A quasi-experimental analysis on the causal effects of COVID-19 on urban park visits: The role of park features and the surrounding built environment

Although many studies have explored the correlations between mobility intervention policies and park use during COVID-19, only a few have used causal inference approaches to assessing the policy’s treatment effects and how such effects vary across park features and surrounding built environments. In this study, we develop an interrupted time-series quasi-experimental design based on three-month mobile phone big data to infer the causal effects of mobility intervention policies on park visits in Shenzhen, including the first-level response (FLR) and return-to-work (RTW) order. The results show that the FLR caused an abrupt decline of 2.21 daily visits per park, with a gradual reduction rate of 0.54 per day, whereas the RTW order helped recover park visits with an immediate increase of 2.20 daily visits and a gradual growth rate of 0.94 visits per day. The results also show that the impact of COVID-19 on park visits exhibited social and spatial heterogeneities: the mobility-reduction effect was smaller in low-level parks (e.g., community-level parks) with small sizes but without sports facilities and water scenes, whereas parks surrounded by compact neighborhoods and land use were more impacted by the pandemic. These findings provide planners with important insights into resilient green space and sustainable neighborhood planning for the post-COVID era.