The Resilience of the Interprovincial Population Mobility Network in China? Spatial Reorganization under the Impact of the COVID‐19 Pandemic

ABSTRACT The COVID‐19 pandemic significantly affected population mobility and triggered adaptive shifts in mobility patterns. Using migration data from Gaode Map (2019–2023), this study applies spatiotemporal statistical analyses, social network analysis, and panel fixed‐effects models to systematically examine the spatiotemporal patterns, structural characteristics, and determinants of interprovincial population mobility networks in China before and after the pandemic. The results indicate that the intensity of interprovincial population mobility in China followed an N‐shaped trajectory during the study period, demonstrating notable resilience and recovery. Although the pandemic's impact on the overall strength of the mobility network was temporary, it exacerbated structural heterogeneity within the network, leading to a reconfiguration of degree centrality in several provinces. The study also reveals that the number of confirmed COVID‐19 cases acted as a primary inhibiting factor for mobility, while foreign direct investment (FDI), employment opportunities, nonagricultural industrial structures, educational resources, and natural climate conditions served as significant pull factors. Notably, per capita GDP had a significant negative impact on mobility. These findings offer important theoretical and practical insights into the long‐term effects of major public health events on changes in the geographical characteristics of population distribution and the structure of population mobility networks.