This research study demonstrates a numerical model intended for comprehension the COVID-19 spread of the year 2020 by utilizing the improved SIR model. The paper focuses on deceased rates rather than confirmed cases. A model derived from the standard SIR epidemiological model including asymptomatic and hospitalized, is presented, but includes symptomatic and critical states as well, for better simulate real disease dynamics. A three-dimensional nonlinear differential equation is formulated and solved numerically utilizing the Runge-Kutta’s method in MS excel. It appears from the research study that, by looking at the impact of varying people contact rates in populations shown that reducing contact rates by 50%, COVID-19 should be controllable to levels like the seasonal flu. It is additionally indicated numerically that the pandemic can be reduced to a less dangerous level when there are less infected people in contact in the populace.
