A Fuzzy Dynamic Optimal Model for COVID-19 Epidemic in India Based on Granular Differentiability

15 Pages Posted: 16 Jun 2020

See all articles by Debnarayan Khatua

Debnarayan Khatua

Global Institute of Science and Technology

Anupam De

Haldia Institute of Technology; National Institute of Technology Durgapur

Samarjit Kar

National Institute of Technology (NIT), Durgapur

Soumyadeep Samonto

Global Institute of Science and Technology, Haldia; MAKAUT, WB

Arif Ahmed Seikh

University of Tromsø - The Arctic University of Norway

Debashree Guha

IIT Kharagpur

Date Written: June 7, 2020

Abstract

The pandemic SARS-CoV-2 has become an undying virus to spread sustainable disease named COVID-19 for upcoming few years. The mortality rate of the disease is increasing rapidly as the approved drug is not available yet. Isolation from the infected individual or community is the recommended choice to save our existence. As the human is the only carrier so in that case if the host carriers are isolated from each other then it might be possible to control the spread or positive rates of infected population. Whereas only isolation might not be the only recommended solution. These are the resolutions of previous research work carried out on COVID-19 throughout the world. The present scenario of the world and public health is knocking hard with a big question of critical uncertainty of COVID-19 because of its imprecise database as per daily positive cases recorded all over the world and in India as well. In this research work we have presented an optimal control model for COVID-19 by using fuzzy dynamical system based granular differentiability. In the first step, we have formulated the fuzzy SEIAHRD model for COVID-19, analysed using granular differentiability and reported the disease dynamics for time independent disease control parameter. In the second step, we have upgraded the concerned fuzzy dynamical system and granular differentiability model up to an optimal control problem invader with time dependent control parameter. The theoretical findings are validated graphically with some realistic data for pandemic COVID-19 with respect to India’s perspective.

Note: Funding: None to declare

Declaration of Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Keywords: COVID-19, Asymptomatic, Susceptible, Fuzzy dynamical system, Granular(gr) differentiability

Suggested Citation

Khatua, Debnarayan and De, Anupam and Kar, Samarjit and Samanta, Eshan and Seikh, Arif Ahmed and Guha, Debashree, A Fuzzy Dynamic Optimal Model for COVID-19 Epidemic in India Based on Granular Differentiability (June 7, 2020). Available at SSRN: https://ssrn.com/abstract=3621640 or http://dx.doi.org/10.2139/ssrn.3621640

Debnarayan Khatua

Global Institute of Science and Technology ( email )

ICARE Complex
Hatiberia
Haldia
India

Anupam De

Haldia Institute of Technology ( email )

Dept. of Applied Sciences
P.O.-Hatiberia, Haldia
Haldia, West Bengal 721657
India

National Institute of Technology Durgapur

Dept. of Mathematics
Mahatma Gandhi Avenue
Durgapur, West Bengal 713209
India

Samarjit Kar

National Institute of Technology (NIT), Durgapur ( email )

M.G. Avenue
West Bengal
Durgapur, West Bengal 713209
India

Eshan Samanta (Contact Author)

Global Institute of Science and Technology, Haldia ( email )

ICARE Complex
Hatiberia
Haldia
India

MAKAUT, WB ( email )

India

Arif Ahmed Seikh

University of Tromsø - The Arctic University of Norway ( email )

UiT Norges arktiske universitet
Postboks 6050 Langnes
Tromsø, 9037
Norway

Debashree Guha

IIT Kharagpur ( email )

Kharagpur
IIT Khragpur
Kharagpur, IN West Bengal 721302
India

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