Forecast on Covid-19 cases in Malaysia using SIRS model and Adams predictor-corrector method

Abstract

A new severe acute respiratory syndrome coronavirus 2 had become a significant threat to public health by 2020. The pandemic began in a city named Wuhan in China. It then spread throughout the rest of the world, including Malaysia. COVID-19 virus can spread between people in close contact because it spreads through droplets in the air. The virus can spread in small liquid particles from an infected person's mouth or nose when they cough, sneeze, speak, sing, or breathe. To reduce the number of cases in the nation, the Malaysian government created a new order named Movement Control Order (MCO). This paper presents a SIRS model to forecast the COVID-19 cases 100 days after the MCO held in Malaysia. MCO's impact was thought to have the potential to reduce COVID-19 cases. The model then generated a system of differential equations for the calculation proposed. 4-Step AdamsBashforth-Moulton Predictor-Corrector method is used to predict the early COVID-19 outbreak in Malaysia. The number of corrector steps will be determined by the tolerance value. Then, the result from the numerical model using various step sizes is compared with the actual data. The outcome of a computer simulation in which the computation and graphing were done using MATLAB. The numerical method's performance in performing the early COVID-19 outbreak in Malaysia is discussed in terms of mean absolute percentage error (MAPE) and standard deviation absolute percentage error. The simulation results indicate that the computation should only use two corrector steps to optimize the forecast and computational time, regardless of the value of step size.