Covid-19 sir model with nonlinear incidence rate

Abstract Covid-19 is part of worldwide pandemic since early 2020. Various mathematical models have been proposed to understand the behaviour disease, but most them were failed predict biological phenomenon this infectious diseases they use incorrect assumptions due stage symptoms. The aim paper develop a covid-19 model with nonlinear incidence rate. We some logical assumption model. discretize by using Euler method. literature review in our research methodology. Then, we simulate computer software. found that has two equilibrium points, namely disease free point and endemic point. stability changed increament or decreament step-size. If step-size large enough, then it lead numerical solution blown up. Finally, also fair enough case. Also, interesting from simulation effect government policies social distancing. Further work needed analyze delay.