Infectious Disease Spread Analysis Using Stochastic Differential Equations for SIR Model

Pandemic simulation is considered to be crucial as a scenario simulation and it is performed by many kinds of methods; the classical ordinary differential models (SIR model), agent-based models, internet-based models, and etc are among them. The SIR model is one of the fundamental methods to see the behavior of the pandemic with easy computation. However, there are no stochastic variation in the equations. The stochastic differential equations (SDE) can provide such kind of variations. Although the SDE are applied to many fields such as economics, less attention has been paid to the SIR simulations. In this paper, we propose a SDE version of the SIR simulation model with application to SARS (Severe Acute Respiratory Syndrome) case in 2003 in Hong Kong.