The global COVID-19 pandemic has severely impacted the passenger flow. Facing the same pandemic, various regions differ in the resilience of population mobility due to differences in the regional cultural. This study uses mobile big data to quantifies regional mobility resilience of 358 cities in China. Study results reveal the differences in regional mobility resilience of cities through spatial autocorrelation analysis, and verify the effects of regional culture on mobility resilience using a panel logit regression model based on pathogen-stress theory. Spatial heterogeneity and autocorrelation in the regional mobility resilience of Chinese cities are identified through spatial analysis, which are manifested by various hot spots over time. Moreover, the panel regression results indicate that the COVID-19 pandemic has a significant negative effect on regional mobility resilience; and that the negative effect of COVID-19 on regional mobility resilience is amplified in the cities with high degrees of dialect diversity, while it is weakened in the cities with high degrees of cultural tightness (which have strict norms and punishments for deviance). This study provides theoretical implications for mobility resilience in the context of COVID-19 and advances the pathogen-stress theory. Study findings also provide practical recommendations for regions to enhance regional mobility resilience under the challenges of future public health crisis events.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772349PMC
http://dx.doi.org/10.1016/j.jclepro.2022.130621DOI Listing

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