Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation

Chang Sun; Serge Richard; Takemasa Miyoshi; Naohiro Tsuzu

doi:10.3390/jcm11092401

Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation

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

Authors

Chang Sun^{1

2}, Serge Richard^{1

3}, Takemasa Miyoshi^{1

4

5}, Naohiro Tsuzu^{1

3}

Affiliations

¹ Data Assimilation Research Team, RIKEN Center for Computational Science (R-CCS), Kobe 650-0047, Japan.
² School of Science, Nagoya University, Chikusa-ku, Nagoya 464-8602, Japan.
³ Graduate School of Mathematics, Nagoya University, Chikusa-ku, Nagoya 464-8602, Japan.
⁴ Prediction Science Laboratory, RIKEN Cluster for Pioneering Research (CPR), Kobe 650-0047, Japan.
⁵ RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS), Wako 351-0198, Japan.

Abstract

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.

Keywords: COVID-19; agent-based model; data assimilation; effective reproduction number.