CoChat
Sign Up
PreprintCited by 2,557COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 ResearchMathematical and Theoretical Epidemiology and Ecology Models

The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.

Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England

Open access
Davies, Nicholas G., Abbott, Sam, Barnard, Rosanna C., Jarvis, Christopher I., Kucharski, Adam J., Munday, James D., Pearson, Carl A. B., Russell, Timothy W., Tully, Damien C., Washburne, Alex D., Wenseleers, Tom, Gimma, Amy, Waites, William, Wong, Kerry L. M., van Zandvoort, Kevin, Silverman, Justin D., CMMID COVID-19 Working Group, The COVID-19 Genomics UK (COG-UK) Consortium, Diaz-Ordaz, Karla, Keogh, Ruth, Eggo, Rosalind M., Funk, Sebastian, Jit, Mark, Atkins, Katherine E., Edmunds, W. John·2020·Science
DOI 10.1101/2020.12.24.20248822PMC PMC8128288

Preprint — published as 10.1126/science.abg3055 · Paper page

Open this paper in CoChat — free accountOpen PDF

Abstract

A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in November 2020 and is rapidly spreading towards fixation. Using a variety of statistical and dynamic modelling approaches, we estimate that this variant has a 43–90% (range of 95% credible intervals 38–130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine roll-out, COVID-19 hospitalisations and deaths across England in 2021 will exceed those in 2020. Concerningly, VOC 202012/01 has spread globally and exhibits a similar transmission increase (59–74%) in Denmark, Switzerland, and the United States.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/2020.12.24.20248822

