Superspreaders, infected individuals who result in an outsized number of secondary cases, are believed to underlie a significant fraction of total SARS-CoV-2 transmission. Here, we combine empirical observations of SARS-CoV and SARS-CoV-2 transmission and extreme value statistics to show that the distribution of secondary cases is consistent with being fat-tailed, implying that large superspreading events are extremal, yet probable, occurrences. We integrate these results with interaction-based network models of disease transmission and show that superspreading, when it is fat-tailed, leads to pronounced transmission by increasing dispersion. Our findings indicate that large superspreading events should be the targets of interventions that minimize tail exposure.
【저자키워드】 COVID-19, SARS-CoV-2, Infectious disease, superspreading, extreme value theory, 【초록키워드】 SARS-CoV, Intervention, Transmission, SARS-CoV-2 transmission, superspreading event, target, distribution, disease transmission, observation, infected individual, fraction, secondary cases, secondary case, extreme, underlie, 【제목키워드】 coronavirus,