Dynamic analysis on the epidemic model of infectious diseases using a powerful computational method

S. Mohsenian, S. E. Ghasemi, Sina Gouran and Ali Zolfagharian
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S. Mohsenian: Department of Mechanical Engineering, University of Akron, Akron, OH, USA
S. E. Ghasemi: ��Department of Engineering Sciences, Hakim Sabzevari University, Sabzevar, Iran
Sina Gouran: ��School of Mechanical Engineering, Babol University of Technology, Babol, Iran
Ali Zolfagharian: �School of Engineering, Deakin University, Geelong 3216, Australia

International Journal of Modern Physics C (IJMPC), 2022, vol. 33, issue 06, 1-17

Abstract: In this research, a convenient and effective semi-analytical technique namely the Differential Transformation Method (DTM) is employed to investigate the nonlinear epidemic model. The design of the mathematical model is explained according to five classifications of susceptible, exposed, infective, asymptomatic and recovered people. The corresponding solution points are validated against numerical outcomes. The results reveal a high degree of accuracy for DTM combination with Padé approximation. Moreover, this technique is a promising method to solve various nonlinear equations applicable for epidemic models. The results indicate that by increasing R parameter, the values of infected individuals are enhanced. Also, it can be concluded that increasing in γ parameter leads to increase of recovered profile.

Keywords: Epidemic model; infectious diseases; computational study; nonlinear equation; differential transformation method (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0129183122500838

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