Multiagent model simulation : Measures to prevent 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

Individual-based simulation of evaluating the impact of regular influx of infected people into tourist destination on community medicine (Using 1/5-size model of Myoko city’s demographics, evaluated risk in a scenario that influx of one infected person each week into the city.)

The diagram highlights that one infected person moving each week results in an average of 3.7 times (up to 6.5 times) more severe cases of illness than the cancellation of tourism.

The following measures can reduce it up to 1.3 times (up to 1.6 times)

  • 80% use of contact tracking app
  • Bi-weekly virus testing for high-risk tourism staff
  • 75% reduction in senior citizen interactions

Influx of one infected person each week causes more than 3 times the number of critically ill beds, but can be reduced up to 1.3 times through contact tracking app, high-risk person testing, and elderly protection.

Courtesy of University of Tsukuba