COVID-19 impacts on cross-border mobility of senior population between Shenzhen and Hong Kong.

The onset of the COVID-19 outbreak led to widespread adoption of mobility intervention policies, which were widely regarded as effective measures to control the spread of the virus. The initial pandemic wave, accompanied by the enforcement of mobility intervention policies, greatly changed human mobility patterns, especially cross-border mobility (CBM). This study investigates the impact of the first wave of the pandemic and related mobility intervention policies on the CBM of the senior population between Shenzhen and Hong Kong. Based on anonymous mobile phone trajectory data from 17 million devices active in Shenzhen spanning December 2019 to May 2020, we consider the implementation of mobility intervention policies during different stages of pandemic in both cities. We adopt interrupted time series (ITS) analysis to explore the causal effects of different mobility intervention policies on the CBM of older people between Hong Kong and Shenzhen. We find that most mobility intervention policies have a significant abrupt or gradual effect on the CBM of older people, especially in the 60-64 age group. As these policies neglect the mobility needs and characteristics among the senior groups, such as visiting relatives or friends and seeking medical treatment across borders, we suggest that more coordinated and integrated policies and measures are required to address the CBM needs of older people in Shenzhen and Hong Kong, especially in the post-pandemic era.

Causal effects of mobility intervention policies on intracity flows during the COVID-19 pandemic: The moderating role of zonal locations in the transportation networks.

Many studies have investigated the impact of mobility restriction policies on the change of intercity flows during the outbreak of COVID-19, whereas only a few have highlighted intracity flows. By using the mobile phone trajectory data of approximately three months, we develop an interrupted time series quasi-experimental design to estimate the abrupt and gradual effects of mobility intervention policies during the pandemic on intracity flows of 491 neighborhoods in Shenzhen, China, with a focus on the role of urban transport networks. The results show that the highest level of public health emergency response caused an abrupt decline by 4567 trips and a gradually increasing effect by 34 trips per day. The effectiveness of the second return-to-work order (RtW2) was found to be clearly larger than that of the first return-to-work order (RtW1) as a mobility restoration strategy. The causal effects of mobility intervention policies are heterogenous across zonal locations in varying urban transport networks. The declining effect of health emergency response and rebounding effect of RtW2 are considerably large in better-connected neighborhoods with metro transit, as well as in those close to the airport. These findings provide new insights into the identification of pandemic-vulnerable hotspots in the transport network inside the city, as well as of crucial neighborhoods with increased adaptability to mobility interventions during the onset and decline of COVID-19.

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.