The prevention and control of COVID-19 in megacities is under large pressure because of tens of millions and high-density populations. The majority of epidemic prevention and control policies implemented focused on travel restrictions, which severely affected urban mobility during the epidemic. Considering the impacts of epidemic and associated control policies, this study analyzes the relationship between COVID-19, travel of residents, Point of Interest (POI), and social activities from the perspective of taxi travel. First, changes in the characteristics of taxi trips at different periods were analyzed. Next, the relationship between POIs and taxi travels was established by the Geographic Information System (GIS) method, and the spatial lag model (SLM) was introduced to explore the changes in taxi travel driving force. Then, a social activities recovery level evaluation model was proposed based on the taxi travel datasets to evaluate the recovery of social activities. The results demonstrated that the number of taxi trips dropped sharply, and the travel speed, travel time, and spatial distribution of taxi trips had been significantly influenced during the epidemic period. The spatial correlation between taxi trips was gradually weakened after the outbreak of the epidemic, and the consumption travel demand of people significantly decreased while the travel demand for community life increased dramatically. The evaluation score of social activity is increased from 8.12 to 74.43 during the post-epidemic period, which may take 3–6 months to be fully recovered as a normal period. Results and models proposed in this study may provide references for the optimization of epidemic control policies and recovery of public transport in megacities during the post-epidemic period.

Understanding the spatially varying effect mechanism of intermodal connection on metro ridership helps policymakers develop differentiated interventions to promote metro usage, especially for megacities with multiple city sub-centers and ring roads. Using multiple datasets in Shanghai, this study combines Light Gradient Boosting Machine (LightGBM) with Shapley additive explanations (SHAP) to explore these effects with the consideration of the built environment and metro network topology. Results show that the collective impacts of intermodal connection are positive, not only within the main city but also alongside the main commuting corridors, while negative effects occur in the peripheral area. Specifically, bike sharing trips increase metro ridership within the inner ring of the city, while bus services lower metro usage at stations alongside the elevated ring roads. Parking facilities enable metro usage at city sub-centers, and the small pedestrian catchment area increases metro riders alongside the main commuting corridors. Empirical findings help policymakers understand the effect mechanism of intermodal connection for stations in different regions and prioritize customized planning strategies.

In developing countries, aging is rapid and new towns in suburban and rural districts are emerging. However, the spatial accessibility and equity of healthcare services for older adults in new towns is rarely examined. This study is among the earliest attempts to evaluate the spatial accessibility and equity of public hospitals for older adults, using data from Songjiang District, Shanghai, China. A modified Gaussian Huff-based three-step floating catchment area (GH3SFCA) method was adopted based on the real-time travel costs of public transit, driving, cycling, and walking. The Gini coefficient and Bivariate Moran’s Index were integrated to estimate spatial equity. The results showed that the spatial accessibility of high-tier hospitals decreases from the central areas to the outskirts for older adults in Songjiang. Meanwhile, the accessibility of low-tier hospitals varies substantially across areas. Although the low-tier hospitals are distributed evenly, their Gini coefficient showed less equitable spatial accessibility than the high-tier hospitals. Furthermore, driving and cycling lead to more equitable spatial accessibility than public transit or walking. Finally, communities with a low-supply–high-demand mismatch for public hospitals were suggested to be improved preferentially. These findings will facilitate planning strategies for public hospitals for older adults in developing new towns.

Public transport improves mobility and well-being for the rapidly aging population. However, few planning interventions have addressed the urban–rural disparity in bus usage among older adults. Using data from Zhongshan, China, this study adopts the eXtreme Gradient Boosting (XGBoost) model to examine urban–rural differences in the nonlinear relationship between built environment and daily bus usage among elderly adults. The results indicate nonlinearities across all built environment variables and stronger effects of the built environment in rural areas. Distance to transit contributes the most in urban neighborhoods but least in rural ones. Furthermore, dwelling unit density and green space accessibility play the biggest roles in the rural context. Additionally, the most effective ranges of intersection density, land use mixture, and CBD accessibility are greater in rural areas. The findings facilitate fine-grained and diversified planning interventions to facilitate bus usage among older adults in both urban and rural areas.