Checkpoint Travel Numbers as a Proxy Variable in Population-Based Studies During the COVID-19 Pandemic: Validation...

Area of Science:

• Public Health
• Epidemiology
• Behavioral Science

Background:

• The COVID-19 pandemic significantly impacted human health, influencing social and behavioral factors.
• It introduced potential history bias into population-level research conducted during the pandemic.

Purpose of the Study:

• To identify and validate an accessible, flexible measure for use as a covariate in research spanning the COVID-19 pandemic period.
• To address history bias in health research due to pandemic-related behavioral changes.

Main Methods:

• Utilized Transportation Security Administration (TSA) checkpoint travel numbers as a proxy for population movement.
• Validated TSA data against self-reported social distancing practices from a national youth survey and Google's Community Mobility Reports.
• Employed Spearman rank correlation to assess the relationship between TSA data and validation measures.

Main Results:

• TSA checkpoint data showed strong correlations with social distancing practices (ρ=0.90) and community mobility reports (e.g., transit stations ρ=0.92, retail ρ=0.89) from 2019-2022.
• High correlations were consistent across various demographic groups, including age, race/ethnicity, and socioeconomic status.
• Moderate to strong correlations were observed with different mobility categories, including a strong negative correlation with residence.

Conclusions:

• TSA travel checkpoint data serve as a valuable, publicly available, and time-varying metric.
• This metric can effectively control for history bias in research studies conducted during the COVID-19 pandemic.
• Its flexibility and strong validation make it a useful covariate for epidemiological and behavioral health research.