The COVID-19 pandemic outbreak significantly challenged the cities' abilities to recover from shocks, and cities' responses have widely differed. Understanding these disparate responses has been insufficient, especially from a social recovery perspective. In this study, we propose the concept of social recovery and develop a comprehensive perspective on how a city's socioeconomic characteristics affect it. The analytical framework is applied to 296 prefecture-level cities in China, with social recovery measured by the changes in intercity intensity between the pre-pandemic baseline (2019 Q1 and Q2) and the period in which the pandemic slightly abated (2020 Q1 and Q2) through anonymized location-based big data. The results indicate that the social recovery of Chinese cities during the COVID-19 pandemic are significantly spatially correlated. Cities with larger populations, a higher proportion of GDP in the secondary industry, higher road density or more adequate medical resources tend to recover socially better. Moreover, these municipal characteristics have significant spatial spillover effects. Specifically, city size, government intervention and industrial structure show negative spillover effects on neighboring areas while information dissemination efficiency, road density, and the number of community health services per capita have positive spillover. This study fills the knowledge gap regarding the different performances of cities when they face pandemic shocks. The assessment of a city's social recovery is an insight into the theoretical framework of vulnerability that aids in translating it into urban resilience. Hence our findings provide practice implications for China and beyond as the interest in urban-resilience development surges around the post-pandemic world.
Keywords: COVID-19; China; City characteristics; Driving factor; Social recovery; Spatial effect.
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