Parameter estimation for a SEIRS model with COVID-19 data of Türkiye

Arzu Unal; Elif Demirci

doi:10.2478/auom-2023-0041

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Parameter estimation for a SEIRS model with COVID-19 data of Türkiye

Analele ştiinţifice ale Universităţii "Ovidius" Constanţa. Seria Matematică

Volume 31 (2023): Issue 3 (September 2023)

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.

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Articles in this issue

DOI: https://doi.org/10.2478/auom-2023-0041 | Journal eISSN: 1844-0835 | Journal ISSN: 1224-1784

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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

Keywords:

Parameter estimation,

Related subjects:

© 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.

Volume 31 (2023): Issue 3 (September 2023)