On the Homotopy analysis method of MSEIR epidemic model

Ibrahim, M. O.; Raji, I.I.; Aladesuyi, A.; Nwagwo, Alexander

doi:10.9790/4861-06325561

Cited by 2 publications

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“…The system of differential equations for the numbers in the epidemiology classes and the population size is [20].…”

Section: Introductionmentioning

confidence: 99%

On the Differential Fractional Transformation Method of MSEIR Epidemic Model

Asfour¹,

Ibrahim²

2015

IJCA

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In this paper we solve the MSEIR epidemic model by using the differential fractional transformation method. Using the differential Riemann-Liouville and the Caputo fractional derivative; we study convergent of MSEIR epidemic model; we use some theorems of fractional to introduce the solution of MSEIR epidemic Model. Numerical results are provided to confirm the theoretical result and the efficiency of the proposed method. KeywordsCaputo and Riemann-Liouville of fractional; theorems of fractional; we study convergent of MSEIR epidemic Model; MSEIR Model; numerical solutions

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“…The system of differential equations for the numbers in the epidemiology classes and the population size is [20].…”

Section: Introductionmentioning

confidence: 99%

On the Differential Fractional Transformation Method of MSEIR Epidemic Model

Asfour¹,

Ibrahim²

2015

IJCA

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Exploring the Landscape of Fractional-Order Models in Epidemiology: A Comparative Simulation Study

Agarwal,

Airan,

Agarwal

2024

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Mathematical models play a crucial role in evaluating real-life processes qualitatively and quantitatively. They have been extensively employed to study the spread of diseases such as hepatitis B, COVID-19, influenza, and other epidemics. Many researchers have discussed various types of epidemiological models, including deterministic, stochastic, and fractional order models, for this purpose. This article presents a comprehensive review and comparative study of the transmission dynamics of fractional order in epidemiological modeling. A significant portion of the paper is dedicated to the graphical simulation of these models, providing a visual representation of their behavior and characteristics. The article further embarks on a comparative analysis of fractional-order models with their integer-order counterparts. This comparison sheds light on the nuances and subtleties that differentiate these models, thereby offering valuable insights into their respective strengths and limitations. The paper also explores time delay models, non-linear incidence rate models, and stochastic models, explaining their use and significance in epidemiology. It includes studies and models that focus on the transmission dynamics of diseases using fractional order models, as well as comparisons with integer-order models. The findings from this study contribute to the broader understanding of epidemiological modeling, paving the way for more accurate and effective strategies in disease control and prevention.

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On the Homotopy analysis method of MSEIR epidemic model

Abstract: Abstract:We considered an MSEIR epidemic model as proposed by Hethcote (2000). Homotopy analysis method is used to solve the problem because of its advantages over methods.

Cited by 2 publications

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On the Differential Fractional Transformation Method of MSEIR Epidemic Model

On the Differential Fractional Transformation Method of MSEIR Epidemic Model

Exploring the Landscape of Fractional-Order Models in Epidemiology: A Comparative Simulation Study

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