Cites

69 of 69 references verified0 citation errors · 0 not checkable

Statistics

Figures

Impact of SARS-CoV-2 Variant of Concern 202012/01. (A) Spread of VOC 202012/01 (lineage B.1.1.7) in England. (B) The estimated relative transmissibility of VOC 202012/01 (mean and 95% confidence interval) is similar across the United Kingdom as a whole, England, Denmark, Switzerland, and the United States. (C) Projected COVID-19 deaths (median and 95% confidence interval) in England, 15 December 2020 to 30 June 2021. Vaccine rollout and control measures help to mitigate the burden of VOC 202012/01.
Impact of SARS-CoV-2 Variant of Concern 202012/01. (A) Spread of VOC 202012/01 (lineage B.1.1.7) in England. (B) The estimated relative transmissibility of VOC 202012/01 (mean and 95% confidence interval) is similar across the United Kingdom as a whole, England, Denmark, Switzerland, and the United States. (C) Projected COVID-19 deaths (median and 95% confidence interval) in England, 15 December 2020 to 30 June 2021. Vaccine rollout and control measures help to mitigate the burden of VOC 202012/01.CC BY · PubMed Central
Fig. 1 Rapid spread of VOC 202012/01 in England. (A) Proportion of S gene target failure among positive Pillar 2 community SARS-CoV-2 tests in upper-tier local authorities of England from 1 October 2020 to 10 January 2021, sorted by latitude. (B) Spread of S gene target failure by age, index of multiple deprivation decile (1 = most deprived), and sex within Greater London. (C and D) Estimates of R0 from CoMix social contact survey (12) compared to Rt estimates from REACT-1 prevalence survey (9) for England, with 90% CIs. Rt estimates based on single and aggregated REACT-1 survey rounds are shown. Horizontal error bars in (C) show the date range over which Rt was measured. (E and F) Percentage change (95% CI) in Google Mobility indices relative to baseline over time (E) and setting-specific mean contacts (95% CI) from the CoMix study (12) over time and by age for Tier 4 local authorities compared to the rest of England (F). Tier 4 local authorities are areas within the South East, East of England, and London regions that were placed under stringent restrictions from 20 December 2020 because of high prevalence of VOC 202012/01 and growing case rates. Gray shaded areas show the second national lockdown in England.
Fig. 1 Rapid spread of VOC 202012/01 in England. (A) Proportion of S gene target failure among positive Pillar 2 community SARS-CoV-2 tests in upper-tier local authorities of England from 1 October 2020 to 10 January 2021, sorted by latitude. (B) Spread of S gene target failure by age, index of multiple deprivation decile (1 = most deprived), and sex within Greater London. (C and D) Estimates of R0 from CoMix social contact survey (12) compared to Rt estimates from REACT-1 prevalence survey (9) for England, with 90% CIs. Rt estimates based on single and aggregated REACT-1 survey rounds are shown. Horizontal error bars in (C) show the date range over which Rt was measured. (E and F) Percentage change (95% CI) in Google Mobility indices relative to baseline over time (E) and setting-specific mean contacts (95% CI) from the CoMix study (12) over time and by age for Tier 4 local authorities compared to the rest of England (F). Tier 4 local authorities are areas within the South East, East of England, and London regions that were placed under stringent restrictions from 20 December 2020 because of high prevalence of VOC 202012/01 and growing case rates. Gray shaded areas show the second national lockdown in England.CC BY · PubMed Central
Fig. 2 Measuring the growth rate of VOC 202012/01. (A) Average relativized growth rate (i.e., a measure of variant fitness relative to other variants present during the 31 days after initial phylogenetic observation of a given variant) for all lineages in the COG-UK dataset, highlighting many lineages that have risen to prominence including B.1.177, the lineage with the highest relative abundance during the initial phylogenetic observation of VOC 202012/01. The shaded regions show conservative 95% rejection intervals; VOC 202012/01 is the first strain to exceed this threshold of faster relativized growth. Although many lineages exhibit above-average rates of growth, VOC 202012/01 has had the highest average relativized growth of any lineage in the history of COG-UK surveillance of SARS-COV-2. (B) Plotting all lineages’ relativized growth rates [ρ(t)] as a function of lineage age with conservative 95% rejection intervals highlights the significantly faster growth of VOC 202012/01 relative to other lineages at comparable times since their initial observation. Later declines in VOC and B.1.177 correspond to highly uncertain estimates of growth rates for data that are yet to be backfilled, so these declines in ρ(t) are sensitive to the processing of future sequences from recent dates (fig. S1). (C) Muller plots of the relative abundances of the major SARS-CoV-2 variants in the UK, based on a multinomial spline fit to COG-UK sequence data (Table 1 and table S1, separate-slopes multinomial spline model). A model extrapolation until 1 March 2021 is shown (shaded area). Minority variants are 440 circulating SARS-CoV-2 variants of low abundance. Specific colors represent the same lineages in (A) to (C). (D) Mean reproduction number over 7-day periods in 149 upper-tier local authorities of England (colored by the NHS England region they are within) plotted against the weekly proportion of Pillar 2 community SARS-CoV-2 tests with S gene target failure shows the spread of VOC 202012/01, a corresponding increase in the reproduction number in each local authority, and the eventual impact of targeted government restrictions from 20 December 2020. Testing data are shown for the week after the reproduction number estimates to account for delays from infection to test.
Fig. 2 Measuring the growth rate of VOC 202012/01. (A) Average relativized growth rate (i.e., a measure of variant fitness relative to other variants present during the 31 days after initial phylogenetic observation of a given variant) for all lineages in the COG-UK dataset, highlighting many lineages that have risen to prominence including B.1.177, the lineage with the highest relative abundance during the initial phylogenetic observation of VOC 202012/01. The shaded regions show conservative 95% rejection intervals; VOC 202012/01 is the first strain to exceed this threshold of faster relativized growth. Although many lineages exhibit above-average rates of growth, VOC 202012/01 has had the highest average relativized growth of any lineage in the history of COG-UK surveillance of SARS-COV-2. (B) Plotting all lineages’ relativized growth rates [ρ(t)] as a function of lineage age with conservative 95% rejection intervals highlights the significantly faster growth of VOC 202012/01 relative to other lineages at comparable times since their initial observation. Later declines in VOC and B.1.177 correspond to highly uncertain estimates of growth rates for data that are yet to be backfilled, so these declines in ρ(t) are