Concerns about the risk of infection spread due to the activation of domestic travel
・Increased cross-regional travel increases the introduction of viruses between regions (direct effect)
・Travelers have more opportunities to eat out, so the activation of travel increases high-risk contact (direct and indirect effects)
・The implementation of GoTo Travel campaign will spread the mood of lifting the restriction on going out, and increase the number of outings that are not related to travel (indirect effect)
Indirect effects matter
・Indirect effects present problems:
・How much does GoTo Travel campaign increase high-risk contact?
・How much does incremental high-risk contact contribute to the spread of infections?
・Indirect effects are difficult to estimate
・Indirect effects of the Olympics: Unknown and without indication
・Effects of implementing GoTo Travel campaign for the second time: Can we use the data from the first implementation as an indication?
・Data on purchasing activities and human flow
・Location information data provided by DOCOMO (80 million units)
・"JCB Consumption NOW" provided by Nowcast/JCB (10 million people)
Fixed-point observation
・Fixed-point observations of human flow at tourist sites show that human flow has returned to about 80% of the normal level.
・However, the data does not provide details such as where the visitors came from.
Monthly change in the number of observations
・In many locations, human flow is about 1.1-1.2 times as large as in the lowest months, even in peak months
Where major tourist sites visitors came from (2019)
・For each tourist site, the percentage of people who came from a different prefecture was calculated.
・It was shown that among tourist sites, the characteristics varied greatly.
Percentage of visitors (monthly change)
・The percentage of change in the monthly rate of visitors from other prefectures tends to be higher for tourist sites where many people come from other prefectures.
Travel patterns among 47 prefectures
Great variation depending on the observed facility
Travel patterns among prefectures (2019)
・The data on travel patterns between prefectures suggests that measures taken at each facility may affect people’s travel patterns.
"Source: Nowcast/JCB"
The graphs plot where people came from (vertical axis) and the destinations (horizontal axis).
Travel patterns among prefectures (2020)
"Source: Nowcast/JCB"
The graphs plot where people came from (vertical axis) and the destinations (horizontal axis).
Travel patterns between prefectures (2021)
"Source: Nowcast/JCB"
The graphs plot where people came from (vertical axis) and the destinations (horizontal axis).
Tokyo
・We plotted the linkage between accommodation and eating/drinking.
・It was suggested that travelers’ eating and drinking at izakaya restaurants may not be recovering.
In the izakaya restaurants sector, it is shown that the recovery of visitors from outside the Tokyo metropolitan area may not be as advanced as in the accommodation sector.
"Source: Nowcast/JCB"
Osaka
・The trend was similar to that of Tokyo, suggesting that travelers’ eating and drinking in izakaya restaurants may not be recovering.
"Source: Nowcast/JCB"
Hypotheses from the data
・The effect of the announcement of GoTo campaign is suggested for both accommodation and eating/drinking at izakaya restaurants
・The number of restaurants customers from long-distance areas have not recovered as much as those for overnight travelers
・Travelers may refrain from eating out while traveling
・In a phase of increased social activity, the restaurant industry in the prefecture may recover soon?
・Easy outings that require no planning
・Suggesting that there are “indirect effects”
・Effects vary among different regions
・Restaurant types other than “izakaya” are needed
