Dynamics of COVID-19 Using SEIQR Epidemic Model

N. Avinash, G. Britto Antony Xavier, Ammar Alsinai, Hanan Ahmed, V. Rexma Sherine, P. Chellamani and Ali Sajid

Journal of Mathematics, 2022, vol. 2022, 1-21

Abstract: The major goal of this study is to create an optimal technique for managing COVID-19 spread by transforming the SEIQR model into a dynamic (multistage) programming problem with continuous and discrete time-varying transmission rates as optimizing variables. We have developed an optimal control problem for a discrete-time, deterministic susceptible class (S), exposed class (E), infected class (I), quarantined class (Q), and recovered class (R) epidemic with a finite time horizon. The problem involves finding the minimum objective function of a controlled process subject to the constraints of limited resources. For our model, we present a new technique based on dynamic programming problem solutions that can be used to minimize infection rate and maximize recovery rate. We developed suitable conditions for obtaining monotonic solutions and proposed a dynamic programming model to obtain optimal transmission rate sequences. We explored the positivity and unique solvability nature of these implicit and explicit time-discrete models. According to our findings, isolating the affected humans can limit the danger of COVID-19 spreading in the future.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:2138165

DOI: 10.1155/2022/2138165

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