Changes in spatiotemporal pattern and network characteristics in population migration of China's cities before and after COVID-19

This paper analyzes the spatiotemporal patterns and structural characteristics of population mobility in Chinese cities before and after the COVID-19 pandemic using Baidu Migration Big Data from 2019 to 2023. The study finds significant temporal and spatial differences in the pandemic's impact, with stronger shocks on mid-sized migration cities. Population migration proved robust, with COVID-19 primarily causing short-term effects. A total of 119 cities experienced community transfers (32.25%), and urban link closeness remained geographically influenced, with community boundaries closely aligning with provincial borders. The findings offer insights into the long-term effects of major public health events on population distribution and mobility networks.

Yaming Zhang, Xiaoyu Guo, Yanyuan Su, Yaya Hamadou Koura H, Na Wang, Wenjie Song