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Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic

In this study, we propose a time-dependent susceptible-unidentified infected-confirmed (tSUC) epidemic mathematical model for the COVID-19 pandemic, which has a time-dependent transmission parameter. Using the tSUC model with real confirmed data, we can estimate the number of unidentified infected c...

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Detalles Bibliográficos
Autores principales: Hwang, Youngjin, Kwak, Soobin, Kim, Junseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564194/
https://www.ncbi.nlm.nih.gov/pubmed/34745502
http://dx.doi.org/10.1155/2021/5877217
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author Hwang, Youngjin
Kwak, Soobin
Kim, Junseok
author_facet Hwang, Youngjin
Kwak, Soobin
Kim, Junseok
author_sort Hwang, Youngjin
collection PubMed
description In this study, we propose a time-dependent susceptible-unidentified infected-confirmed (tSUC) epidemic mathematical model for the COVID-19 pandemic, which has a time-dependent transmission parameter. Using the tSUC model with real confirmed data, we can estimate the number of unidentified infected cases. We can perform a long-time epidemic analysis from the beginning to the current pandemic of COVID-19 using the time-dependent parameter. To verify the performance of the proposed model, we present several numerical experiments. The computational test results confirm the usefulness of the proposed model in the analysis of the COVID-19 pandemic.
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spelling pubmed-85641942021-11-04 Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic Hwang, Youngjin Kwak, Soobin Kim, Junseok J Healthc Eng Research Article In this study, we propose a time-dependent susceptible-unidentified infected-confirmed (tSUC) epidemic mathematical model for the COVID-19 pandemic, which has a time-dependent transmission parameter. Using the tSUC model with real confirmed data, we can estimate the number of unidentified infected cases. We can perform a long-time epidemic analysis from the beginning to the current pandemic of COVID-19 using the time-dependent parameter. To verify the performance of the proposed model, we present several numerical experiments. The computational test results confirm the usefulness of the proposed model in the analysis of the COVID-19 pandemic. Hindawi 2021-10-28 /pmc/articles/PMC8564194/ /pubmed/34745502 http://dx.doi.org/10.1155/2021/5877217 Text en Copyright © 2021 Youngjin Hwang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hwang, Youngjin
Kwak, Soobin
Kim, Junseok
Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
title Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
title_full Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
title_fullStr Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
title_full_unstemmed Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
title_short Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
title_sort long-time analysis of a time-dependent suc epidemic model for the covid-19 pandemic
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564194/
https://www.ncbi.nlm.nih.gov/pubmed/34745502
http://dx.doi.org/10.1155/2021/5877217
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