key: cord-0920150-w4l2vpiy authors: On Kwok, Kin; Hin Chan, Henry Ho; Huang, Ying; Cheong Hui, David Shu; Anantharajah Tambyah, Paul; In Wei, Wan; Kwan Chau, Patsy Yuen; Shan Wong, Samuel Yeung; Tze Tang, Julian Wei title: Inferring super-spreading from transmission clusters of COVID-19 in Hong Kong, Japan and Singapore date: 2020-05-22 journal: J Hosp Infect DOI: 10.1016/j.jhin.2020.05.027 sha: d9dc334d0e8f0aa12a77c4c805869984fcae5b30 doc_id: 920150 cord_uid: w4l2vpiy Super-spreading events in an outbreak can change the nature of an epidemic. Therefore, it is useful for public health teams to determine if an ongoing outbreak has any contribution from such events, which may be amenable to interventions. We estimated the basic reproductive number (R(0)) and the dispersion factor (k) from empirical data on clusters of epidemiologically-linked COVID-19 cases in Hong Kong, Japan and Singapore. This allowed us to infer the presence or absence of super-spreading events during the early phase of these outbreaks. The relatively large values of k implied that large cluster sizes, compatible with super-spreading, were unlikely. Super-spreading events in an outbreak can change the nature of an epidemic. Therefore, it is useful for public health teams to determine if an ongoing outbreak has any contribution from such events, which may be amenable to interventions. We estimated the basic reproductive number (R 0 ) and the dispersion factor (k) from empirical data on clusters of epidemiologicallylinked COVID-19 cases in Hong Kong, Japan and Singapore. This allowed us to infer the presence or absence of super-spreading events during the early phase of these outbreaks. The relatively large values of k implied that large cluster sizes, compatible with super-spreading, were unlikely. Word count = 100 The spread of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2), from Wuhan to other Asian regions is ongoing. As of 3 March 2020, the number of laboratory-confirmed COVID-19 cases in Hong Kong (HK), Japan (JP) and Singapore (SG) were 101, 284, and 110; whereas the number of deaths were 2 (HK), 6 (JP) and 0 (SG) respectively. Human-to-human transmission clusters have been observed, including 16 cases originating from a Buddhist worship hall (HK); 28 cases linked to a couple returning from Hawaii (JP), and 31 cases related to a church gathering (SG). Here, we explore whether super-spreading is involved in the early phase of the COVID-19 outbreaks in these populations. Generally, super-spreaders are individuals who generate a more-than-expected number of In this study, we applied a previously published method [3] to empirical data on clusters of epidemiologically-linked COVID-19 cases. With estimates of the basic reproductive number (R 0 ), which is the number of secondary cases generated by a typical index case in a wholly susceptible population, and the dispersion factor (k), which is a measure of variability in empirical cluster sizes, we explored the presence of SSEs in outbreaks of COVID-19 in HK, JP and SG. Using publicly available data on laboratory-confirmed cases of COVID-19 (up to 3 March 2020) for HK, JP and SG, from the Centre for Health Protection (HK), Ministry of Health, Labour and Welfare (JP) and Ministry of Health (SG) respectively, we obtained an empirical distribution of secondary case transmission cluster sizes from each population. In this context, a cluster was defined where each case within it could be epidemiologically linked to the others. Such epidemiological links include temporal and geographical groupings that involve one or more index cases and secondary transmissions. A single index case was considered as a cluster of size one. Cases with unclear epidemiological links were excluded from the analysis. These included: (i) imported cases intercepted at borders with subsequent quarantine or medical surveillance, for example cases evacuated from affected areas by government-chartered flights (SG, JP); and (ii) cases identified from the international conveyance who were then isolated (HK, JP). Cases that appeared to be re-infected upon hospital discharge (one case in JP) were only counted once. A previously published method was applied to the extracted data (Online Appendix) [3] to estimate R 0 and k, and determine if SSEs were involved in recent COVID-19 outbreaks in HK, JP and SG so far. For k <1, it represents a greater degree of dispersion, hence more variability in transmission cluster sizes, such that SSEs may be more likely. We also investigated the relationship among R 0 , k and the probabilities of observing a cluster with size being at least the empirically maximum cluster size as of 3 March 2020 ( Figure S1 ). We denote p n as the probability of observing a cluster p of size being at least n. For a fixed value of k, p 16 (HK), p 28 (JP) and p 31 (SG) all increased with R 0 . When R 0 is small (say 0.3), a higher variation in the number of secondary cases (that is, a smaller k) increases the chance of observing a large transmission cluster (suggestive of a SSE). This effect was reversed when R 0 >0.9. These two effects were consistent across the three populations. 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