week 13); 2021 https://www.cogconsortium.uk/wp-content/uploads/2021/04/COG-UK-geo-coverage_2021-04-12_summary.pdf
  22. Cyranoski D. Alarming COVID variants show vital role of genomic surveillance. Nature 2021; 589:337–338 [View Article] [PubMed]
    [Google Scholar]
  23. Elbe S, Buckland-Merrett G. Data, disease and diplomacy: GISAID’s innovative contribution to global health. Glob Chall 2017; 1:33–46 [View Article]
    [Google Scholar]
  24. COVID-19 Genomics UK Consortium Summary report: COG-UKgeographic coverage of SARS-CoV-2 sample sequencing, week commencing 28December 2020. COG-UK; 2021 Jan. Report No.: Report on the week commencing on28 December 2020 (week 53); 2021 https://www.cogconsortium.uk/wp-content/uploads/2021/02/COG-UK-geo-coverage_2021-01-18_summary.pdf
  25. Riley S, Atchison C, Ashby D, Donnelly CA, Barclay W et al. REal-time Assessment of Community Transmission (REACT) of SARS-CoV-2 virus: Study protocol. Wellcome Open Res 2020; 5:200 [View Article] [PubMed]
    [Google Scholar]
  26. Quick J. nCoV-2019 sequencing protocol v3 (LoCost). 2020 [cited 4 May 2021]; 2020 https://www.protocols.io/view/ncov-2019-sequencing-protocol-v3-locost-bh42j8ye
  27. Baker DJ, Aydin A, Le-Viet T, Kay GL, Rudder S et al. CoronaHiT: high-throughput sequencing of SARS-CoV-2 genomes. Genome Med 2021; 13:21 [View Article] [PubMed]
    [Google Scholar]
  28. A Nextflow pipeline for running the ARTIC network’s field bioinformatics tools. Github. n.d https://github.com/connor-lab/ncov2019-artic-nf
  29. Connor TR, Loman NJ, Thompson S, Smith A, Southgate J et al. CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community. Microb Genom 2016; 2:e000086 [View Article]
    [Google Scholar]
  30. Phylogenetic Assignmentof Named Global Outbreak LINeages (PANGOLIN). Github. n.d https://github.com/cov-lineages/pangolin
  31. Standardised Variant Definitions: A repository containing the up-to-date lineage definitions for variants of concern (VOC) and variants of interest (VUI) as curated by Public Health England. Github. n.d https://github.com/phe-genomics/variant_definitions
  32. Cluster Investigation& Virus Epidemiology Tool (CIVET). Github. n.d https://github.com/COG-UK/civet
  33. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 2015; 32:268–274 [View Article] [PubMed]
    [Google Scholar]
  34. Wilson EB. Probable inference, the law of succession, and statistical inference. J Am Stat Assoc 1927; 22:209–212 [View Article]
    [Google Scholar]
  35. Brown LD, Cai TT, DasGupta A. Interval estimation for a binomial proportion. SSO Schweiz Monatsschr Zahnheilkd 2001; 16:101–133 [View Article]
    [Google Scholar]
  36. XNomial: Exact Goodness-of-Fit Test for Multinomial Data with Fixed Probabilities. [cited 21 Mar 2021]; 2021 https://cran.r-project.org/web/packages/XNomial/index.html
  37. Park N. Population estimates for the UK, England and Wales, Scotland and Northern Ireland - Office for National Statistics. Office for National Statistics; 23 Jun 2020 [cited 6 Mar 2021]; 2020 https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/annualmidyearpopulationestimates/latest
  38. Wallinga J, Lipsitch M. How generation intervals shape the relationship between growth rates and reproductive numbers. Proc Biol Sci 2007; 274:599–604 [View Article] [PubMed]
    [Google Scholar]
  39. Bi Q, Wu Y, Mei S, Ye C, Zou X et al. Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts. MedRxiv; 2020 https://www.medrxiv.org/content/medrxiv/early/2020/03/19/2020.03.03.20028423.full.pdf
  40. Anderson SC, Ward EJ. Black swans in space: modeling spatiotemporal processes with extremes. Ecology 2019; 100:e02403 [View Article] [PubMed]
