Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Dec 9, 2022
Date Accepted: May 16, 2023
Date Submitted to PubMed: May 16, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Validation of a proxy measure to control for the confounding effects of the COVID-19 pandemic in population-based research studies
ABSTRACT
Background:
The COVID-19 pandemic had wide-ranging systemic impacts, with implications for social and behavioral factors in human health. These impacts may act as confounders in population-level research studies.
Objective:
We sought to identify and validate an affordable, flexible measure to serve as a covariate in research spanning the COVID-19 pandemic period.
Methods:
Transportation Security Administration (TSA) checkpoint travel numbers were used to calculate a weekly sum of daily passengers and validated against a self-reported item on social distancing practices drawn from a continuous tracking survey among a national sample of youth and young adults (15-24 years) in the United States (N=45,080). An aggregated week-level variable was calculated as the proportion of respondents who did not practice social distancing that week (January 1, 2019 – May 31, 2022). Spearman’s rank correlation coefficients were calculated for the two measures.
Results:
TSA data ranged from 668,719 travelers the week of April 8, 2020 to nearly 15.5 million travelers the week of May 18, 2022. The weekly proportion of survey respondents who did not practice social distancing ranged from 18.1% (week of April 15, 2020) to 70.9% (week of May 25, 2022). The measures were strongly correlated from January 2019 to May 2022 (ρ=.90, p<0.001) and March 2020 to May 2022 (ρ=.87, p<0.001). Strong correlations were observed when analyses were restricted to age groups (15-17: ρ =.90, p<0.001; 18-20: ρ=.0.87, p<0.001; 21-24: 0.88, p<0.001), racial/ethnic minorities (ρ=.86, p<0.001) and respondents with lower socioeconomic status (ρ=.88, p<0.001).
Conclusions:
The TSA’s travel checkpoint data provide a publicly available, flexible metric to control for time-varying pandemic impacts at a national level.
Citation
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