Examining the impacts of public transit on healthy aging through a natural experiment: study protocols and lessons learned from the Active El Paso project.

This paper describes protocols and experiences from a seven-year natural-experiment study in El Paso, Texas, a border city of predominantly Latino/Hispanic population. The study focuses on how Bus Rapid Transit (BRT) impacts physical activity and thus plays a role in alleviating obesity and related chronic diseases that impact healthy aging. Our protocols describe a longitudinal and case-comparison study, which compared residents exposed to new BRT stations with those who were not. This paper also introduces lessons and experiences to overcome the following challenges: delays in the BRT opening (the main intervention), the COVID-19 pandemic, methodological challenges, participant recruitment and retention, and predatory survey takers. Our transdisciplinary approach was pivotal in addressing these challenges. We also proposed and tested multi-level intervention strategies to reduce modifiable barriers to transit use. Our most important takeaway for researchers, practitioners, and policy makers is the importance of being flexible and ready to adapt to new circumstances. Future natural-experiment researchers need to become more versatile in an increasingly volatile and uncertain world.

Transportation as a Disease Vector in COVID-19: Border Mobility and Disease Spread.

More than a year after COVID-19 was declared a pandemic by the World Health Organization, the U.S.A. and Mexico rank first and fourth, respectively, with regard to the number of deaths. From March 2020, nonessential travelers were not allowed to cross the border into the U.S.A. from Mexico via international land ports of entry, which resulted in a more than 50% decrease in the number of people crossing the border. However, border communities still face a higher number of cases and faster community spread compared with those without international land ports of entry. This paper established an econometric model to understand the effects of cross-border mobility and other socioeconomic parameters on the speed of spread. The model was developed at the U.S. county level using data from all 3,141 counties in the U.S.A. Additionally, a follow-up U.S. county comparative analysis was developed to examine the significance of having a border crossing between the U.S.A. and Mexico for U.S. counties. The findings of the analysis revealed that the variables having a significant effect are as follows: population density; number of people per household; population in the 15-65 age group; median household income; mask use; number of visits to transit stations; number of visits to workplace; overall mobility; and having a border crossing to Mexico within county limits. The comparative analysis found that U.S. counties with border crossings have an average of 123 cases per 1,000 population whereas their counterparts without border crossings only have 90 cases per 1,000 population.