[3I1-GS-5d] エージェント：社会問題解決

[3I1-GS-5d-04] Infection Diffusion Analysis based on Human Behavior Model and Infection Diffusion Network

〇Satoshi Kurihara¹, Fumito Ihara¹, Daiki Kishimoto¹, Naoto Yoshida² (1. Faculty of Science and Technology, Keio University, 2. Graduate School of Science and Technology, Keio University)

Keywords:Infection Diffusion Simulation, Social Network Analysis, Infection Model

In order to understand and predict the spread of COVID-19 infection, we analyzed tweets and TV news programs concerning about COVID-19. We then simulated the spread of COVID-19 infection diffusion by using our proposed extended SERI model, consisted on a power-law based human behavior model and human movement network constructed as a small world network structure. As a result, we found that it was possible to reproduce the COVID-19 infection situation from last year in Japan. In this paper, we also discuss the effect of the emergency declaration and its lifting time, as well as the effect of vaccination rate and method of consumption.