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

Youngjin Hwang | Zendy; Soobin Kwak | Zendy; Junseok Kim | Zendy

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

Author(s) -

Youngjin Hwang,

Soobin Kwak,

Junseok Kim

Publication year - 2021

Publication title -

journal of healthcare engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.509

H-Index - 29

eISSN - 2040-2309

pISSN - 2040-2295

DOI - 10.1155/2021/5877217

Subject(s) - covid-19 , pandemic , epidemic model , transmission (telecommunications) , virology , computer science , statistics , mathematics , medicine , infectious disease (medical specialty) , disease , population , environmental health , telecommunications , pathology , outbreak

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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