Evaluating the Real-Time Impact of COVID-19 on Cities: China as a Case Study

Abstract

Since the beginning of 2020, the COVID-19 epidemic has dramatically influenced the human socioeconomic system. If we conceive of the city as a complex organism with a metabolism, then the daily flows of people, materials, and information into and out of a city can be regarded as its metabolism. To evaluate the real-time impact of COVID-19 on a city’s economy and society, we construct a health index of cities (HIC) using human mobility big data from Baidu and analyze the temporal and spatial changes of the HIC in China. The results show that both internal and intercity population movements have been significantly affected by the COVID-19 epidemic, and the decline in both was more than 50% at some points. The intercity movement is more affected than the intracity movement, and the impact is more sustained. Compared with the same period before the outbreak, the HIC in China decreased by 28.6% from January 20 to April 21, 2020. The deterioration rate of the HIC was faster than the growth rate of COVID-19 cases, but the improvement in the HIC was much slower than the decline in COVID-19 cases. Although the HIC is highly correlated with COVID-19 in both the spatial and temporal dimensions, the effect of the epidemic on the HIC varied across regions. The HIC fell more significantly in provincial capitals, such as Beijing, Shanghai, Guangzhou, and Zhengzhou, and in urban agglomerations, and these cities’ HICs were lower with a longer-lasting reduction. This study can serve as a frame of reference for studying the real-time impact of the epidemic, helping cities’ policymakers to quickly assess its socioeconomic impact. By extension, this index can be applied to other countries and other public health emergencies.