The aim of the present Diploma Thesis is to investigate the impact of pandemic on mobility behavior in the European Union using time-series analysis. Mobility and restrictive measures data were collected for twenty-five countries from online databases. For the data analysis, SARIMAX time-series models were developed for all countries, using driving and walking data as endogenous variables and countermeasures as exogenous variables. The aforementioned methodology resulted in a significant number of models in order to estimate mobility during pandemic almost in every country of the study. It was revealed that school closing is the most important exogenous factor for describing driving or walking, while the effect of “Stay at home” orders was not a significant factor for the evolution of people movements. In addition, countries which suffered the most due to the pandemic showed a strong correlation with the restrictive measures. Furthermore, no time-series models were found to describe the countries which implemented weak countermeasures.