A reliable numerical simulation technique for solving COVID-19 model

Abstract

The nature of epidemiological models is characterized by randomness in their coefficients, while the classical or analytical and numerical methods deal with systems with fixed coefficients, which makes these methods inappropriate for solutions of epidemiological systems that have coefficients that change with time. For that, the numerical simulation methods that deal with time change are more appropriate than other ways. The aim of the research is to apply some of these methods to the COVID-19 system. Two efficient methods used for previous studies are used to solve this system, which are Monte Carlo Finite Difference Method and Mean Latin Hypercube Finite Difference Method. For the sake of comparison, a numerical method, the finite difference method, is used to solve this system. We have reached good results that give an analysis and impression of the behavior of the Covid 19 epidemic since its inception and predict its behavior for the next years. All results have been written in graphs and tabulated.