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1.
Transp Res Interdiscip Perspect ; 17: 100744, 2023 Jan.
Article in English | MEDLINE | ID: mdl-36590070

ABSTRACT

By the end of 2021, the Omicron variant of coronavirus disease 2019 had become the dominant cause of a worldwide pandemic crisis. This demands a deeper analysis to support policy makers in creating interventions that not only protect people from the pandemic but also remedy its negative effects on the economy. Thus, this study investigated people's mobility changes through the relationship between spatiotemporal population density and urban facilities. Results showed that places related to daily services, restaurants, commercial areas, and offices experienced decreased visits, with the highest decline belonging to commercial facilities. Visits to health care and production facilities were stable on weekdays but increased on holidays. Educational institutions' visits decreased on weekdays but increased on holidays. People's visits to residential housing and open spaces increased, with the rise in residential housing visits being more substantial. The results also confirmed that policy interventions (e.g., declaration of emergency and upgrade of restriction level) have a great impact on people's mobility in the short term. The findings would seem to indicate that visit patterns at service and restaurant places decreased least during the pandemic. The analysis outcomes suggest that policy makers should pay more attention to risk perception enhancement as a long-term measure. Furthermore, the study clarified the population density of each facility type in a time series. Improving model performance would be promising for tracking and predicting the spread of future pandemics.

2.
Transp Res Interdiscip Perspect ; 7: 100212, 2020 Sep.
Article in English | MEDLINE | ID: mdl-34173468

ABSTRACT

At the time of writing, the world is facing the new coronavirus pandemic, which has been declared one of the most dangerous disasters of the 21st century. All nations and communities have applied many countermeasures to control the spread of the epidemic. In terms of countermeasures, lockdowns and reductions of social activities are meant to flatten the curve of infection. Nevertheless, to date, there has been no evaluation of the effectiveness of these methods. Thus, the present study aims to interpret the change in the population density of Sapporo city in the emergency's period declaration using big data obtained from mobile spatial statistics. The results indicate that, in the time of refraining from traveling, the city's residents have been more likely to stay home and less likely to travel to the center area. This has led to a decrease of up to 90% of the population density in crowded areas. The study's outcomes partly explain the statement of reducing 70%-80% of contact between people in line with the purpose of the emergency declaration. Moreover, these findings establish the primary step for further analysis of estimating the efficiency of policy in controlling the epidemic.

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