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

• Published in: International journal of environmental research and public health Vol. 18; no. 24; p. 12893
• Main Authors: Lee, Hyojung, Han, Changyong, Jung, Jooyi, Lee, Sunmi
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 07.12.2021; MDPI
• Subjects: Cluster analysis; Coronaviruses; COVID-19; Disease Outbreaks; Disease transmission; Epidemics; Epidemiology; Heterogeneity; Humans; Infections; Middle East respiratory syndrome; Nightclubs; Pandemics; Religious groups; Republic of Korea - epidemiology; SARS-CoV-2; Schools; Severe acute respiratory syndrome coronavirus 2; Social distancing; Viral diseases; Workplaces; Republic of Korea; South Korea; China; COVID-19; SARS-CoV-2; statistical model; cluster-specific reproduction number; cluster-induced transmissions; superspreading events
• ISSN: 1660-4601; 1661-7827; 1660-4601
• DOI: 10.3390/ijerph182412893

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 Reff and the dispersion parameter κ using a maximum likelihood method. We also compute Rm as the mean secondary daily cases during the infection period with a cluster size . 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 Reff 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 Reff 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.