P23M21 | NUMERICAL ANALYSIS OF MODIFIED SIR MODEL FOR COVID-19 DATA USING RUNGE KUTTA METHOD

ABSTRACT COVID-19 has left a huge impact on human livelihoods. Therefore, mathematical modelling has been widely used to observe the spreading of the virus. SIR model is the most common model used to forecast the disease and it can be modified with certain variables to fit the current situation. However, the basic SIR model is not suitable to be used to observe the pattern of the pandemic in long term. Hence, modified SIR model is proposed to overcome the inability of the basic SIR model. Thus, this study was conducted to apply the basic SIR model and the modified SIR model which is the SIRD model and SIRV model to predict the number of infected, number of recovered and number of death on the viral dynamic of COVID-19 and compares them with real data and fit with the model. This study also determines the effect of the basic number of reproduction, R-naught on infected and removed population. The numerical method using the fourth-order Runge-Kutta method is applied to solve the system of ordinary differential equations in the modified SIR models to compute the result for this study. The result shows that the models give approximately similar results in comparing the real data with the fit model. It also reveals that R-naught m ore than1 will have a higher number of infected population compared to R-naught less than1.