Transactions of the Japanese Society for Artificial Intelligence
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
Short Paper
Estimating Effectiveness of Preventing Measures for 2019 Novel Coronavirus Diseases (COVID-19)
Setsuya Kurahashi
Author information

2020 Volume 35 Issue 3 Pages D-K28_1-8


This paper implements the infection process of 2019 Novel Coronavirus Diseases (COVID-19) in an agentbasedmodel and compares the effectiveness of multiple infection prevention measures. In the model, 1120 virtualresidents agents live in two towns where they commute to office or school and visiting stores. The model simulates aninfection process in which they were exposed to the risk of transmission of the novel coronavirus. The results of theexperiments showed that individual infection prevention measures (commuting, teleworking, class closing, contactrate reduction, staying at home after fever) alone or partially combined them do not produce significant effects. Onthe other hand, if comprehensive measures were taken, it was confirmed that the number of deaths, the infectionrate, and the number of severe hospitalised patients per day were decreased significantly at the median and maximumrespectively.

Information related to the author
© The Japanese Society for Artificial Intelligence 2020
Previous article