https://doi.org/10.1140/epjds/s13688-026-00622-9
Research
Spatiotemporal dynamics of human mobility after lifting of COVID-19 control measures in China: evidence from Nanjing City’s Spring Festival
Department of Geographic Information Science, School of Geography and Ocean Science, Nanjing University, 210023, Nanjing, Jiangsu Province, P.R. China
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Received:
3
September
2025
Accepted:
14
January
2026
Published online:
21
January
2026
Abstract
The COVID-19 pandemic profoundly disrupted urban mobility. To ensure sustainable urban governance, it is essential to understand the behavioral changes following the lifting of COVID-19 control measures in China, although few studies have examined this. This study examines people’s movement and lifestyle patterns, network structure, activity sequences, and sightseeing behavior during the 2023 Spring Festival in Nanjing, using the same period in 2024 as a post-recovery baseline. First, key mobility indicators are analyzed for the entire period. Complex network analysis is then applied to examine urban flow during the 15-day homecoming phase. Spatiotemporal clustering is used to reveal travel patterns at the Chinese New Year’s Eve. Finally, Markov models and travel chain analysis are applied to characterize visitor behavior during the Lantern Festival. Travel distances in 2023 showed partial recovery, reducing the gap with 2024 to 26.85%, while dwell durations remained largely constrained. Despite a 32.31% lower total flow in 2023, the overall population flow network structure was similar in both years. In 2023, nighttime travel on New Year’s Eve involved more stops, shorter distances, and shorter durations at destinations than in 2024. Lantern Festival attendance was higher in 2023 than in 2024, likely reflecting the release of previously suppressed social and recreational demand. This study analyzes changes in mobility through a multi-scale analytical framework, introduces a novel scalable tool for analyzing large-scale travel data, and provides empirical insights for considering comprehensive urban operation optimization strategies, thereby contributing to sustainable urban governance.
Key words: COVID-19 / Human mobility / Urban spatial analysis / Spatiotemporal clustering / Tourism pattern
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1140/epjds/s13688-026-00622-9.
Handling Editor: Sabrina Gaito
© The Author(s) 2026
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