On Dynamical Analysis of the Data-Driven SIR model (COVID-19 Outbreak in Indonesia)

An archipelago country such as Indonesia has a different beginning of the outbreak, therefore the management of epidemics not uniform. For this reason, the results in the data of confirmed cases COVID-19 to fluctuate and difficult to predict. We use the data-driven SIR model to analyze the dynamics and behavior of the evolution of the disease. We run the data-driven SIR model gradually and found that there are shifting of the peak and the distance of saturation point. We found that a transmission acceleration of the outbreak occurring in Indonesia where it could be seen from increasing of the time the saturation and the confirmed cases. It is finally argued that a new parameter can be used to guidance the condition when the new normal begins.