Estimating the Economic Effects of the Early Covid-19 Emergency Response in Cities Using Intracity Travel Intensity Data

Lijiao Yang,Caiyun Wei,Hirokazu Tatano,Qian Ye,Xinyu Jiang

doi:10.1007/s13753-022-00393-7

Abstract

In the early days of the Covid-19 pandemic, China implemented the most stringent and serious emergency response. To understand the effect of such an emergency response strategy on the economic system, this study proposed a simultaneous overall estimation method using intracity travel intensity data. The overall effect is represented by the difference between intracity travel intensity with and without the emergency response. Using historical data and time series analysis, we compared intracity travel intensity post China’s implementation of the emergency response with predicted intracity travel intensity without such a response. The loss rates, defined by the proportion of intracity travel intensity loss, were calculated for 360 cities within 33 provincial-level regions in China based on data availability. We found that 30 days after the emergency response, 21% of the cities saw over 80% recovery and 10% of the cities showed more than 90% recovery; 45 days after the emergency response, more than 83% of the 360 cities witnessed 80% recovery. The correlation between gross domestic production loss rate and travel intensity loss rate was studied quantitatively to demonstrate the representativeness of the intracity travel intensity loss rate. This indicator was also used to analyze the spatial and temporal patterns of the effects on the economy. The results of this study can help us understand the economic effects caused by the early Covid-19 emergency response and the method can be a reference for fast and real-time economic loss estimation to support emergency response decision making under pandemic conditions.

Highlights

In December 2019, a novel coronavirus infection, known as Covid-19, rapidly spread across the world, affecting many people grievously
Severity, and scope of impact, public health emergencies in China are classified into four levels (I, II, III, and IV), with severity decreasing from Level I to Level IV; emergency responses are prepared for the four levels (Sun et al 2018)
We show the use of the prediction model developed in the previous section to predict the travel intensity without emergency response in 2020

Summary

Introduction

In December 2019, a novel coronavirus infection, known as Covid-19, rapidly spread across the world, affecting many people grievously. In March 2020, the World Health Organization (WHO) declared the outbreak a pandemic, characterized by fast transmission speed, wide range of infection, and difficulty in controlling the disease. All provinces in China successively carried out the Level I emergency response (Tang et al 2020; Tian, Li, et al 2020). The nationwide emergency response efficiently delayed the expansion of the virus by three to five days (Chinazzi et al 2020), and significantly reduced the travel flow and concentration of people

Methods

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Discussion

Conclusion