Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic. (January 2022) - Long, Jed A.; Ren, Chang
Abstract: Covid-19 interventions are greatly affecting patterns of human mobility. Changes in mobility during Covid-19 have differed across socio-economic gradients during the first wave. We use fine-scale network mobility data in Ontario, Canada to study the association between three different mobility measures and four socio-economic indicators throughout the first and second wave of Covid-19 (January to December 2020). We find strong associations between mobility and the socio-economic indicators and that relationships between mobility and other socio-economic indicators vary over time. We further demonstrate that understanding how mobility has changed in response to Covid-19 varies considerably depending on how mobility is measured. Our findings have important implications for understanding how mobility data should be used to study interventions across space and time. Our results support that Covid-19 non-pharmaceutical interventions have resulted in geographically disparate responses to mobility and quantifying mobility changes at fine geographical scales is crucial to understanding the impacts of Covid-19. Highlights: Network mobility data is used to generate fine-scale aggregate mobility indices. Spatial seemingly unrelated regression models are used to study aggregate mobility indices. Associations between mobility and socio-economic variables vary throughout the year 2020. The nature of the relationship depends on the socio-economic indicators. How mobility is measured matters in the study of the impacts of Covid-19.