Data-driven Simulation for Reducing COVID-19 Epidemic Spreads and Data Quality

Abstract

　This article discusses how to reduce the infection rate for COVID-19 infectious disease with a reduction target. To do so, we need to set an adequate quantitative target estimated from a numerical simulation. This article introduces the method for estimating the reduction target from numerical simulation based on a delayed stochastic SIR model. Furthermore, the method to estimate potential time when we can be active in outside in order to reduce the infection rate for COVID-19.The data quality and data portability required for meaningfully preventing infectious spread are also mentioned.