TY - JOUR
T1 - Long-Time Analysis of a Time-Dependent SUC Epidemic Model for the COVID-19 Pandemic
AU - Hwang, Youngjin
AU - Kwak, Soobin
AU - Kim, Junseok
N1 - Publisher Copyright:
© 2021 Youngjin Hwang et al.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85118921985&partnerID=8YFLogxK
U2 - 10.1155/2021/5877217
DO - 10.1155/2021/5877217
M3 - Article
C2 - 34745502
AN - SCOPUS:85118921985
SN - 2040-2295
VL - 2021
JO - Journal of Healthcare Engineering
JF - Journal of Healthcare Engineering
M1 - 5877217
ER -