    [Google Scholar]
  41. Moshe M, Daunt A, Flower B, Simmons B, Brown JC et al. SARS-CoV-2 lateral flow assays for possible use in national covid-19 seroprevalence surveys (React 2): diagnostic accuracy study. BMJ 2021; 372:423 [View Article]
    [Google Scholar]
  42. Eales O, Walters CE, Wang H, Haw D, Ainslie KEC et al. Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2. Wellcome Open Res 2022; 7:102 [View Article]
    [Google Scholar]
  43. Yelin I, Aharony N, Tamar ES, Argoetti A, Messer E et al. Evaluation of COVID-19 RT-qPCR test in multi sample pools. Clin Infect Dis 2020; 71:2073–2078 [View Article]
    [Google Scholar]
  44. COG-UK Mutation Explorer. [cited 24 Mar 2021]; 2021 http://sars2.cvr.gla.ac.uk/cog-uk/
  45. Elie B, Roquebert B, Sofonea MT, Trombert-Paolantoni S, Foulongne V et al. Variant-specific SARS-CoV-2 within-host kinetics. J Med Virol 2022; 94:3625–3633 [View Article]
    [Google Scholar]
  46. Hay JA, Kennedy-Shaffer L, Kanjilal S, Lennon NJ, Gabriel SB et al. Estimating epidemiologic dynamics from cross-sectional viral load distributions. Science 2021; 373:eabh0635 [View Article]
    [Google Scholar]
  47. Michalakis Y, Sofonea MT, Alizon S, Bravo IG. SARS-CoV-2 viral RNA levels are not “viral load.”. Trends Microbiol 2021; 29:970–972 [View Article] [PubMed]
    [Google Scholar]
  48. Department for Education New guidance for schools, colleges and early years. In: GOV.UK [Internet]. 4 Nov 2020 [cited 24 Apr 2021]; 2020 https://www.gov.uk/government/news/new-guidance-for-schools-colleges-and-early-years
  49. Davies NG, Jarvis CI. CMMID COVID-19 Working Group Edmunds WJ, Jewell NP et al. Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7. Nature 2021; 593:270–274 [View Article] [PubMed]
    [Google Scholar]
  50. Challen R, Brooks-Pollock E, Read JM, Dyson L, Tsaneva-Atanasova K et al. Risk of mortality in patients infected with SARS-CoV-2 variant of concern 202012/1: matched cohort study. BMJ 2021; 372:579 [View Article]
    [Google Scholar]
  51. Graham MS, Sudre CH, May A, Antonelli M, Murray B et al. Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study. Lancet Public Health 2021; 6:e335–e345 [View Article] [PubMed]
    [Google Scholar]
  52. Campbell F, Archer B, Laurenson-Schafer H, Jinnai Y, Konings F et al. Increased transmissibility and global spread of SARS-CoV-2 variants of concern as at June 2021. Euro Surveill 2021; 26:2100509 [View Article]
    [Google Scholar]
  53. Surge testing for new coronavirus (COVID-19) variants. [cited 5 Mar 2021]; 2021 https://www.gov.uk/guidance/surge-testing-for-new-coronavirus-covid-19-variants
  54. Roquebert B, Trombert-Paolantoni S, Haim-Boukobza S, Lecorche E, Verdurme L et al. The SARS-CoV-2 B.1.351 lineage (VOC β) is outgrowing the B.1.1.7 lineage (VOC α) in some French regions in April 2021. Euro Surveill 2021; 26:2100447 [View Article]
    [Google Scholar]
  55. Jiang CQ, Lessler J, Kim L, Kwok KO, Read JM et al. Cohort profile: a study of influenza immunity in the urban and rural Guangzhou region of China: the Fluscape Study. Int J Epidemiol 2017; 46:e16 [View Article] [PubMed]
    [Google Scholar]
  56. Elliott P, Bodinier B, Eales O, Wang H, Haw D et al. Rapid increase in Omicron infections in England during December 2021: REACT-1 study. Science 2022; 375:1406–1411 [View Article]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000887
Loading
/content/journal/mgen/10.1099/mgen.0.000887
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL

Supplementary material 3

EXCEL

Supplementary material 4

EXCEL
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error