Estimating Effectiveness of Preventing Measures for 2019 Novel Coronavirus Diseases (COVID-19)

• Published in: Transactions of the Japanese Society for Artificial Intelligence Vol. 35; no. 3; pp. D-K28_1 - 8
• Main Author: Kurahashi, Setsuya
• Format: Journal Article
• Language: Japanese
• Published: Tokyo The Japanese Society for Artificial Intelligence 01.05.2020; Japan Science and Technology Agency
• Subjects: 2019 Novel Coronavirus Diseases; agent-based model; Computer simulation; Coronaviruses; COVID-19; Disease transmission; Infections; infectious disease; preventing measures; Viral diseases
• ISSN: 1346-0714; 1346-8030; 1346-8030
• DOI: 10.1527/tjsai.D-K28

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.