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A social network analysis of the spread of COVID-19 in South Korea and policy implications
This study estimates the COVID-19 infection network from actual data and draws on implications for policy and research. Using contact tracing information of 3283 confirmed patients in Seoul metropolitan areas from January 20, 2020 to July 19, 2020, this study created an infection network and analyze...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060276/ https://www.ncbi.nlm.nih.gov/pubmed/33883601 http://dx.doi.org/10.1038/s41598-021-87837-0 |
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author | Jo, Wonkwang Chang, Dukjin You, Myoungsoon Ghim, Ghi-Hoon |
author_facet | Jo, Wonkwang Chang, Dukjin You, Myoungsoon Ghim, Ghi-Hoon |
author_sort | Jo, Wonkwang |
collection | PubMed |
description | This study estimates the COVID-19 infection network from actual data and draws on implications for policy and research. Using contact tracing information of 3283 confirmed patients in Seoul metropolitan areas from January 20, 2020 to July 19, 2020, this study created an infection network and analyzed its structural characteristics. The main results are as follows: (i) out-degrees follow an extremely positively skewed distribution; (ii) removing the top nodes on the out-degree significantly decreases the size of the infection network, and (iii) the indicators that express the infectious power of the network change according to governmental measures. Efforts to collect network data and analyze network structures are urgently required for the efficiency of governmental responses to COVID-19. Implications for better use of a metric such as R0 to estimate infection spread are also discussed. |
format | Online Article Text |
id | pubmed-8060276 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80602762021-04-22 A social network analysis of the spread of COVID-19 in South Korea and policy implications Jo, Wonkwang Chang, Dukjin You, Myoungsoon Ghim, Ghi-Hoon Sci Rep Article This study estimates the COVID-19 infection network from actual data and draws on implications for policy and research. Using contact tracing information of 3283 confirmed patients in Seoul metropolitan areas from January 20, 2020 to July 19, 2020, this study created an infection network and analyzed its structural characteristics. The main results are as follows: (i) out-degrees follow an extremely positively skewed distribution; (ii) removing the top nodes on the out-degree significantly decreases the size of the infection network, and (iii) the indicators that express the infectious power of the network change according to governmental measures. Efforts to collect network data and analyze network structures are urgently required for the efficiency of governmental responses to COVID-19. Implications for better use of a metric such as R0 to estimate infection spread are also discussed. Nature Publishing Group UK 2021-04-21 /pmc/articles/PMC8060276/ /pubmed/33883601 http://dx.doi.org/10.1038/s41598-021-87837-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jo, Wonkwang Chang, Dukjin You, Myoungsoon Ghim, Ghi-Hoon A social network analysis of the spread of COVID-19 in South Korea and policy implications |
title | A social network analysis of the spread of COVID-19 in South Korea and policy implications |
title_full | A social network analysis of the spread of COVID-19 in South Korea and policy implications |
title_fullStr | A social network analysis of the spread of COVID-19 in South Korea and policy implications |
title_full_unstemmed | A social network analysis of the spread of COVID-19 in South Korea and policy implications |
title_short | A social network analysis of the spread of COVID-19 in South Korea and policy implications |
title_sort | social network analysis of the spread of covid-19 in south korea and policy implications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060276/ https://www.ncbi.nlm.nih.gov/pubmed/33883601 http://dx.doi.org/10.1038/s41598-021-87837-0 |
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