データ同化によるSIR感染方程式の数理解析

抄録

The new coronavirus infection (COVID-19) is rampant. The most troublesome part of this infection are the time between infection and onset and the infectiveness for several days even in the not-onset state. Therefore, a considerable number of infected persons with infectivity are left unchecked. Even if the infection status is simulated by the SIR equation or the like, the true values of the infection parameters and the true number of infected persons cannot be grasped. On the other hand, the daily number of infected people and the cumulative number of infected people are announced. These numbers are not true values, but they reflect the true values. Hence, it will be possible to estimate the true value by combining it with the observation equation. In short, the data assimilation framework is considered to be effective.