sensitive to the processing of future sequences from recent dates (fig. S1). (C) Muller plots of the relative abundances of the major SARS-CoV-2 variants in the UK, based on a multinomial spline fit to COG-UK sequence data (Table 1 and table S1, separate-slopes multinomial spline model). A model extrapolation until 1 March 2021 is shown (shaded area). Minority variants are 440 circulating SARS-CoV-2 variants of low abundance. Specific colors represent the same lineages in (A) to (C). (D) Mean reproduction number over 7-day periods in 149 upper-tier local authorities of England (colored by the NHS England region they are within) plotted against the weekly proportion of Pillar 2 community SARS-CoV-2 tests with S gene target failure shows the spread of VOC 202012/01, a corresponding increase in the reproduction number in each local authority, and the eventual impact of targeted government restrictions from 20 December 2020. Testing data are shown for the week after the reproduction number estimates to account for delays from infection to test.CC BY · PubMed Central
Fig. 3 Comparison of possible biological mechanisms underlying the rapid spread of VOC 202012/01. Each row shows a different assumed mechanism. (A) Relative frequency of VOC 202012/01 (black line and ribbon respectively denote observed S gene target failure frequency with 95% binomial credible interval; purple line and ribbon respectively denote mean and 95% credible interval from model fit). (B) Posterior estimates (mean and 95% credible intervals) for relative odds of hospitalization (severe illness), relative odds of ICU admission (critical illness), relative odds of death (fatal illness), growth rate as a multiplicative factor per week [i.e., exp(7·∆r)], and the parameter that defines the hypothesized mechanism; all parameters are relative to those estimated for preexisting variants. (C to E) Illustrative model fits for the South East NHS England region: (C) fitted two-strain increased transmissibility model with VOC 202012/01 included; (D) fitted two-strain increased transmissibility model with VOC 202012/01 removed; (E) fitted single-strain model without emergence of VOC 202012/01. Black lines denote observed data; error bars denote the date range and 95% credible intervals for observed PCR prevalence and seroprevalence; colored lines and ribbons denote median and 95% credible intervals from model fit.
Fig. 3 Comparison of possible biological mechanisms underlying the rapid spread of VOC 202012/01. Each row shows a different assumed mechanism. (A) Relative frequency of VOC 202012/01 (black line and ribbon respectively denote observed S gene target failure frequency with 95% binomial credible interval; purple line and ribbon respectively denote mean and 95% credible interval from model fit). (B) Posterior estimates (mean and 95% credible intervals) for relative odds of hospitalization (severe illness), relative odds of ICU admission (critical illness), relative odds of death (fatal illness), growth rate as a multiplicative factor per week [i.e., exp(7·∆r)], and the parameter that defines the hypothesized mechanism; all parameters are relative to those estimated for preexisting variants. (C to E) Illustrative model fits for the South East NHS England region: (C) fitted two-strain increased transmissibility model with VOC 202012/01 included; (D) fitted two-strain increased transmissibility model with VOC 202012/01 removed; (E) fitted single-strain model without emergence of VOC 202012/01. Black lines denote observed data; error bars denote the date range and 95% credible intervals for observed PCR prevalence and seroprevalence; colored lines and ribbons denote median and 95% credible intervals from model fit.CC BY · PubMed Central
Fig. 4 Projections of epidemic dynamics under different control measures. We compare four alternative scenarios for nonpharmaceutical interventions from 1 January 2021: (i) mobility returning to levels observed during relatively moderate restrictions in early October 2020; (ii) mobility as observed during the second lockdown in England in November 2020, then gradually returning to October 2020 levels from 1 March to 1 April 2021, with schools open; (iii) as (ii), but with schools closed until 15 February 2021; (iv) as (iii), but with a lockdown of greater stringency as observed in March 2020 (fig. S20). (A) Without vaccination. (B) With 200,000 people vaccinated per week. (C) With 2 million people vaccinated per week. We assume that vaccination confers 95% vaccine efficacy against disease and 60% vaccine efficacy against infection, and that vaccination starts on 1 January 2021 with vaccine protection starting immediately upon receipt. This is intended to approximate the fact that vaccination started in early December, with full protection occurring after a time lag and potentially after a second dose. Vaccines are given first to people aged 70+ until 85% coverage is reached in this age group, then to people aged 60+ until 85% coverage is reached in this age group, continuing into younger age groups in 10-year decrements. Resurgences starting in March 2021 are due to the relaxation of nonpharmaceutical interventions, including reopening schools (fig. S20). Median and 95% credible intervals are shown. The dashed lines in rows 2 and 3 show peak hospitalizations and deaths from the first COVID-19 wave in England (April 2020).
Fig. 4 Projections of epidemic dynamics under different control measures. We compare four alternative scenarios for nonpharmaceutical interventions from 1 January 2021: (i) mobility returning to levels observed during relatively moderate restrictions in early October 2020; (ii) mobility as observed during the second lockdown in England in November 2020, then gradually returning to October 2020 levels from 1 March to 1 April 2021, with schools open; (iii) as (ii), but with schools closed until 15 February 2021; (iv) as (iii), but with a lockdown of greater stringency as observed in March 2020 (fig. S20). (A) Without vaccination. (B) With 200,000 people vaccinated per week. (C) With 2 million people vaccinated per week. We assume that vaccination confers 95% vaccine efficacy against disease and 60% vaccine efficacy against infection, and that vaccination starts on 1 January 2021 with vaccine protection starting immediately upon receipt. This is intended to approximate the fact that vaccination started in early December, with full protection occurring after a time lag and potentially after a second dose. Vaccines are given first to people aged 70+ until 85% coverage is reached in this age group, then to people aged 60+ until 85% coverage is reached in this age group, continuing into younger age groups in 10-year decrements. Resurgences starting in March 2021 are due to the relaxation of nonpharmaceutical interventions, including reopening schools (fig. S20). Median and 95% credible intervals are shown. The dashed lines in rows 2 and 3 show peak hospitalizations and deaths from the first COVID-19 wave in England (April 2020).CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 60 references

