SynthesisBMJ open2020
Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research.
Synthesis in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 268 papers, 7 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
268 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Meta-Analysis of COVID-19 Cluster Events Suggestive of Long-Distance Airborne Transmission/Inhalation.MicrobiologyOpen · 2026Pooled it
- Consolidating Estimates of the Incubation Period for Omicron Subvariants From the Literature and Their Comparison to the Estimate From Taiwan: A Systematic Review and Meta-Analysis, September 2024.Influenza and other respiratory viruses · 2025Pooled 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
- Inferring the true number of SARS-CoV-2 infections in Japan.Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2022Pooled it
- Comprehensive estimation for the length and dispersion of COVID-19 incubation period: a systematic review and meta-analysis.Infection · 2022Pooled it
- Incubation Period of COVID-19 Caused by Unique SARS-CoV-2 Strains: A Systematic Review and Meta-analysis.JAMA network open · 2022Pooled it
- Presymptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data.BMJ open · 2021Pooled it
- Efficacy and safety of a single dose of casirivimab and imdevimab for the prevention of COVID-19 over an 8-month period: a randomised, double-blind, placebo-controlled trial.The Lancet. Infectious diseases · 2022Trial
- On the type II exponentiated half-logistic exponential distribution with applications to hydrological and financial data.Scientific reports · 2026Article
- Assessment of simulation-based inference methods for stochastic compartmental models in epidemiological research.PloS one · 2026Article
- Bigger is faster in the adaptive immune response.Scientific reports · 2025Article
- Models for SARS-CoV-2 health policies: social distancing amid vaccination and virus variants.Royal Society open science · 2025Article
- Comparison of contact tracing methods: A modelling study.Infectious Disease Modelling · 2025Article
- A Retrospective Multicenter Study of Arterial Thromboembolic Events in Hospitalized COVID-19 Patients: Incidence and Imaging Characteristics.Clinical neuroradiology · 2025Article
- COVID-19 clinical presentation, management, and epidemiology: a concise compendium.Frontiers in public health · 2025Review
- Adaptive vaccination and surveillance testing strategies for infectious diseases with diverse strain dynamics.Health systems (Basingstoke, England) · 2025Article
- Article
- Nurses' perspectives on working conditions while caring for patients with COVID-19 during the epidemic threat in Poland.Frontiers in public health · 2025Article
- COVID-19 Reproduction Numbers and Long COVID Prevalences in California State Prisons.medRxiv : the preprint server for health sciences · 2024Article
- Addressing current limitations of household transmission studies by collecting contact data.American journal of epidemiology · 2024Article
208 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation period of COVID-19.
designRapid systematic review and meta-analysis of observational research.
settingInternational studies on incubation period of COVID-19.
participantsSearches were carried out in PubMed, Google Scholar, Embase, Cochrane Library as well as the preprint servers MedRxiv and BioRxiv. Studies were selected for meta-analysis if they reported either the parameters and CIs of the distributions fit to the data, or sufficient information to facilitate calculation of those values. After initial eligibility screening, 24 studies were selected for initial review, nine of these were shortlisted for meta-analysis. Final estimates are from meta-analysis of eight studies. PRIMARY OUTCOME MEASURES: Parameters of a lognormal distribution of incubation periods.
resultsThe incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters (95% CIs) of 1.63 (95% CI 1.51 to 1.75) and 0.50 (95% CI 0.46 to 0.55), respectively. The corresponding mean (95% CIs) was 5.8 (95% CI 5.0 to 6.7) days. It should be noted that uncertainty increases towards the tail of the distribution: the pooled parameter estimates (95% CIs) resulted in a median incubation period of 5.1 (95% CI 4.5 to 5.8) days, whereas the 95th percentile was 11.7 (95% CI 9.7 to 14.2) days.
conclusionsThe choice of which parameter values are adopted will depend on how the information is used, the associated risks and the perceived consequences of decisions to be taken. These recommendations will need to be revisited once further relevant information becomes available. Accordingly, we present an R Shiny app that facilitates updating these estimates as new data become available.
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Registered trials
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.