The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Transmission of SARS-CoV-2 Lineage B.1.1.7 in England: Insights from linking epidemiological and genetic data
Open accessPreprint — published as 10.1038/s41586-021-03470-x · Paper page
Abstract
The SARS-CoV-2 lineage B.1.1.7, now designated Variant of Concern 202012/01 (VOC) by Public Health England, originated in the UK in late Summer to early Autumn 2020. We examine epidemiological evidence for this VOC having a transmission advantage from several perspectives. First, whole genome sequence data collected from community-based diagnostic testing provides an indication of changing prevalence of different genetic variants through time. Phylodynamic modelling additionally indicates that genetic diversity of this lineage has changed in a manner consistent with exponential growth. Second, we find that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S-gene target failures (SGTF) in community-based diagnostic PCR testing. Third, we examine growth trends in SGTF and non-SGTF case numbers at local area level across England, and show that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. Available SGTF data indicate a shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Fourth, we assess the association of VOC frequency with independent estimates of the overall SARS-CoV-2 reproduction number through time. Finally, we fit a semi-mechanistic model directly to local VOC and non-VOC case incidence to estimate the reproduction numbers over time for each. There is a consensus among all analyses that the VOC has a substantial transmission advantage, with the estimated difference in reproduction numbers between VOC and non-VOC ranging between 0.4 and 0.7, and the ratio of reproduction numbers varying between 1.4 and 1.8. We note that these estimates of transmission advantage apply to a period where high levels of social distancing were in place in England; extrapolation to other transmission contexts therefore requires caution.
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“In particular, the mild restrictions that kept around 0.9 with the original virus strain would keep it around 1.3 (at least) if the new variants increase transmissibility of at least 40–50%, as reported in the literature49–51.”
From Modeling vaccination rollouts, SARS-CoV-2 variants and the requirement for non-pharmaceutical interventions in Italy (2021) · cites this paper as [49]
Experimental — accuracy not yet measuredIn the citing paper
“Recently, viral variants of concern have emerged in the UK (B.1.1.7), South Africa (B.1.351), and Brazil (P.1) that harbor specific mutations in their S proteins that may be associated with increased transmissibility (50–55).”
From mRNA vaccination boosts cross-variant neutralizing antibodies elicited by SARS-CoV-2 infection (2021) · cites this paper as [51]
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“SARS-CoV-2 and SARS-CoV enter host cells through binding of the S glycoprotein to angiotensin converting enzyme 2 (ACE2)1,28.”
From Sensitivity of SARS-CoV-2 B.1.1.7 to mRNA vaccine-elicited antibodies (2021) · cites this paper as [1]
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“and has been reported to increase transmissibility of the B.1.17 variant circulating in the UK.16”
From Efficacy of NVX-CoV2373 Covid-19 Vaccine against the B.1.351 Variant (2021) · cites this paper as [16]
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Citations
Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era
Minh, B. Q., Schmidt, H. A., Chernomor, O., Schrempf, D., Woodhams, M. D., von Haeseler, A., & Lanfear, R. (2020) · Molecular Biology and Evolution · doi:10.1093/molbev/msaa015 · Cited by 16,873
Hastie, T., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013604 · Cited by 12,575
Posterior summarization in Bayesian phylogenetics using tracer 1.7
Rambaut, A., Drummond, A. J., Xie, D., Baele, G., & Suchard, M. A. (2018) · Systematic Biology · doi:10.1093/sysbio/syy032 · Cited by 11,159
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Bürkner, P.-C. (2017) · Journal of Statistical Software · doi:10.18637/jss.v080.i01 · Cited by 9,476
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10
Suchard, M. A., Lemey, P., Baele, G., Ayres, D. L., Drummond, A. J., & Rambaut, A. (2018) · Virus Evolution · doi:10.1093/ve/vey016 · Cited by 3,749
Self-citationEstimating the effects of non-pharmaceutical interventions on COVID-19 in Europe
Flaxman, S. R., Mishra, S., Gandy, A., Unwin, H. J. T., Mellan, T. A., Coupland, H., Whittaker, C., Zhu, H., Berah, T., Eaton, J. W., et al. (2020) · Nature · doi:10.1038/s41586-020-2405-7 · Cited by 3,398
Self-citationHastie, T. J., & Tibshirani, R. J. (2014) · Wiley StatsRef: Statistics Reference Online · doi:10.1002/9781118445112.stat03141 · Cited by 3,156
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2020) · doi:10.1101/2020.12.24.20248822 · Cited by 2,557
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Self-citationDetection of a SARS-CoV-2 variant of concern in South Africa
Tegally, H., Wilkinson, E., Giovanetti, M., Iranzadeh, A., Fonseca, V., Giandhari, J., Doolabh, D., Pillay, S., San, E. J., Msomi, N., et al. (2021) · Nature · doi:10.1038/s41586-021-03402-9 · Cited by 2,510
Efficacy of the ChAdOx1 nCoV-19 Covid-19 Vaccine against the B.1.351 Variant
Madhi, S. A., Baillie, V., Cutland, C. L., Voysey, M., Koen, A. L., Fairlie, L., Padayachee, S. D., Dheda, K., Barnabas, S. L., Bhorat, Q. E., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2102214 · Cited by 1,257
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“Lastly, variants in the UK and USA, albeit with fewer potential antibody escape mutations have also been described, suggesting the global emergence of new SARS-CoV-2 variants 26 .”
