Covid-19 sir model with nonlinear incidence rate

Abstract

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