NUMERICAL MODELING OF A NOVEL STOCHASTIC CORONAVIRUS

Abstract

The aim is to study the dynamics of Coronavirus model using stochastic methods. Threshold parameter [Formula: see text] is obtained for the model. Afterwards, both the disease-free equilibrium (DFE) and endemic equilibrium (EE) points are acquired and the stability of the model is discussed. Both the equilibrium points are locally asymptotically stable. Euler–Maruyama, stochastic Euler scheme (SES), stochastic fourth-order Runge–Kutta scheme (SRKS) and stochastic non-standard finite difference technique (SNFDT) are applied to solve the model equations. Euler–Maruyama, SES, SRKS fail for large time step size, while, SNFDT preserves the dynamics of the proposed model for any step size. Numerical comparison of applied methods is provided using different step sizes.