In this research work, we present a mathematical model for novel coronavirus-19 infectious disease which consists of three different compartments: susceptible, infected, and recovered under convex incident rate involving immigration rate. We first derive the formulation of the model. Also, we give some qualitative aspects for the model including existence of equilibriums and its stability results by using various tools of nonlinear analysis. Then, by means of the nonstandard finite difference scheme (NSFD), we simulate the results for the data of Wuhan city against two different sets of values of immigration parameter. By means of simulation, we show how protection, exposure, death, and cure rates affect the susceptible, infected, and recovered population with the passage of time involving immigration. On the basis of simulation, we observe the dynamical behavior due to immigration of susceptible and infected classes or one of these two.

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This paper investigates a new mathematical SQIR model for COVID-19 by means of four dimensions; susceptible, quarantine, infected and recovered (SQIR) via Non-linear Saturated Incidence Rate. First of all the model is formulated in the form of differential equations. Disease-free, endemic equilibriums and Basic Reproduction Number are found for the said model. Local Stability is analyzed through Jacobean Matrix while Lyapunov Function is constructed for the study of Global Stability of the Model. Using nonstandard finite difference method, numerical results are simulated. By Simulation, we mean how protection, exposure, death and cure rates affect the Susceptible, Quarantined, Infected and recovered population with the passage of time.

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