<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>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.</p>
</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.

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

Analele ştiinţifice ale Universităţii "Ovidius" Constanţa. Seria Matematică

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Parameter estimation for a SEIRS model with COVID-19 data of Türkiye"}

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...

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

Data publikacji: 21 paź 2023

Zakres stron: 229 - 244

Otrzymano: 25 wrz 2022

Przyjęty: 14 lut 2023

DOI: https://doi.org/10.2478/auom-2023-0041

Słowa kluczowe
Parameter estimation, COVID-19, epidemic model

© 2023 Arzu Unal et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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

Data publikacji: 21 paź 2023

Zakres stron: 229 - 244

Otrzymano: 25 wrz 2022

Przyjęty: 14 lut 2023

DOI: https://doi.org/10.2478/auom-2023-0041

Słowa kluczoweParameter estimation, COVID-19, epidemic model

© 2023 Arzu Unal et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
Parameter estimation, COVID-19, epidemic model