Changes in mobility amid the COVID-19 pandemic in Sapporo City, Japan: An investigation through the relationship between spatiotemporal population density and urban facilities

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.

Keywords: COVID-19; Mobile spatial statistics; Population density; Sapporo; Urban facility; Urban mobility.

Fig. 1

COVID-19 pandemic progress in Sapporo City(Source: DATA-SMART City Sapporo https://ckan.pf-sapporo.jp/dataset/covid_19_patients).

Fig. 2

Distribution of the city’s population at specific times.

Fig. 3

Residential housing and commercial floor area distribution.

Fig. 4

Adjusted R-squared and median p-values for each hour.

Fig. 5

Variation of median standardized coefficients in a day.

Fig. 6

Standardized coefficients at 0000.

Fig. 7

Standardized coefficients at 0800.

Fig. 8

Standardized coefficients at 1600.