The impact of COVID-19 on relative changes in aggregated mobility using mobile-phone data

TL;DR

This study uses compositional data analysis on mobile-phone data to reveal hidden mobility patterns during COVID-19, showing increased relative mobility among elderly and less decrease among younger groups on weekends.

Contribution

It introduces the application of compositional data analysis to mobility data to uncover nuanced behavioral changes during the pandemic.

Findings

Elderly groups increased relative mobility during COVID-19.

Younger groups on weekends showed less decrease in mobility.

Revealed hidden mobility patterns not visible through absolute change analysis.

Abstract

Evaluating relative changes leads to additional insights which would remain hidden when only evaluating absolute changes. We analyze a dataset describing mobility of mobile phones in Austria before, during COVID-19 lock-down measures until recent. By applying compositional data analysis we show that formerly hidden information becomes available: we see that the elderly population groups increase relative mobility and that the younger groups especially on weekends also do not decrease their mobility as much as the others.