Author
Listed:
- N. Avinash
- G. Britto Antony Xavier
- Ammar Alsinai
- Hanan Ahmed
- V. Rexma Sherine
- P. Chellamani
- Ali Sajid
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.
Suggested Citation
N. Avinash & G. Britto Antony Xavier & Ammar Alsinai & Hanan Ahmed & V. Rexma Sherine & P. Chellamani & Ali Sajid, 2022.
"Dynamics of COVID-19 Using SEIQR Epidemic Model,"
Journal of Mathematics, Hindawi, vol. 2022, pages 1-21, September.
Handle:
RePEc:hin:jjmath:2138165
DOI: 10.1155/2022/2138165
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