Dynamics of Caputo Fractional Order SEIRV Epidemic Model with Optimal Control and Stability Analysis

• Published in: International journal of applied and computational mathematics Vol. 8; no. 1; p. 28
• Main Authors: Mahata, Animesh, Paul, Subrata, Mukherjee, Supriya, Das, Meghadri, Roy, Banamali
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.01.2022; Springer Nature B.V
• Subjects: Applications of Mathematics; Applied mathematics; Computational mathematics; Computational Science and Engineering; Control stability; Coronaviruses; COVID-19; Disease control; Disease transmission; Epidemics; Mathematical and Computational Physics; Mathematical Modeling and Industrial Mathematics; Mathematical models; Mathematics; Mathematics and Statistics; Nuclear Energy; Operations Research/Decision Theory; Optimal control; Optimization; Original Paper; Public health; Stability analysis; Theoretical; SEIRV model; Numerical simulation; Stability analysis; Adam-bashforth-moulton predictor–corrector scheme; Optimal control
• ISSN: 2349-5103; 2199-5796; 2199-5796
• DOI: 10.1007/s40819-021-01224-x

In mid-March 2020, the World Health Organization declared COVID-19, a worldwide public health emergency. This paper presents a study of an SEIRV epidemic model with optimal control in the context of the Caputo fractional derivative of order 0 < ν ≤ 1 . The stability analysis of the model is performed. We also present an optimum control scheme for an SEIRV model. The real time data for India COVID-19 cases have been used to determine the parameters of the fractional order SEIRV model. The Adam-Bashforth-Moulton predictor–corrector method is implemented to solve the SEIRV model numerically. For analyzing COVID-19 transmission dynamics, the fractional order of the SEIRV model is found to be better than the integral order. Graphical demonstration and numerical simulations are presented using MATLAB (2018a) software.