The forecasting of COVID-19 with mortality using SIRD epidemic model for the United States, Russia, China, and the Syrian Arab Republic

In this paper, we apply an algorithm for simulating the susceptible-infected-recovered-dead pandemic model for demonstrating the forecasting and the spreading of the new coronavirus disease. For this purpose, we apply an implicit analytical solution for parts of the model, in addition to applying the finite difference methods for other parts of the model. Based on the collected data of the number of infected cases, recovered cases, and deceased cases of the new coronavirus pandemic as of 30 May 2020, we find the values of the coefficient of infection, the coefficient of recovery, and the coefficient of mortality of the new coronavirus pandemic for four different countries, namely, China, the United States, Russia, and the Syrian Arab Republic. Besides, we find the ratio of the average rate of recovery to the average rate of death of the new coronavirus pandemic for the same four countries. For the following months, we predict the number of the infected cases, the recovered cases, and the deceased cases of the pandemic for the United States, Russia, and the Syrian Arab Republic using the methods normally used for the epidemic model. We find that the number of infected cases of the new coronavirus disease may increase to about two million cases in the United States, about eight hundred thousand cases in Russia, and about three hundred cases in the Syrian Arab Republic. We believe that the algorithm we use for simulating the spreading and the forecasting of the new coronavirus disease can be applied for finding other related coefficients of the pandemic such as the basic reproduction numbers with a certain population.