Infection Diffusion Analysis based on Human Behavior Model and Infection Diffusion Network

Abstract

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.