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Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea
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 fro...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8701974/ https://www.ncbi.nlm.nih.gov/pubmed/34948504 http://dx.doi.org/10.3390/ijerph182412893 |
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author | Lee, Hyojung Han, Changyong Jung, Jooyi Lee, Sunmi |
author_facet | Lee, Hyojung Han, Changyong Jung, Jooyi Lee, Sunmi |
author_sort | Lee, Hyojung |
collection | PubMed |
description | 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 [Formula: see text] and the dispersion parameter [Formula: see text] using a maximum likelihood method. We also compute [Formula: see text] 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 [Formula: see text] and [Formula: see text] 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 [Formula: see text] 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. |
format | Online Article Text |
id | pubmed-8701974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87019742021-12-24 Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea Lee, Hyojung Han, Changyong Jung, Jooyi Lee, Sunmi Int J Environ Res Public Health Article 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 [Formula: see text] and the dispersion parameter [Formula: see text] using a maximum likelihood method. We also compute [Formula: see text] 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 [Formula: see text] and [Formula: see text] 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 [Formula: see text] 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. MDPI 2021-12-07 /pmc/articles/PMC8701974/ /pubmed/34948504 http://dx.doi.org/10.3390/ijerph182412893 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lee, Hyojung Han, Changyong Jung, Jooyi Lee, Sunmi Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea |
title | Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea |
title_full | Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea |
title_fullStr | Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea |
title_full_unstemmed | Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea |
title_short | Analysis of Superspreading Potential from Transmission Clusters of COVID-19 in South Korea |
title_sort | analysis of superspreading potential from transmission clusters of covid-19 in south korea |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8701974/ https://www.ncbi.nlm.nih.gov/pubmed/34948504 http://dx.doi.org/10.3390/ijerph182412893 |
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