Decision-making of travel bubble implementation process using metapopulation model
Yang Liu, Shinya Hanaoka, Kashin Sugishita
Abstract
The COVID-19 pandemic has had a tremendous impact on the transportation and tourism sectors. As vaccines were being administered and lockdowns implemented, owing to the significant social and economic impacts, travel bubbles were proposed as a gradual and intermediate open policy to balance risks and economic recovery. However, the travel bubble framework and associated costs and benefits were not well-established during policy implementation. In this study, we propose a travel bubble transportation framework using a metapopulation epidemic and mobility model, and conduct a cost–benefit analysis for the decision-making process during the border reopening phase. Our model focuses on the control of domestic and international long-distance travel inside the bubble to maximize monetary returns derived from tourism benefits and pandemic costs. A sequential decision problem is proposed to make multiple decisions based on real-time observations. We conduct a case study on travel bubbles in Australia, New Zealand, and Japan to test the feasibility of the model. The simulation results show that controlled intra-bubble transportation can generate positive economic benefits while keeping the epidemic within an acceptable range of control. Our framework can assist policymakers in making informed, open decisions by considering multiple attributes during a global pandemic.