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Parameter estimation for a SEIRS model with COVID-19 data of Türkiye Cover
By: Arzu Unal and  Elif Demirci  
Open Access
|Oct 2023

Abstract

In this paper, the unknown parameters of a SEIRS mathematical model for the dynamics of COVID-19 are estimated by the least squares approach using data of Trkiye. In the considered model, the infective group is divided into two classes consisting of diagnosed and undiagnosed individuals. Since the data for undiagnosed infective individuals in the community is unknown, three di erent scenarios are proposed. The numerical solutions of the model using the estimated parameter values and the actual data are demonstrated with graphs.

DOI: https://doi.org/10.2478/auom-2023-0041 | Journal eISSN: 1844-0835 | Journal ISSN: 1224-1784
Language: English
Page range: 229 - 244
Submitted on: Sep 25, 2022
Accepted on: Feb 14, 2023
Published on: Oct 21, 2023
Published by: Ovidius University of Constanta
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2023 Arzu Unal, Elif Demirci, published by Ovidius University of Constanta
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.