Fiolet, T., Kherabi, Y., MacDonald, C.-J., Ghosn, J., & Peiffer-Smadja, N. (2022) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2021.10.005 · Cited by 911
Metadata
- Authors
- Volz, E., Mishra, S., Chand, M., Barrett, J. C., Johnson, R., Geidelberg, L., Hinsley, W. R., Laydon, D. J., Dabrera, G., O’Toole, Á., Amato, R., Ragonnet-Cronin, M., Harrison, I., Jackson, B., Ariani, C. V., Boyd, O., Loman, N. J., McCrone, J. T., Gonçalves, S., Jorgensen, D., Myers, R., Hill, V., Jackson, D. K., Gaythorpe, K., Groves, N., Sillitoe, J., Kwiatkowski, D. P., The COVID-19 Genomics UK (COG-UK) consortium, Flaxman, S., Ratmann, O., Bhatt, S., Hopkins, S., Gandy, A., Rambaut, A., & Ferguson, N. M.
- Affiliations
- Imperial College London (GB)
- Public Health England (GB)
- Wellcome Sanger Institute (GB)
- University of Edinburgh (GB)
- University of Copenhagen (DK)
- Corresponding author
- Volz, Erik
- Ferguson, Neil M
- ORCID
- Volz, Erik
- Mishra, Swapnil
- Chand, Meera
- Barrett, Jeffrey C.
- Geidelberg, Lily
- Hinsley, Wes R
- Laydon, Daniel J
- Dabrera, Gavin
- Harrison, Ian
- Jackson, Ben
- Ariani, Cristina V.
- Boyd, Olivia
- Loman, Nicholas J
- McCrone, John T
- Gonçalves, Sónia
- Jorgensen, David
- Myers, Richard
- Hill, Verity
- Jackson, David K.
- Gaythorpe, Katy
- Groves, Natalie
- Kwiatkowski, Dominic P.
- Flaxman, Seth
- Ratmann, Oliver
- Bhatt, Samir
- Hopkins, Susan
- Gandy, Axel
- Rambaut, Andrew
- Ferguson, Neil M
- Venue
- Nature
- Publisher
- openRxiv
- Published
- 2021-01-04
- Volume
- 593
- Issue
- 7858
- Pages
- 266-269
- ISSN
- 0028-0836 (ISSN-L)
- OpenAlex
- W3136588845
- Cited by
- 1,611
- References
- 28
- Citations by year
- 2026: 38 · 2025: 86 · 2024: 116 · 2023: 216 · 2022: 464 · 2021: 685
- FWCI
- 116.92
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- medRxiv (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Figshare (submittedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- Northumbria Research Link (Northumbria University) (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion, other-oa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Spiral (Imperial College London) (submittedVersion, cc-by)
- Spiral (Imperial College London) (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- Bill and Melinda Gates Foundation (OPP 1175094, 206194, OPP1197730, MR/R015600/1, OPP1084362)
- Wellcome Trust (MR/R015600/1, 204911/Z/16/Z, Z/17/Z, 206298/Z/17/Z, RDA02, 206298, 206194)
- UK Research and Innovation (MR/V038109/1, MR/R015600/1, MC_PC_19027)
- National Institute for Health Research Health Protection Research Unit
- Cancer Research UK (23923)
- National Institute for Health and Care Research (PR-OD-1017–20002, MR/R015600/1, RDA02, NIHR301445, OPP1175094, ACF-2018-04-014)
- Academy of Medical Sciences (AMS-CSF4-Torok, SBF004\1080)
- Imperial College London (MR/R015600/1)
- European Commission (725422, MR/R015600/1, 101003653, COVID-19, 206298/Z/17/Z)
- Rural Development Administration
- Novo Nordisk (NNF20OC0059309)
- Novo Nordisk Fonden (NNF20OC0059309)
- Medical Research Council (MR/R015600/1, MR/M006212/1, MC_PC_19026, MR/V038109/1, MR/S00291X/1, MC_PC_19012, COVID-19)
- Engineering and Physical Sciences Research Council (EP/V002910/1, EP/V002910/2)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
- Keywords
- SARS-CoV-2, B.1.1.7 lineage, variants of concern, transmissibility, S-gene target failure, time-varying reproduction number, viral genomic surveillance, COVID-19 pandemic, England
- MeSH terms
- COVID-19, SARS-CoV-2, Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, England, Humans, Infant, Infant, Newborn, Middle Aged, Phylogeny, Time Factors, Genome, Viral, Age Distribution, Evolution, Molecular, Basic Reproduction Number, Young Adult, Spike Glycoprotein, Coronavirus
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