A study on the fractional-order COVID-19 SEIQR model and parameter analysis using homotopy perturbation method

In this article, we present a fractional-order susceptible-exposed-infected-quarantine-recovered (SEIQR) model to analyze the dynamics of the COVID-19 pandemic. The model includes susceptible ( S ), exposed ( E ), infected ( I ), quarantined ( Q ), and recovered ( R ) populations and uses a fractional-order differential equation to provide a further accurate representation of the disease's progression. We employ the homotopy perturbation method (HPM) to derive analytical solutions and the Runge-Kutta fourth-order (RK4) method to obtain numerical solutions. The results indicate that the fractional-order model, particularly for a fractional parameter α = 0.40, provides better accuracy and stability compared to the classical integer-order model. This study highlights the importance of fractional-order modeling in understanding the spread of COVID-19 and suggests its potential application in predicting and controlling future epidemics.

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Publication Details

Journal
Partial Differential Equations in Applied Mathematics
Published
2024-10-10
DOI
https://doi.org/10.1016/j.padiff.2024.100960
Citations
5
Primary Topic
Fractional Differential Equations Solutions
Type
article
Field-Weighted Citation Impact
1.98
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article

A study on the fractional-order COVID-19 SEIQR model and parameter analysis using homotopy perturbation method

Mominul Islam, M. Ali Akbar
5 citations
Partial Differential Equations in Applied Mathematics
Fractional Differential Equations Solutions
1.98
article

A study on the fractional-order COVID-19 SEIQR model and parameter analysis using homotopy perturbation method

Mominul Islam, M. Ali Akbar
article en
5 citations

Abstract

In this article, we present a fractional-order susceptible-exposed-infected-quarantine-recovered (SEIQR) model to analyze the dynamics of the COVID-19 pandemic. The model includes susceptible ( S ), exposed ( E ), infected ( I ), quarantined ( Q ), and recovered ( R ) populations and uses a fractional-order differential equation to provide a further accurate representation of the disease's progression. We employ the homotopy perturbation method (HPM) to derive analytical solutions and the Runge-Kutta fourth-order (RK4) method to obtain numerical solutions. The results indicate that the fractional-order model, particularly for a fractional parameter α = 0.40, provides better accuracy and stability compared to the classical integer-order model. This study highlights the importance of fractional-order modeling in understanding the spread of COVID-19 and suggests its potential application in predicting and controlling future epidemics.

Partial Differential Equations in Applied MathematicsVol. 12
University of Rajshahi (BD)
Climate action
Openalex Percentile: Top 14%
Fractional Differential Equations Solutions
1.98
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