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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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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. |
format | Online Article Text |
id | pubmed-8564194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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