Urban Transportation Measures and Vaccination Impact on The Number of COVID-19 Infections: A Before and After Study

Abstract

Prior research on COVID-19 focused primarily on travel behavior changes before, during, and after the pandemic, with the aim of analyzing the significant variables. However, this research aims to study and compare the effects of traffic and transportation measures, specific events, and vaccination rates on the COVID-19 infection rate in Tehran, Iran. A correlation analysis is employed to investigate the degree of relationship between the number of infected individuals on each day and the implementation time of measures, events, and the vaccination rate. Over a 14-day period, the majority (67%) of measures and events had a significant impact on either decreasing or increasing the number of infections at a significant level of 1%. Results indicate that congestion pricing suspension has the most effect on decreasing the virus spread (correlation coefficient between -0.75 and -0.94). As another traffic-related measure, intercity travel bans also contributed to a decrease in infections. Additionally, certain holidays/events and their related movements and gatherings are linked to an increase in cases (correlation coefficient between 0.71 and 0.96). The ongoing decrease in infection rate could be attributed to the increasing vaccination rate, showing a negative correlation with a coefficient of -0.771.

Keywords

• pandemic control
• transportation measure
• traffic management
• response effectiveness
• correlation analysis