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

Youngjin Hwang, Soobin Kwak, Junseok Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Article number5877217
JournalJournal of Healthcare Engineering
Volume2021
DOIs
Publication statusPublished - 2021

ASJC Scopus subject areas

  • Biotechnology
  • Surgery
  • Biomedical Engineering
  • Health Informatics

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