通过基于代理模型和数据同化分析新冠病毒在东京的传播情况。

Sun Chang, Richard Serge, Miyoshi Takemasa, Tsuzu Naohiro

Data Assimilation Research Team, RIKEN Center for Computational Science (R-CCS), Kobe 650-0047, Japan.

School of Science, Nagoya University, Chikusa-ku, Nagoya 464-8602, Japan.

J Clin Med. 2022 Apr 25;11(9):2401. doi: 10.3390/jcm11092401.

In this paper, we introduce an agent-based model together with a particle filter approach to study the spread of COVID-19. Investigations are mainly performed on the metropolis of Tokyo, but other prefectures of Japan are also briefly surveyed. A novel method for evaluating the effective reproduction number is one of the main outcomes of our approach. Other unknown parameters are also evaluated. Uncertain quantities, such as, for example, the probability that an infected agent develops symptoms, are tested and discussed, and the stability of our computations is examined. Detailed explanations are provided for the model and for the assimilation process.

在本文中，我们引入了一种基于智能体的模型以及一种粒子滤波方法来研究新冠病毒的传播。研究主要针对东京都进行，但也简要调查了日本的其他县。评估有效再生数的一种新方法是我们方法的主要成果之一。还评估了其他未知参数。对诸如感染个体出现症状的概率等不确定量进行了测试和讨论，并检验了我们计算的稳定性。文中对模型和同化过程给出了详细解释。