The COVID-19 Outbreak Transmission Dynamic Prediction with SIR Model using Runge-Kutta Method
Abstract
The COVID-19 disease has been going on for almost three years since it emerged in December 2019. COVID-19 has become the deadliest contagious virus in the world, and the situation is still serious everywhere. Therefore, accurate epidemic predictions are required to find a suitable and efficient prevention measure. To comprehend the transmission of this disease, this research examines the Susceptible Infected Recovered Model (SIR) using actual data based on Malaysian cases. The 4th order Runge-Kutta method was utilised to formulate and solve differential equations numerically. The model has been studied theoretically and through computer simulations using MATLAB. As a result, the rate of COVID-19 transmission from susceptible to infected will increase the number of affected populations. The pace of recovery of COVID-19 transmission from infected to recovered will result in a decline in infected populations. By observing the data, the COVID-19 outbreak transmission dynamics had a longer incubation period and recovery phase. The 4th order Runge-Kutta numerical method approximates the value depicting the virus's movement or transmission. It may be utilised to investigate numerical solutions in the SIR model and analyse the movement of the COVID-19 outbreak. The described model can be used in other countries, a vital strategy when considering COVID-19 transmission.
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