COVID-19, traffic demand, and activity restriction in China: A national assessment. (April 2023) - Zhang, Zhao; Fu, Daocheng; Liu, Feng; Wang, Jinghua; Xiao, Kai; Wolshon, Brian
Highlights: Resilience analysis of Chinese national highway transportation system. A linear relationship between highway traffic volume and COVID-19 effective spreading rate. Two COVID-19 control polices based on an SIR COVID-19 spreading model. Shorten the length of COVID-19 outbreak period is effective. Abstract: The global COVID pandemic of 2020, affected travel patterns across the world. The level of impact was influenced not only by the virus itself, but also by the nature, extent, and duration of governmental restriction on commerce and personal activity to limit its spread. This paper focuses on the interaction between COVID-19 transmission and traffic volume and further explores the impact of traffic control policies on the interaction. Roadway traffic volume was used to quantify and assess the Chinese response to the pandemic; specifically, the relationship between government restrictions, travel activity, and COVID-19 progression across 29 provinces. Space and time distributions of traffic volume across China during the first half of 2020, were used to quantity the response and recovery of travel during the critical initial onset period of the virus. Most revealing of these trends were the impact of the Chinese restriction policies on both travel and the virus as well as the relationship of traffic trends during the closure period with the speed and extent of the recovery "bounce" across individual provinces based on location, economic activity, and restriction policy. These suggest that the most significant and rapid declines in traffic volume during the restriction period resulted in the most pronounced returns to normal (or more) demand levels. Based on these trends a Susceptible Infection Recovery model was created to simulate a range of outbreak and restriction policies to examine the relationship between COVID-19 spread and traffic volume in China.