Modeling and analysis of the spread of the COVID-19 pandemic using the classical SIR model

In this paper modeling, analysis and prediction of novel epidemic of COVID-19 are concerned to identify effective spread parameters of it in Iran. For this purpose, the basic susceptible-infected-removed (SIR) model is used which has two parameters: the infection rate and remove rate. The occurrence of several maximum points in the Iranian data and the single peak of the SIR model makes it impossible to use a model with the same parameters for all times. For this reason, the Iranian data are divided into five time periods and then the parameters of each period are obtained. In addition to adapting to the behavior of disease-related data, these time periods are consistent with the realities of society, including the timing of government decisions and the changing patterns of individuals in society. Finally, an analysis based on the obtained parameters and the trend of disease spread in the continuation of this year is presented. Since the economic,social and health consequences of this virus are catastrophic, using the results of mathematical modeling to identify the factors affecting the spread of the disease can be a step towards future actions to control the disease.