International Journal of Infectious Diseases · 2011 · 404 citations · 44 references
Veterinary MedicineInfectious Disease ControlInfectious DiseasesDisease SurveillanceHost-pathogen InteractionsInfectious Disease EpidemiologyDisease SpreadInfectious Disease DynamicsOutbreak ManagementPandemic PreparednessRespiratory Infectious DiseasesTransmission DynamicsHost Immune SuppressionImmune Suppression MechanismsInfectious Disease ManagementPathogen Spread DynamicsPathogen Spread In PopulationsPathogen-host InteractionsSevere Acute Respiratory SyndromeSuper-spreading Events
Early studies and the 20/80 rule revealed that a small fraction of infected individuals, termed super‑spreaders, drive most transmission events across many pathogens, as shown during the SARS pandemic. The study aims to predict and identify super‑spreaders to address medical and public health challenges and improve pandemic preparedness. The authors analyze SARS transmission and other outbreaks, showing that super‑spreading events result from multiple factors such as co‑infection, immune suppression, airflow changes, delayed admission, misdiagnosis, and inter‑hospital transfers.
Early studies that explored host–pathogen interactions assumed that infected individuals within a population have equal chances of transmitting the infection to others. Subsequently, in what became known as the 20/80 rule, a small percentage of individuals within any population was observed to control most transmission events. This empirical rule was shown to govern inter-individual transmission dynamics for many pathogens in several species, and individuals who infect disproportionately more secondary contacts, as compared to most others, became known as super-spreaders. Studies conducted in the wake of the severe acute respiratory syndrome (SARS) pandemic revealed that, in the absence of super-spreading events, most individuals infect few, if any, secondary contacts. The analysis of SARS transmission, and reports from other outbreaks, unveil a complex scenario in which super-spreading events are shaped by multiple factors, including co-infection with another pathogen, immune suppression, changes in airflow dynamics, delayed hospital admission, misdiagnosis, and inter-hospital transfers. Predicting and identifying super-spreaders open significant medical and public health challenges, and represent important facets of infectious disease management and pandemic preparedness plans.
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Superspreading and the effect of individual variation on disease emergence
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