COVID-19 Outbreak with Fuzzy Uncertainties: A Mathematical Perspective

Authors

  • Prasenjit Mahato Department of Mathematics, Sidho-Kanho-Birsha University, India
  • Sanat Kumar Mahato Department of Mathematics, Sidho-Kanho-Birsha University, India https://orcid.org/0000-0001-5455-5173
  • Subhashis Das Department of Mathematics, Sidho-Kanho-Birsha University, India https://orcid.org/0000-0002-4273-7241

DOI:

https://doi.org/10.47852/bonviewJCCE2202236

Keywords:

COVID-19 virus, triangular fuzzy number, utility function method, optimal control

Abstract

In this article, we design a mathematical SEQAIMR (susceptible, exposed, quarantined, asymptomatic, symptomatic, isolated, recovered) epidemic model and investigate the nature of the system. We transform the crisp model into the fuzzy model. All the biological parameters are treated as triangular fuzzy numbers (TFNs). With the help of utility function method, the fuzzy model is defuzzified. We use the MATLAB codes to solve the system of equations and to predict different situations under different values of the control parameters. Lastly, optimal control for COVID-19 disease is explained.

 

Received: 30 April 2022 | Revised: 4 July 2022 | Accepted: 13 July 2022

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

 

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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Published

2022-07-16

How to Cite

Mahato, P., Mahato, S. K., & Das, S. (2022). COVID-19 Outbreak with Fuzzy Uncertainties: A Mathematical Perspective. Journal of Computational and Cognitive Engineering, 3(1), 43–57. https://doi.org/10.47852/bonviewJCCE2202236

Issue

Vol. 3 No. 1 (2024)

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.