Evidence map›Paper›PMID 35176230›Full record

ArticleThe Lancet. Infectious diseases2022

Generation time of the alpha and delta SARS-CoV-2 variants: an epidemiological analysis.

William S Hart, Elizabeth Miller, Nick J Andrews, Pauline Waight, Philip K Maini, Sebastian Funk, Robin N Thompson

Abstract read
In one paragraph

Article in The Lancet. Infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 143 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
143citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

143 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

83 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

William S HartMathematical Institute, University of Oxford, Oxford, UK.
Elizabeth MillerDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Immunisation and Countermeasures Division, UK Health Security Agency, London, UK.
Nick J AndrewsData and Analytical Sciences, UK Health Security Agency, London, UK.
Pauline WaightImmunisation and Countermeasures Division, UK Health Security Agency, London, UK.
Philip K MainiMathematical Institute, University of Oxford, Oxford, UK.
Sebastian FunkDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Robin N ThompsonMathematics Institute, University of Warwick, Coventry, UK; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, UK. Electronic address: robin.n.thompson@warwick.ac.uk.

Funding

Wellcome Trust 210758/Z/18/Z
6 · The paper itself

Abstract

backgroundIn May, 2021, the delta (B.1.617.2) SARS-CoV-2 variant became dominant in the UK, superseded by the omicron (B.1.1.529) variant in December, 2021. The delta variant is associated with increased transmissibility compared with the alpha variant, which was the dominant variant in the UK between December, 2020, and May, 2021. To understand transmission and the effectiveness of interventions, we aimed to investigate whether the delta variant generation time (the interval between infections in infector-infectee pairs) is shorter-ie, transmissions are happening more quickly-than that of the alpha variant.

methodsIn this epidemiological analysis, we analysed transmission data from an ongoing UK Health Security Agency (UKHSA) prospective household study. Households were recruited to the study after an index case had a positive PCR test and genomic sequencing was used to determine the variant responsible. By fitting a mathematical transmission model to the data, we estimated the intrinsic generation time (which assumes a constant supply of susceptible individuals throughout infection) and the household generation time (which reflects realised transmission in the study households, accounting for susceptible depletion) for the alpha and delta variants.

findingsBetween February and August, 2021, 227 households consisting of 559 participants were recruited to the UKHSA study. The alpha variant was detected or assumed to be responsible for infections in 131 households (243 infections in 334 participants) recruited in February-May, and the delta variant in 96 households (174 infections in 225 participants) in May-August. The mean intrinsic generation time was shorter for the delta variant (4·7 days, 95% credible interval [CI] 4·1-5·6) than the alpha variant (5·5 days, 4·7-6·5), with 92% posterior probability. The mean household generation time was 28% (95% CI 0-48%) shorter for the delta variant (3·2 days, 95% CI 2·5-4·2) than the alpha variant (4·5 days, 3·7-5·4), with 97·5% posterior probability.

interpretationThe delta variant transmits more quickly in households than the alpha variant, which can be attributed to faster depletion of susceptible individuals in households and a possible decrease in the intrinsic generation time. Interventions such as contact tracing, testing, and isolation might be less effective if transmission of the virus occurs quickly.

fundingNational Institute for Health Research, UK Health Security Agency, Engineering and Physical Sciences Research Council, and UK Research and Innovation.

Indexed as

COVID-19SARS-CoV-2Contact TracingHumansProspective Studies

Identifiers

PMID35176230
PMCPMC8843191

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.