Cited by

Sorted by citations

Items 901–1,000 of 1,005

Related

See all

Metadata

Authors
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., Wenseleers, T., Gimma, A., Waites, W., Wong, K. L. M., van Zandvoort, K., Silverman, J. D., CMMID COVID-19 Working Group, The COVID-19 Genomics UK (COG-UK) Consortium, Diaz-Ordaz, K., Keogh, R., Eggo, R. M., Funk, S., Jit, M., Atkins, K. E., & Edmunds, W. J.
Affiliations
  • London School of Hygiene & Tropical Medicine (GB)
  • KU Leuven (BE)
  • Pennsylvania State University (US)
Corresponding author
Davies, Nicholas G.
ORCID
Venue
Science
Publisher
openRxiv
Published
2020-12-26
Volume
372
Issue
6538
ISSN
0036-8075 (ISSN-L)
DOI
10.1101/2020.12.24.20248822
PMC
PMC8128288
OpenAlex
W3134208712
Cited by
2,557
References
60
Citations by year
2026: 54 · 2025: 90 · 2024: 184 · 2023: 323 · 2022: 839 · 2021: 1060 · 2020: 6
FWCI
233.82
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Science (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • University of Birmingham Research Portal (University of Birmingham) (publishedVersion, cc-by)
  • ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion, cc-by)
  • Northumbria Research Link (Northumbria University) (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • Strathprints: The University of Strathclyde institutional repository (University of Strathclyde) (acceptedVersion)
  • Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion, cc-by)
  • Lirias (KU Leuven) (submittedVersion, other-oa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion)
  • Apollo
Funders
  • Bill and Melinda Gates Foundation (INV-016832, OPP1184344, INV-003174)
  • University of Kentucky
  • University of Bern
  • Wellcome Trust (206250, 210758/Z/18/Z, 206250/Z/17/Z, Z/17/Z, 221303/Z/20/Z, 221303, 210758, 218554/Z/19/Z)
  • UK Research and Innovation (ES/P010873/1, ES/P010873, MC_PC_19027)
  • Universitätsspital Basel
  • National Institute for Health Research Health Protection Research Unit (NIHR200908, NIHR200929)
  • National Institute for Health and Care Research ((NIHR200929), MR/V027956/1, (NIHR200908), 16/137/109, 16/137/10)
  • Research Councils UK (MR/S003975/1, ES/P010873/1)
  • Academy of Medical Sciences (AMS-CSF4-Torok)
  • University of Warwick
  • European Commission (101003688, COVID-19, 19065)
  • Public Health England
  • CANDU Owners Group
  • Eidgenössische Technische Hochschule Zürich
  • Hôpitaux Universitaires de Genève
  • Université de Sfax
  • Foreign, Commonwealth and Development Office (221303/Z/20/Z)
  • Medical Research Council (MR/S003975/1, 206250/Z/17/Z, MR/V027956/1, NIHR200908, COVID-19, MC_PC_19065)
  • Economic and Social Research Council (ES/P010873/1)
  • Statens Serum Institut
  • Research England
  • National Institute of General Medical Sciences (T32GM145449)
  • H2020 European Research Council (757688)
  • Health Data Research UK
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
Keywords
SARS-CoV-2, B.1.1.7 variant, reproduction number, SARS-CoV-2 transmission, epidemic forecasting, COVID-19 containment measures, vaccine rollout, school closures, England
MeSH terms
COVID-19, SARS-CoV-2, COVID-19 Vaccines, Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Communicable Disease Control, England, Europe, Female, Humans, Infant, Male, Middle Aged, Models, Theoretical, Mutation, Severity of Illness Index, Socioeconomic Factors, United States, Viral Load, Basic Reproduction Number, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review