摘要
The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years.Mortality rates are rising rapidly as approved drugs are not yet available.Isolation from the infected person or community is the preferred choice to protect our health.Since humans are the only carriers,it might be possible to control the positive rate if the infected population or host carriers are isolated from each other.Isolation alone may not be a proper 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 pre-sented an optimal control model for COVID-19 using granular differentiability based on fuzzy dynamical systems.In the first step,we created a fuzzy Susceptible-Exposed-Infected-Asymptomatic-Hospitalized-Recovered-Death(SEIAHRD)model for COVID-19,analyzed it using granular differentiability,and reported disease dynamics for time-independent disease control parameters.In the second step,we upgraded the fuzzy dynamical system and granular differentiability model related to time-dependent disease control parameters as an optimal control problem invader.Theoretical studies have been validated with some practical data from the epidemic COVID-19 related to the Indian perspective during first wave and early second wave.
