Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
102 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Effectiveness of the COVID-19 Contact-Confirming Application (COCOA) based on a Multi Agent Simulation (2008.13166v1)

Published 30 Aug 2020 in cs.CY and cs.MA

Abstract: As of Aug. 2020, coronavirus disease 2019 (COVID-19) is still spreading in the world. In Japan, the Ministry of Health, Labor, and Welfare developed "COVID-19 Contact-Confirming Application (COCOA)," which was released on Jun. 19, 2020. By utilizing COCOA, users can know whether or not they had contact with infected persons. If those who had contact with infectors keep staying at home, they may not infect those outside. However, effectiveness decreasing the number of infectors depending on the app's various usage parameters is not clear. If it is clear, we could set the objective value of the app's usage parameters (e.g., the usage rate of the total populations) and call for installation of the app. Therefore, we develop a multi-agent simulator that can express COVID-19 spreading and usage of the apps, such as COCOA. In this study, we describe the simulator and the effectiveness of the app in various scenarios. The result obtained in this study supports those of previously conducted studies.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Yuto Omae (8 papers)
  2. Jun Toyotani (4 papers)
  3. Kazuyuki Hara (8 papers)
  4. Yasuhiro Gon (2 papers)
  5. Hirotaka Takahashi (23 papers)
Citations (3)