Dynamics of COVID-19 Using SEIQR Epidemic Model

• Published in: Journal of mathematics (Hidawi) Vol. 2022; no. 1
• Main Authors: Avinash, N., Britto Antony Xavier, G., Alsinai, Ammar, Ahmed, Hanan, Rexma Sherine, V., Chellamani, P.
• Format: Journal Article
• Language: English
• Published: Cairo Hindawi 2022; Hindawi Limited
• Subjects: Constraint modelling; Coronaviruses; COVID-19; Disease transmission; Dynamic programming; Epidemics; Epidemiology; Infections; Infectious diseases; Mathematical models; Mathematics; Medical research; Optimal control; Optimization; Pandemics; Public health; Severe acute respiratory syndrome coronavirus 2; Social distancing; Viral diseases
• ISSN: 2314-4629; 2314-4785
• DOI: 10.1155/2022/2138165

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.