Modelling the relationship between covid-19 restrictive measures and mobility patterns across Europe using time-series analysis

Abstract

Since early 2020, strict restrictions on non-essential movements were imposed globally as countermeasures to the rapid spread of COVID-19. The various containment and closures strategies, taken by the majority of countries, have directly affected travel behavior. This paper aims to investigate and model the relationship between covid-19 restrictive measures and mobility patterns across Europe using time-series analysis. Driving and walking data, as well as confinement policies were collected from February 2020 to February 2021 for twenty-five European countries and were implemented into Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors (SARIMAX) time-series models. Results reveal a significant number of models in order to estimate mobility during pandemic almost in every country of the study. School closing was found to be the most important exogenous factor for describing driving or walking, while “Stay at home” orders had not a significant effect on the evolution of people movements. In addition, countries which suffered the most due to the pandemic indicated a strong correlation with the restrictive measures. No time-series models were found to describe the countries which implemented weak confinement policies.