Multiagent model simulation : Prevention of infection in tourist destinations

Research and Development by

Setsuya KURAHASHI, University of Tsukuba

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

Evaluating the effects of pubs, events and telework restrictions in Tokyo

■Evaluating the effect of emergency declarations using the individual-based model and the SEIR model

Restricting restaurants, large-scale events and teleworking (Individual-based model)

Projected number of new patients (Machine learning+SEIR model)

  • Estimated the reproduction rate when restricting restaurants, large-scale events, and teleworking(A)
  • SEIR model incorporating the flowing population in Tokyo and machine learning to optimize the model (B) (error 1.28 ppl/day).
  • Predicted results on Jan. 7 when restaurants hours are reduced by 25-50%, event restrictions* of up to 5,000 and 50% capacity, and 70% teleworking**: 1,100 with restaurants restrictions (C1), 860 with integrated measures (C2).

*14 venues, including the National Stadium, are restricted to 5,000 people, and 124 venues with a capacity of 1,000 people or more are restricted to 50%.
**Effect of strengthening 40% implementation to 70%.

→Restrictions on restaurants will be effective with a 50% reduction, but not enough to lift the declaration after one month. Comprehensive measures are needed, including restrictions on events and teleworking.