Regional population mobility network changes driven by central city lockdowns

Drawing on China Mobile cellphone signaling data, this study uses 128 sub-cities in the core area of the Yangtze River Delta as units of analysis. Employing complex network topology metrics, a Weighted Stochastic Block Model, and improved Within-module degree and Participation coefficients, this study systematically examines the evolutionary characteristics of the regional intercity population mobility network at the macro-, meso-, and micro-scales before, during, and after Shanghai’s 2022 lockdown. The findings are as follows: At the macro level, network connectivity and efficiency declined significantly during the lockdown, then rapidly recovered and achieved adaptive optimization. At the meso level, the network structure underwent a systematic transition—from a multi-community homogeneous structure before the lockdown to a hybrid structure combining core-periphery and random connections during the lockdown, and finally to a nested multi-community structure after the lockdown. At the micro level, most nodes in the network were peripheral, whereas a few key nodes performed core functions; their roles and numbers changed mainly during periods of network volatility and were not strongly correlated with overall mobility. The study demonstrates that regional population mobility networks possess intrinsic resilience mechanisms. Although the lockdown of a megacity temporarily deconstructed the original intercity travel network, the network tended toward localized or regional reintegration during the recovery phase. This research extends the theoretical perspective at the urban sub-city scale over a large regional scope and provides scientific evidence and policy references for pandemic control strategies, regional resilience planning, and coordinated development of urban agglomerations.