Understanding Socioeconomic Disparities in Mobility Behavior During the COVID-19 Pandemic in Developing Countries
by Samuel Paul Fraiberger , Lorenzo Lucchini , Ollin Langle Chimal , Nancy Lozano GraciaVeraset Inequality and Shared Prosperity
The COVID-19 pandemic profoundly disrupted global mobility, but how did it affect different socioeconomic groups, particularly in developing and middle-income countries?
By combining high-resolution geolocation data from Veraset with population census data,the World Bank’s Global Practice for Urban, Disaster Risk Management, Resilience and Land (GPURL) collaborated with the Development Economics Vice Presidency (DEC) to uncover the systematic socioeconomic disparities in mobility behavior during the health crisis in developing countries.
Challenge
In response to the COVID-19 pandemic, governments and local authorities worldwide implemented non-pharmaceutical interventions such as stay-at-home orders or workplace closures in an effort to limit the spread of the virus. While these interventions significantly reduced people’s mobility, they also exacerbated existing inequalities. People stayed at home from work or school, avoided large gatherings, and refrained from commuting, thereby changing their mobility behavior. Although there are studies on how the pandemic impacted the most vulnerable, little is known about the socioeconomic disparities in mobility behavior across middle-income economies. The lack of detailed, real-time data on how different groups respond to restrictions has sometimes left researchers and policymakers with an incomplete understanding of the impacts of the enacted interventions on different socioeconomic groups. This is particularly problematic in regions where income inequality is often stark, and access to formal and more secure employment, healthcare, and remote work is limited.
Solution
By leveraging aggregated and anonymized mobile geolocation data with population census data for 6 middle-income countries across 3 continents –Brazil, Colombia, Indonesia, Mexico, the Philippines, and South Africa– between January 1st and December 31st, 2020 (“observation period”), this analysis uncovered common cross-national disparities in the behavioral response to the pandemic across socioeconomic groups.
The core dataset consisted of anonymized movement trajectories of more than 281 million mobile phone devices and was shared by Veraset through the Development Data Partnership.
In this study the team used a spatiotemporal clustering technique to accurately infer how people allocated their time between their home, their workplace, and other locations they visited. By assigning to each user a wealth proxy derived from census data on the administrative unit where they live, they then characterized the propensity of mobile phone users of various socioeconomic groups to self-isolate at home, relocate to a rural area, or commute to work.
This study found that when the pandemic hit, urban individuals 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. Among them, those who used to commute to high-wealth places prior to the pandemic stopped commuting 1.4 times more than those who used to commute to low-wealth places. The gap in the behavioral responses between socioeconomic groups persisted during the entire observation period. In particular, among individuals living in low-wealth neighborhoods, those who used to commute to work in high-wealth neighborhoods pre-pandemic were particularly at risk, facing both the reduction in economic activity in the high-wealth neighborhood and being more likely to be affected by public transport closures.
Impact
This World Bank study revealed how non-pharmaceutical interventions during the COVID-19 pandemic affected the mobility options of economically vulnerable groups. The data from Veraset was essential for quantifying human mobility during the global emergency period and providing key insights into the capacity of mobile-users across different socioeconomic groups to respond to the evolution of the pandemic and mobility restrictions. The gap in mobility behavior uncovered by the team not only showed that individuals living in low-wealth neighborhoods faced a greater exposure to the virus, but also highlighted the need for public health authorities to carefully balance the measures aimed at controlling the epidemic with the economic burden on these more vulnerable communities.
As developing countries often lack the capacity to access up-to-date information on individuals, mobile data could help policymakers and international development organizations target aid to the most vulnerable in a timely fashion and respond to future health crises more effectively.