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Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020

BACKGROUND: The novel coronavirus (coronavirus disease 2019 [COVID-19]) outbreak began in China in December last year, and confirmed cases began occurring in Korea in mid-February 2020. Since the end of February, the rate of infection has increased greatly due to mass (herd) infection within religio...

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Autores principales: Bae, Tae Wuk, Kwon, Kee Koo, Kim, Kyu Hyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Medical Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458854/
https://www.ncbi.nlm.nih.gov/pubmed/32864913
http://dx.doi.org/10.3346/jkms.2020.35.e317
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author Bae, Tae Wuk
Kwon, Kee Koo
Kim, Kyu Hyung
author_facet Bae, Tae Wuk
Kwon, Kee Koo
Kim, Kyu Hyung
author_sort Bae, Tae Wuk
collection PubMed
description BACKGROUND: The novel coronavirus (coronavirus disease 2019 [COVID-19]) outbreak began in China in December last year, and confirmed cases began occurring in Korea in mid-February 2020. Since the end of February, the rate of infection has increased greatly due to mass (herd) infection within religious groups and nursing homes in the Daegu and Gyeongbuk regions. This mass infection has increased the number of infected people more rapidly than was initially expected; the epidemic model based on existing studies had predicted a much lower infection rate and faster recovery. METHODS: The present study evaluated rapid infection spread by mass infection in Korea and the high mortality rate for the elderly and those with underlying diseases through the Susceptible-Exposed-Infected-Recovered-Dead (SEIRD) model. RESULTS: The present study demonstrated early infection peak occurrence (-6.3 days for Daegu and -5.3 days for Gyeongbuk) and slow recovery trend (= -1,486.6 persons for Daegu and -223.7 persons for Gyeongbuk) between the actual and the epidemic model for a mass infection region compared to a normal infection region. CONCLUSION: The analysis of the time difference between infection and recovery can help predict the epidemic peak due to mass (or normal) infection and can also be used as a time index to prepare medical resources.
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spelling pubmed-74588542020-09-06 Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020 Bae, Tae Wuk Kwon, Kee Koo Kim, Kyu Hyung J Korean Med Sci Original Article BACKGROUND: The novel coronavirus (coronavirus disease 2019 [COVID-19]) outbreak began in China in December last year, and confirmed cases began occurring in Korea in mid-February 2020. Since the end of February, the rate of infection has increased greatly due to mass (herd) infection within religious groups and nursing homes in the Daegu and Gyeongbuk regions. This mass infection has increased the number of infected people more rapidly than was initially expected; the epidemic model based on existing studies had predicted a much lower infection rate and faster recovery. METHODS: The present study evaluated rapid infection spread by mass infection in Korea and the high mortality rate for the elderly and those with underlying diseases through the Susceptible-Exposed-Infected-Recovered-Dead (SEIRD) model. RESULTS: The present study demonstrated early infection peak occurrence (-6.3 days for Daegu and -5.3 days for Gyeongbuk) and slow recovery trend (= -1,486.6 persons for Daegu and -223.7 persons for Gyeongbuk) between the actual and the epidemic model for a mass infection region compared to a normal infection region. CONCLUSION: The analysis of the time difference between infection and recovery can help predict the epidemic peak due to mass (or normal) infection and can also be used as a time index to prepare medical resources. The Korean Academy of Medical Sciences 2020-08-26 /pmc/articles/PMC7458854/ /pubmed/32864913 http://dx.doi.org/10.3346/jkms.2020.35.e317 Text en © 2020 The Korean Academy of Medical Sciences. https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Bae, Tae Wuk
Kwon, Kee Koo
Kim, Kyu Hyung
Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020
title Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020
title_full Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020
title_fullStr Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020
title_full_unstemmed Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020
title_short Mass Infection Analysis of COVID-19 Using the SEIRD Model in Daegu-Gyeongbuk of Korea from April to May, 2020
title_sort mass infection analysis of covid-19 using the seird model in daegu-gyeongbuk of korea from april to may, 2020
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458854/
https://www.ncbi.nlm.nih.gov/pubmed/32864913
http://dx.doi.org/10.3346/jkms.2020.35.e317
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