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Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
Youngjin Hwang1, Soobin Kwak1, Junseok Kim1
1Department of Mathematics, Korea University, Seoul 02841, Republic of Korea.
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.
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