PreprintCited by 60SARS-CoV-2 and COVID-19 ResearchCOVID-19 epidemiological studiesSARS-CoV-2 detection and testing

Increased infections, but not viral burden, with a new SARS-CoV-2 variant

Open access
Walker, A. Sarah, Vihta, Karina-Doris, Gethings, Owen, Pritchard, Emma, Jones, Joel, House, Thomas, Bell, Iain, Bell, John I +14 more·2021·medRxiv

Abstract

Background: A new variant of SARS-CoV-2, B.1.1.7/VOC202012/01, was identified in the UK in December-2020. Direct estimates of its potential to enhance transmission are limited. Methods: Nose and throat swabs from 28-September-2020 to 2-January-2021 in the UK’s nationally representative surveillance study were tested by RT-PCR for three genes (N, S and ORF1ab). Those positive only on ORF1ab+N, S-gene target failures (SGTF), are compatible with B.1.1.7/VOC202012/01. We investigated cycle threshold (Ct) values (a proxy for viral load), percentage of positives, population positivity and growth rates in SGTF vs non-SGTF positives. Results: 15,166(0.98%) of 1,553,687 swabs were PCR-positive, 8,545(56%) with three genes detected and 3,531(23%) SGTF. SGTF comprised an increasing, and triple-gene positives a decreasing, percentage of infections from late-November in most UK regions/countries, e.g. from 15% to 38% to 81% over 1.5 months in London. SGTF Ct values correspondingly declined substantially to similar levels to triple-gene positives. Population-level SGTF positivity remained low (<0.25%) in all regions/countries until late-November, when marked increases with and without self-reported symptoms occurred in southern England (to 1.5-3%), despite stable rates of non-SGTF cases. SGTF positivity rates increased on average 6% more rapidly than rates of non-SGTF positives (95% CI 4-9%) supporting addition rather than replacement with B.1.1.7/VOC202012/01. Excess growth rates for SGTF vs non-SGTF positives were similar in those up to high school age (5% (1-8%)) and older individuals (6% (4-9%)). Conclusions: Direct population-representative estimates show that the B.1.1.7/VOC202012/01 SARS-CoV-2 variant leads to higher infection rates, but does not seem particularly adapted to any age group.

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 · 10.1101/2021.01.13.21249721

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

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.

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. Endo A, Centre for the Mathematical Modelling of Infectious Diseases C-WG, Abbott S, Kucharski AJ, Funk S. Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. Wellcome Open Res 2020;5:67.
  2. Walker AS, Pritchard E, House T, et al. Viral load in community SARS-CoV-2 cases varies widely and temporally MedrXiv 2020;https://www.medrxiv.org/content/10.1101/2020.10.25.20219048v1. · DOI

Cited by

Sorted by citations

Authors
Walker, A. S., Vihta, K.-D., Gethings, O., Pritchard, E., Jones, J., House, T., Bell, I., Bell, J. I., Newton, J. N., Farrar, J., Diamond, I., Studley, R., Rourke, E., Hay, J., Hopkins, S., Crook, D., Peto, T., Matthews, P. C., Eyre, D. W., Stoesser, N., Pouwels, K. B., & COVID-19 Infection Survey team
Affiliations
  • National Institute for Health and Care Research (GB)
  • Office for National Statistics (GB)
  • Public Health England (GB)
  • University of Oxford (GB)
  • Wellcome Trust (GB)
  • Queen Elizabeth University Hospital (GB)
  • John Radcliffe Hospital (GB)
Corresponding author
Walker, A. Sarah
Venue
medRxiv
Publisher
openRxiv
Published
2021-01-15
OpenAlex
W3119143601
Cited by
58
References
19
Citations by year
2026: 1 · 2025: 1 · 2024: 2 · 2023: 5 · 2022: 10 · 2021: 38 · 2020: 1
Type
posted content
Language
en
Open access
Licence
cc-by-nc-nd
Locations
medRxiv (acceptedVersion, cc-by-nc-nd)
Funders
  • Scottish Government
  • Llywodraeth Cymru
  • National Institute for Health Research Health Protection Research Unit (NIHR200915)
  • National Institute for Health and Care Research (NIHR200915)
  • Department of Health and Social Care
  • University of Oxford (NIHR200915)
  • Public Health England (NIHR200915)
  • Oxford University Hospitals NHS Foundation Trust
  • Huo Family Foundation
  • Medical Research Council (MC_UU_12023/22, COVID-19)
  • NIHR Oxford Biomedical Research Centre (NIHR200915)
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 variant, S-gene target failure, viral load, cycle threshold, virus transmission, infection rate, growth rate, age-specific transmission, COVID-19 surveillance

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