ArticleeLife2021
Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled 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.
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
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Are medical procedures that induce coughing or involve respiratory suctioning associated with increased generation of aerosols and risk of SARS-CoV-2 infection? A rapid systematic review.The Journal of hospital infection · 2021Pooled it
- Accounting for the long-distance transmission route: An epidemiological model of airborne disease transmission in hospitals.PLoS computational biology · 2026Article
- Quantifying the role of pre-existing tissue resident cellular immunity in limiting respiratory virus transmission.PLoS pathogens · 2026Article
- Study design considerations in clinical trials testing transcutaneous stimulation for spinal cord injury.Spinal cord · 2026Review
- Superspreading and the evolution of virulence.PLoS computational biology · 2025Article
- The NOSTRA model: Coherent estimation of infection sources in the case of possible nosocomial transmission.PLoS computational biology · 2025Article
- Variable rates of SARS-CoV-2 evolution in chronic infections.PLoS pathogens · 2025Article
- Test allocation based on risk of infection from first and second order contact tracing.PloS one · 2025Article
- Revealing single-neuron and network-activity interaction by combining high-density microelectrode array and optogenetics.Nature communications · 2024Article
- Impact of interventions to reduce nosocomial transmission of SARS-CoV-2 in English NHS Trusts: a computational modelling study.BMC infectious diseases · 2024Article
- COVID-19 cluster surveillance using exposure data collected from routine contact tracing: The genomic validation of a novel informatics-based approach to outbreak detection in England.PLOS digital health · 2024Article
- Infectious Disease in the Workplace: Quantifying Uncertainty in Transmission.Bulletin of mathematical biology · 2024Article
- The effectiveness and efficiency of asymptomatic SARS-CoV-2 testing strategies for patient and healthcare workers within acute NHS hospitals during an omicron-like period.BMC infectious diseases · 2024Article
- Evaluating pooled testing for asymptomatic screening of healthcare workers in hospitals.BMC infectious diseases · 2023Article
- Article
- Physical distancing versus testing with self-isolation for controlling an emerging epidemic.Scientific reports · 2023Article
- Impact of supplementary air filtration on aerosols and particulate matter in a UK hospital ward: a case study.The Journal of hospital infection · 2023Article
- Article
- Antimicrobial oral lavage reduces the SARS-CoV-2 load in intubated patients: randomized clinical trial.Journal of oral microbiology · 2023Article
- Consideration of COVID-19 beyond the human-centred approach of prevention and control: the ONE-HEALTH perspective.Emerging microbes & infections · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
40 authors.
Funding
Abstract
SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.