Analyzing COVID-19's impact on the travel mobility of various social groups in China's Greater Bay Area via mobile phone big data.

Abstract

The COVID-19 outbreak has significantly impacted people’s mobility in terms of travel, which is directly related to regional economic vitality and individuals’ well-being. This study conducted research on the COVID-19 epidemic’s impact on travel mobility in China’s Greater Bay Area, utilizing mobile phone big data. The overall influence of COVID-19 was measured by investigating the impact between different income and migration groups in three core cities: Shenzhen, Guangzhou, and Foshan. Individuals’ weekly activity space area and travel frequency were calculated, and the average values between the different cities and various social groups were compared. The results showed that travel mobility declined during the epidemic’s peak, followed by a recovery based on the overall trend. The start and end of strict law enforcement had a significant impact on the initial decline and subsequent recovery of travel mobility in the core cities. COVID-19 had a larger impact on core cities than peripheral areas, and on non-commute travel frequency, compared to commute travel frequency. Compared to advantaged groups, socially disadvantaged groups experienced a steeper decline in travel mobility during the epidemic’s peak, but a more significant recovery afterwards. These findings indicate that discretionary activities have not yet recovered and remain below the pre-epidemic level, and that disadvantaged social groups had limited access to superior precautionary measures for avoiding infection. Based on the findings, we provide several policy suggestions regarding the recovery of travel mobility.