Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea

Hyojung Lee, Changyong Han, Jooyi Jung and Sunmi Lee
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Hyojung Lee: Department of Statistics, Kyungpook National University, Daegu 41566, Korea
Changyong Han: Department of Applied Mathematics, Kyung Hee University, Yongin 17104, Korea
Jooyi Jung: Department of Biostatistics, Korea University, Seoul 02841, Korea
Sunmi Lee: Department of Applied Mathematics, Kyung Hee University, Yongin 17104, Korea

IJERPH, 2021, vol. 18, issue 24, 1-13

Abstract: The COVID-19 pandemic has been spreading worldwide with more than 246 million confirmed cases and 5 million deaths across more than 200 countries as of October 2021. There have been multiple disease clusters, and transmission in South Korea continues. We aim to analyze COVID-19 clusters in Seoul from 4 March to 4 December 2020. A branching process model is employed to investigate the strength and heterogeneity of cluster-induced transmissions. We estimate the cluster-specific effective reproduction number R eff and the dispersion parameter κ using a maximum likelihood method. We also compute R m as the mean secondary daily cases during the infection period with a cluster size m . As a result, a total of 61 clusters with 3088 cases are elucidated. The clusters are categorized into six groups, including religious groups, convalescent homes, and hospitals. The values of R eff and κ of all clusters are estimated to be 2.26 (95% CI: 2.02–2.53) and 0.20 (95% CI: 0.14–0.28), respectively. This indicates strong evidence for the occurrence of superspreading events in Seoul. The religious groups cluster has the largest value of R eff among all clusters, followed by workplaces, schools, and convalescent home clusters. Our results allow us to infer the presence or absence of superspreading events and to understand the cluster-specific characteristics of COVID-19 outbreaks. Therefore, more effective suppression strategies can be implemented to halt the ongoing or future cluster transmissions caused by small and sporadic clusters as well as large superspreading events.

Keywords: SARS-CoV-2; COVID-19; statistical model; superspreading events; cluster-induced transmissions; cluster-specific reproduction number (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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