ArticleeLife2022
Inference of the SARS-CoV-2 generation time using UK household data.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Assessing changes in incubation period, serial interval, and generation time of SARS-CoV-2 variants of concern: a systematic review and meta-analysis.BMC medicine · 2023Pooled it
- Robust estimation of the time-dependent reproduction number in the presence of weekend reporting effects.BMC global and public health · 2026Article
- Assessing SARS-CoV-2 transmission in African households from the reanalysis of serosurveys.American journal of epidemiology · 2026Article
- Estimating the generation time for SARS-CoV-2 transmission using United States household data, December 2021-May 2023.Scientific reports · 2026Article
- Identifying the optimal rapid antigen test for screening and determining the end of isolation: A modeling study.PLoS computational biology · 2026Article
- Chronic infections can generate SARS-CoV-2-like bursts of viral evolution without epistasis.Virus evolution · 2026Article
- Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Daily profile of COVID-19 infections in Europe - a biophysical perspective.Biophysical reviews · 2025Review
- The time-dependent reproduction number for epidemics in heterogeneous populations.Journal of the Royal Society, Interface · 2025Article
- Simulation-based inference of the time-dependent reproduction number from temporally aggregated and under-reported disease incidence time series data.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Article
- Estimating the generation time for influenza transmission using household data in the United States.Epidemics · 2025Article
- Modelling the effectiveness of antiviral treatment strategies to prevent household transmission of acute respiratory viruses.PLoS computational biology · 2024Article
- Fine-scale spatial and social patterns of SARS-CoV-2 transmission from identical pathogen sequences.medRxiv : the preprint server for health sciences · 2024Article
- Model-based estimates of age-structured SARS-CoV-2 epidemiology in households.BMC public health · 2024Article
- Chronic infections can generate SARS-CoV-2-like bursts of viral evolution without epistasis.bioRxiv : the preprint server for biology · 2024Article
- A retrospective assessment of forecasting the peak of the SARS-CoV-2 Omicron BA.1 wave in England.PLoS computational biology · 2024Article
- Estimating the generation time for influenza transmission using household data in the United States.medRxiv : the preprint server for health sciences · 2024Article
- Optimizing the timing of an end-of-outbreak declaration: Ebola virus disease in the Democratic Republic of the Congo.Science advances · 2024Article
- Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey.Infectious Disease Modelling · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The distribution of the generation time (the interval between individuals becoming infected and transmitting the virus) characterises changes in the transmission risk during SARS-CoV-2 infections. Inferring the generation time distribution is essential to plan and assess public health measures. We previously developed a mechanistic approach for estimating the generation time, which provided an improved fit to data from the early months of the COVID-19 pandemic (December 2019-March 2020) compared to existing models (Hart et al., 2021). However, few estimates of the generation time exist based on data from later in the pandemic. Here, using data from a household study conducted from March to November 2020 in the UK, we provide updated estimates of the generation time. We considered both a commonly used approach in which the transmission risk is assumed to be independent of when symptoms develop, and our mechanistic model in which transmission and symptoms are linked explicitly. Assuming independent transmission and symptoms, we estimated a mean generation time (4.2 days, 95% credible interval 3.3-5.3 days) similar to previous estimates from other countries, but with a higher standard deviation (4.9 days, 3.0-8.3 days). Using our mechanistic approach, we estimated a longer mean generation time (5.9 days, 5.2-7.0 days) and a similar standard deviation (4.8 days, 4.0-6.3 days). As well as estimating the generation time using data from the entire study period, we also considered whether the generation time varied temporally. Both models suggest a shorter mean generation time in September-November 2020 compared to earlier months. Since the SARS-CoV-2 generation time appears to be changing, further data collection and analysis is necessary to continue to monitor ongoing transmission and inform future public health policy decisions.
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