Agent-based simulation of COVID-19 infection cluster and its suppression with contact-trace application

Research and Development by

Nobuyasu Ito, RIKEN

Corresponding Research Area

Simulation and designing countermeasures against possible COVID-19 resurgence: predicting spreading of infection, estimating and verifying the effectiveness of countermeasures, and predicting deman

  • Proposal: Use of the contact-trace application COCOA better be forced in places where the infection probability is assumed to be high.
  • Grounds: Use of the contact-trace application decreases the effective reproduction number in agent-based simulations of the infection-cluster dynamics. And, visualization of rich contact with positive persons will help to acquire new safe lifestyle with COVID-19.
  • Present state: So-called the GOTO policies stimulating the destroyed economy are expected not to expand the infection with sufficient prevention of infection, but in reality, infection risk is invisible and normal bias tends to relax the prevention. On the other hand, many research concluded use of the contact-trace application will slow down infection spread. Users of the contact-trace application get benefit of good infection control both to themselves and to close peoples, but its diffusion rate is staying low. Some strong incentive to use it is expected to stop the infection.
  • Example of policies: 
    • The COCOA should be used when ones participate in the GOTO Travel, GOTO Eat, theaters, concerts, sports viewing, and other events.
    • The COCOA should be used in public transportation.
    • Discount campaign for smartphone using the COCOA.

Suppression of infection using contact-trace application: results of agent-based simulations