COVID-19 Spread Modeling Incorporating Suggestive Optimal Control Strategies under Uncertainty

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P.K. Santra
D. Pal
G.S. Mahapatra
H. Alrabaiah

Abstract

In the present paper, we have provided a five-compartmental epidemic model in an interval environment to analyze the spread of COVID-19 infection in India. The proposed model divides the entire population of India into five classes. They are susceptible, exposed, asymptomatic, symptomatic, and recovered classes. Under some suppositions, the crisp model is constructed and converted to an imprecise model by the interval number. We introduced a parametric functional form of an interval number to study the imprecise epidemiological model. The main objective of this study is to develop an epidemiological model in an imprecise environment and to try to understand the dynamics of the epidemic model of COVID-19 infection spread in India. We also presented the COVID-19 model with two controls to effectively control COVID-19 disease in India. Finally, a numerical simulation is carried out considering that the model parameters are imprecise. The numerical results show that our proposed imprecise model is reliable from a practical point of view.

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How to Cite
Santra, P., Pal, D., Mahapatra, G., & Alrabaiah, H. (2023). COVID-19 Spread Modeling Incorporating Suggestive Optimal Control Strategies under Uncertainty. Advances in Systems Science and Applications, 23(3), 66-90. https://doi.org/10.25728/assa.2023.23.3.1389
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