An integrated approach to monitoring and estimating COVID-19 risk exposure among leisure-time physical activity participants

Ingrid E. Schneider, Greg Lindsey, Michael Petesch, Christopher J. Wynveen, Megha Budruk, Bill Hendricks, Heather Gibson, Kim Shinew, Taylor Stein, Deonne VanderWoude

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Leisure time physical activity (LTPA) provides both health benefits and risks, particularly during a pandemic. During the COVID-19 pandemic, significant increases in close-to-home LTPA raised concerns for public health and land managers alike. This project illustrates a novel, integrated monitoring approach to estimating COVID-19 risk exposure during trail-related LTPA, with implications for other public spaces. Methods: COVID-19 risk exposure was conservatively calculated from the integration of in-person observations of LTPA trail groups and automated monitoring of trail traffic volumes in spring 2020. Trained observers tracked 1,477 groups. Traffic volume estimates and observed distance data were integrated, considering occlusion and total trail traffic volume. Results: 70% of groups had one or more encounters. Among individual users, 38.5% were 100% compliant across all events observed but 32.7% were not compliant. Considering trail traffic volumes and annual daily traffic volume, exposure to risk of COVID-19 was conservatively estimated at 61.5% among individual trail users. Conclusions: Monitoring opportunities and challenges of health risk exposure exist. Adjusted exposure measures based on volume counts can approximate numbers of unique individuals exposed, inform management actions, efficacy and policy decisions.

Original languageEnglish (US)
Article number101088
JournalJournal of Transport and Health
Volume22
DOIs
StatePublished - Sep 2021

Bibliographical note

Funding Information:
Thank you to the numerous volunteers and interns who collected, entered and cleaned data through Baylor University, the University of Florida and University of Minnesota. The research team would like to acknowledge and thank Philip W. Lindsey for expert technical assistance in data analysis.

Publisher Copyright:
© 2021 Elsevier Ltd

Keywords

  • Daily traffic
  • Density
  • Public health
  • Risk

PubMed: MeSH publication types

  • Journal Article

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