A paper titled “COVID-19 and driving behavior: Which were the most crucial influencing factors” authored by Marios Sekadakis, Christos Katrakazas, Eva Michelaraki, Apostolos Ziakopoulos and George Yannis, has been published in Data Science for Transportation. Based on the collected data, XGBoost feature analysis algorithms were deployed to obtain the most significant factors. Results revealed that COVID-19 new cases and new fatalities were the most significant factors related to COVID-19 metrics impacting driving behavior. In addition, the correlation between driving behavior with other factors (i.e., distance traveled, mobile use, driving requests, and driving during risky hours) was revealed. Lastly, the differences and similarities of the harsh event rates between the two lockdown periods were identified.