The Impact of the COVID-19 Epidemic on the Structural Resilience of Urban and Town Population Flow Networks: An Empirical Study of the Nanjing Metropolitan Area with Urbanization

This study explores the trend of urban spatial networking driven by information technology transformation and regional economic rise, with a particular focus on the role of resilience in urban network structures in responding to risk disturbances. Scholars worldwide have developed a framework for urban network analysis based on transportation, enterprise, and population flow networks. Building on this framework, research has begun to focus on network resilience, emphasizing how networks maintain functional stability through self-adjustment and continuous development when faced with external shocks. The COVID-19 pandemic, as a global event, has profoundly affected societies and economies, particularly in terms of population mobility. Studies conducted during the pandemic have noted significant changes in population flows between Chinese cities, with residents opting for shorter, dispersed travel. However, the resilience of intraregional population flow networks during the post-pandemic period remains underexplored, providing a vital opportunity for supplementary research. Specifically, it is crucial to identify and understand the core nodes essential for supporting network resilience to guide safer urban development. Metropolitan areas are key hubs for regional resource coordination, and interactions among towns within these areas are crucial for coordinated regional development. Towns should form resilient connections and interaction paths, notably by harnessing the capacities of small towns to handle diverse risks. Dynamic changes within metropolitan areas are particularly noteworthy because urban functions are complex and exchanges are stable, enabling a certain level of recovery after risk disturbances. In contrast, townships may exacerbate the "siphon effect" due to their agricultural roles and population structures. This study examines the Nanjing Metropolitan Area as a typical case, leveraging mobile signaling data to quantitatively analyze the structural resilience of population flow networks before and during the pandemic in 2019 and 2021, respectively. The findings indicate that although the pandemic did not directly reduce overall population movement, it altered network hierarchy and spatial distribution, concentrating flows toward urban centers and reducing cross-boundary and long-distance connections. The leisure flow network exhibits greater volatility than the employment flow network, with the latter exhibiting stronger periodicity and stability. High-centrality cross-boundary nodes play a critical role in maintaining safe network operations. If these nodes fail, network density and stability decrease significantly, highlighting their importance for resilient urban construction.