Socioeconomic disparities in mobility behavior during the COVID-19 pandemic in developing countries (preprint)

Mobile phone data have played a key role in quantifying human mobility during the COVID-19 pandemic. Existing studies on mobility patterns have primarily focused on regional aggregates in high-income countries, obfuscating the accentuated impact of the pandemic on the most vulnerable populations. By combining geolocation data from mobile phones and population census for 6 middle-income countries across 3 continents between March and December 2020, we uncovered common disparities in the behavioral response to the pandemic across socioeconomic groups. When the pandemic hit, urban users living in low-wealth neighborhoods were less likely to respond by self-isolating at home, relocating to rural areas, or refraining from commuting to work. The gap in the behavioral responses between socioeconomic groups persisted during the entire observation period. Among low-wealth users, those who used to commute to work in high-wealth neighborhoods pre-pandemic were particularly at risk, facing both the reduction in activity in high-wealth neighborhood and being more likely to be affected by public transport closures due to their longer commute. While confinement policies were predominantly country-wide, these results suggest a role for place-based policies informed by mobility data to target aid to the most vulnerable.

Uncovering socioeconomic gaps in mobility reduction during the COVID-19 pandemic using location data (preprint)

Using smartphone location data from Colombia, Mexico, and Indonesia, we investigate how non-pharmaceutical policy interventions intended to mitigate the spread of the COVID-19 pandemic impact human mobility. In all three countries, we find that following the implementation of mobility restriction measures, human movement decreased substantially. Importantly, we also uncover large and persistent differences in mobility reduction between wealth groups: on average, users in the top decile of wealth reduced their mobility up to twice as much as users in the bottom decile. For decision-makers seeking to efficiently allocate resources to response efforts, these findings highlight that smartphone location data can be leveraged to tailor policies to the needs of specific socioeconomic groups, especially the most vulnerable.