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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Autores principales:	Youngjin Hwang, Soobin Kwak, Junseok Kim
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Medicine (General) R5-920 Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/a7b7d3cb8b9b444c8a5322873275c7dc
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spelling	oai:doaj.org-article:a7b7d3cb8b9b444c8a5322873275c7dc2021-11-08T02:36:52ZLong-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic2040-230910.1155/2021/5877217https://doaj.org/article/a7b7d3cb8b9b444c8a5322873275c7dc2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/5877217https://doaj.org/toc/2040-2309In 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.Youngjin HwangSoobin KwakJunseok KimHindawi LimitedarticleMedicine (General)R5-920Medical technologyR855-855.5ENJournal of Healthcare Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine (General) R5-920 Medical technology R855-855.5
spellingShingle	Medicine (General) R5-920 Medical technology R855-855.5 Youngjin Hwang Soobin Kwak Junseok Kim Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
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	article
author	Youngjin Hwang Soobin Kwak Junseok Kim
author_facet	Youngjin Hwang Soobin Kwak Junseok Kim
author_sort	Youngjin Hwang
title	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_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_sort	long-time analysis of a time-dependent suc epidemic model for the covid-19 pandemic
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/a7b7d3cb8b9b444c8a5322873275c7dc
work_keys_str_mv	AT youngjinhwang longtimeanalysisofatimedependentsucepidemicmodelforthecovid19pandemic AT soobinkwak longtimeanalysisofatimedependentsucepidemicmodelforthecovid19pandemic AT junseokkim longtimeanalysisofatimedependentsucepidemicmodelforthecovid19pandemic
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Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic

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