SynthesisBMC public health2023
Superspreading, overdispersion and their implications in the SARS-CoV-2 (COVID-19) pandemic: a systematic review and meta-analysis of the literature.
Synthesis in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 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.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Host factors associated with respiratory particle emission and virus presence within respiratory particles: a systematic review.Frontiers in microbiology · 2025Pooled it
- Superspreading of SARS-CoV-2: a systematic review and meta-analysis of event attack rates and individual transmission patterns.Epidemiology and infection · 2024Pooled it
- Disentangling the drivers of heterogeneity in SARS-CoV-2 transmission from data on viral load and daily contact rates.PLoS computational biology · 2026Article
- The impact of school-based mitigation measures on the transmission of respiratory pathogens: the case of SARS-CoV-2.International journal of epidemiology · 2026Article
- Identifying the optimal rapid antigen test for screening and determining the end of isolation: A modeling study.PLoS computational biology · 2026Article
- Stochastic resilience enables particle foraging in oligotrophic marine environments.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Heterogeneity of Airborne Virus Transmission in the Built Environment: A Narrative Review.Pathogens & immunity · 2026Review
- Review
- Controlled human influenza infection reveals heterogeneous expulsion of infectious virus into air.medRxiv : the preprint server for health sciences · 2025Article
- Belgium's SARS-CoV-2 contact tracing effectively curbed transmission, yet challenges persist in terms of delays, scalability and population adherence.BMC public health · 2025Article
- Effects of individual variation and seasonal vaccination on disease risks.Nature communications · 2025Article
- Epidemiological Analysis of the COVID-19 Clusters in the Early Stages of the Epidemic in Shanghai, China: Pandemic-to-Epidemic Response Shift.Tropical medicine and infectious disease · 2025Article
- Variability in the Population Diffusion Patterns of SARS-CoV-2 by Exposure Setting and Its Roles in Driving Epidemic Dynamics.Influenza and other respiratory viruses · 2025Article
- Estimating Re and overdispersion in secondary cases from the size of identical sequence clusters of SARS-CoV-2.PLoS computational biology · 2025Article
- Estimation of end-of-outbreak probabilities in the presence of delayed and incomplete case reporting.Proceedings. Biological sciences · 2025Article
- 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
- High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark.Nature communications · 2024Article
- Epidemiological inference at the threshold of data availability: an influenza A(H1N2)v spillover event in the United Kingdom.Journal of the Royal Society, Interface · 2024Article
- Inferring COVID-19 testing and vaccination behavior from New Jersey testing data.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA recurrent feature of infectious diseases is the observation that different individuals show different levels of secondary transmission. This inter-individual variation in transmission potential is often quantified by the dispersion parameter k. Low values of k indicate a high degree of variability and a greater probability of superspreading events. Understanding k for COVID-19 across contexts can assist policy makers prepare for future pandemics.
methodsA literature search following a systematic approach was carried out in PubMed, Embase, Web of Science, Cochrane Library, medRxiv, bioRxiv and arXiv to identify publications containing epidemiological findings on superspreading in COVID-19. Study characteristics, epidemiological data, including estimates for k and R0, and public health recommendations were extracted from relevant records.
resultsThe literature search yielded 28 peer-reviewed studies. The mean k estimates ranged from 0.04 to 2.97. Among the 28 studies, 93% reported mean k estimates lower than one, which is considered as marked heterogeneity in inter-individual transmission potential. Recommended control measures were specifically aimed at preventing superspreading events. The combination of forward and backward contact tracing, timely confirmation of cases, rapid case isolation, vaccination and preventive measures were suggested as important components to suppress superspreading.
conclusionsSuperspreading events were a major feature in the pandemic of SARS-CoV-2. On the one hand, this made outbreaks potentially more explosive but on the other hand also more responsive to public health interventions. Going forward, understanding k is critical for tailoring public health measures to high-risk groups and settings where superspreading events occur.
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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.