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Abstract Numerous studies have substantiated the substantial impact of COVID-19 on metro travel, which is expected to gradually recover once the pandemic is controlled. Given the potentially more severe repercussions of COVID-19 on vulnerable groups like the elderly and people with disabilities, recovery patterns may differ significantly among various demographic segments. However, limited research has addressed this notable disparity. To address this gap, we collected metro travel data in Wuhan from March 2019 to April 2021. We analyzed changes in travel characteristics among different groups, such as the elderly, people with disabilities, commuters, school students, and others, before and after the pandemic. By employing interrupted time series analysis, we explored the short-term impact of the pandemic on different groups and their long-term recovery trajectories. We also investigated the factors influencing the recovery of metro travel among diverse demographic groups. The findings indicate the following: (1) All groups experienced a sharp decline in travel ridership and frequency in the short term due to the pandemic. (2) There are distinct variations in long-term ridership recovery among different groups, with commuters and school students showing the quickest recovery. However, ridership among people with disabilities remained below pre-pandemic levels even a year after the pandemic. (3) Given the inherent spatiotemporal regularity in residents’ daily activities, post-pandemic metro travel patterns closely align with the pre-pandemic patterns. (4) Different built environment factors exert varying degrees of influence on the recovery of metro ridership among different groups, and distinctions are evident between weekdays and weekends. These findings enhance our comprehension of the pandemic’s impact on diverse demographic groups, which can guide government agencies and urban planners in formulating more resilient strategies for rail transit operations and land use optimization.

The equitable allocation of public service facilities is directly related to the healthy development and socially just functioning of cities. Traditional location-allocation models mostly take travel distance and facility construction cost as the decision-making objectives, with relatively single optimization objectives, and are not sufficiently adaptable to reality. The introduction of the accessibility analysis and the concept of equalization of public services diversify the objectives of urban public service facility optimization decisions. The construction of the circle of life is based on residents' behavior and helps to improve its adaptability in the configuration of public services. This study evaluates the accessibility of eight types of public service facilities in Xiangyang High-tech Zone, China, from a Living Circle perspective, based on the Gaussian Two-step Floating Catchment Area (G2SFCA) method. We integrate the advantages of the Minimum Facility Point (MFP) model, Maximum Covering Location Problem (MCLP) model, and P-Median model to address the equity and efficiency issues in facility configuration, and seek the optimal layout scheme under the fairness objective. Results showed that after using the improved location-allocation models, the maximum travel time for residents was reduced from 76 ​min to 13 ​min, and the average travel time was reduced from 19 ​min to 8 ​min. Additionally, the coverage rate of the facilities increased from an average of 57% to 97%, and the spatial layout of facilities was more rational. The research results contributed to the study of spatial problems and spatial equity in facility allocation.

As the backbone of passenger transportation in many large cities around the world, it is particularly important to explore the association between the built environment and metro ridership to promote the construction of smart cities. Although a large number of studies have explored the association between the built environment and metro ridership, they have rarely considered the spatial and temporal heterogeneity between metro ridership and the built environment. Based on metro smartcard data, this study used EM clustering to classify metro stations into five clusters based on the spatiotemporal travel characteristics of the ridership at metro stations. And the GBDT model in machine learning was used to explore the nonlinear association between the built environment and the ridership of different types of stations during four periods in a day (morning peak, noon, evening peak, and night). The results confirm the obvious spatial heterogeneity of the built environment’s impact on the ridership of different types of stations, as well as the obvious temporal heterogeneity of the impact on stations of the same type. In addition, almost all built environment factors have complex nonlinear effects on metro ridership and exhibit obvious threshold effects. It is worth noting that these findings will help the correct decisions be made in constructing land use measures that are compatible with metro functions in smart cities.

Abstract Transit-oriented development (TOD) has long been recognized as a significant model for prospering urban vibrancy. However, most studies on TOD and urban vibrancy do not consider temporal differences or the nonlinear effects involved. This study applies the gradient boosting decision tree (GBDT) model to metro station areas in Wuhan to explore the nonlinear and synergistic effects of the built-environment features on urban vibrancy during different times. The results show that (1) the effects of the built-environment features on the vibrancy around metro stations differ over time; (2) the most critical features affecting vibrancy are leisure facilities, floor area ratio, commercial facilities, and enterprises; (3) there are approximately linear or complex nonlinear relationships between the built-environment features and the vibrancy; and (4) the synergistic effects suggest that multimodal is more effective at leisure-dominated stations, high-density development is more effective at commercial-dominated stations, and mixed development is more effective at employment-oriented stations. The findings suggest improved planning recommendations for the organization of rail transport to improve the vibrancy of metro station areas.

BackgroundThe feasibility and safety of robotic extended cholecystectomy (REC) are still uncertain. This study was performed to compare the short- and long-term outcomes of REC with those of open extended cholecystectomy (OEC) for T1a–T3 gallbladder cancer.MethodsFrom January 2015 to April 2022, 28 patients underwent REC in our center. To minimize any confounding factors, a 1:2 propensity score-matching analysis was conducted based on the patients’ demographics, liver function indicators, T stage, and symptoms. The data regarding demographics, perioperative outcomes, and long-term oncologic outcomes were reviewed.ResultsThe visual analogue scale score was significantly lower in the REC than OEC group immediately postoperatively (3.68 ± 2.09 vs. 4.73 ± 1.85, P = 0.008), on postoperative day 1 (2.96 ± 1.75 vs. 3.69 ± 1.41, P = 0.023), and on postoperative day 2 (2.36 ± 1.55 vs. 2.92 ± 1.21, P = 0.031). In addition, the REC group exhibited a shorter time to first ambulation (P = 0.043), a shorter time to drainage tube removal (P = 0.038), and a shorter postoperative stay (P = 0.037), but hospital costs were significantly higher in the REC group (P

This study used metro smart-card data from Wuhan, China, and explored the impact of the built environment on the metro ridership and station travel distance of elderly people using geographically weighted regression (GWR). First, our results show that elderly ridership at transfer stations is significantly higher than that at non-transfer stations. The building floor area ratio and the number of commercial facilities positively impact elderly ridership, while the number of road intersections and general hospitals has the opposite impact, of which factors show significant heterogeneity. Second, our results show that the average travel distance of terminal stations is significantly higher than that of non-terminal stations, and the average travel distance of non-transfer stations is higher than that of transfer stations. The distance of stations from the subcenter and building volume ratio have a positive effect, while station opening time and betweenness centrality have a negative effect. Our findings may provide insights for the optimization of land use in the built environment of age-friendly metros, help in the formulation of relevant policies to enhance elderly mobility, and provide a reference for other similar cities.

The expansion of the rail transit network has a positive impact on travel characteristics under spatial and temporal constraints by changing accessibility. However, few empirical studies have examined the longitudinal evolution of the impact of accessibility and travel characteristics. In this paper, a model of the Wuhan rail transit network is constructed and the evolution of the spatial pattern of accessibility over different periods is analyzed. The correlation of accessibility with rail transit travel characteristics is studied longitudinally to provide theoretical support for rail transit construction and traffic demand management. The study shows that: (1) Wuhan’s rail transit network has evolved from a tree to a ring, improving the operational efficiency. (2) The accessibility of Wuhan’s rail transit network has evolved into a circular structure, showing a decreasing trend away from the city center. (3) The change of accessibility greatly affects travel characteristics. The higher the accessibility, the higher the traffic volume, and the lower the travel frequency, the more residents travel during peak hours, and the shorter the travel distance. These findings are useful for gaining insight into public transportation demand in large cities, and thus for developing reasonable transportation demand management policies.