Structural changes in intercity mobility networks of China during the COVID-19 outbreak: A weighted stochastic block modeling analysis

This study focuses on a mesoscale perspective to examine the structural and spatial changes in the intercity mobility networks of China from three phases of before, during and after the Wuhan lockdown due to the outbreak of COVID-19. Taking advantages of mobility big data from Baidu Maps, we introduce the weighted stochastic block model (WSBM) to measure and compare mesoscale structures in the three mobility networks. The results reveal significant changes to volume and structure of the intercity mobility networks. Particularly, WSBM results show that the intercity network transformed from a typical core-periphery structure in the normal phase, to a hybrid and asymmetric structure with mixing core-peripheries and local communities in the lockdown phase, and to a multi-community structure with nested core-peripheries during the post-lockdown phase. These changes suggest that the outbreak of COVID-19 and the travel restrictions deconstructed the original hierarchy of the intercity mobility network in China, making the network more locally or regionally fragmented, even at the recovery stage. This study provides new empirical and methodological insights into understanding mobility network dynamics under the impact of COVID-19, helping assess the emergency-induced impact as well as the recovery process of the mobility network.