Dynamics of SEIR epidemic model by optimal auxiliary functions method. (June 2021)

• Record Type: Journal Article
• Authors: Marinca, Bogdan; Marinca, Vasile; Bogdan, Ciprian
• Is Part Of: Chaos, solitons and fractals. Volume 147(2021)
• Publication Date: 2021-06
• Subjects: Novel coronavirus -- Approximate solutions -- Epidemics SEIR model -- Optimal auxiliary function method; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2021.110949
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: Our procedure is based on the involvement of the convergence-control parameters via auxiliary functions. The parameters are determined by rigorous mathematical procedure. The domain is three month - a large domain, enough for clear understanding of the novel coronavirus. Optimal Auxiliary Functions Method (OAFM) is effective and rapidly convergent after only one iteration. OAFM lead to a high precission comparing our results with numerical results. Abstract: The aim of the present work is to establish an approximate analytical solution for the nonlinear Susceptible, Exposed, Infected, Recovered (SEIR) model applied to novel coronavirus COVID-19. The mathematical model depending of five nonlinear differential equations, is studied and approximate solutions are obtained using Optimal Auxiliary Functions Method (OAFM). Our technique ensures a fast convergence of the solutions after only one iteration. The nonstandard part of OAFM is described by the presence of so-called auxiliary functions and of the optimal convergence-control parameters. We have a great freedom to select the auxiliary functions and the number of optimal convergence-control parameters which are optimally determined. Our approach is independent of the presence of small or large parameters in the governing equations or in the initial/boundary conditions, is effective, simple and very efficient.