Article Text

Initial impact of COVID-19’s stay-at-home order on motor vehicle traffic and crash patterns in Connecticut: an interrupted time series analysis
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  1. Mitchell L Doucette1,2,
  2. Andrew Tucker3,
  3. Marisa E Auguste3,
  4. Amy Watkins2,
  5. Christa Green2,
  6. Flavia E Pereira4,
  7. Kevin T Borrup2,5,
  8. David Shapiro6,
  9. Garry Lapidus2,5
  1. 1Department of Health Science, Eastern Connecticut State University, Willimantic, Connecticut, USA
  2. 2Injury Prevention Center, Connecticut Children's and Hartford Hospital, Hartford, Connecticut, USA
  3. 3Connecticut Transportation Safety Research Center, University of Connecticut, Storrs, Connecticut, USA
  4. 4Office of Highway Safety, Connecticut Department of Transportation, Newington, Connecticut, USA
  5. 5Department of Pediatrics, University of Connecticut School of Medicine, Farmington, Connecticut, USA
  6. 6Department of Surgery, Saint Francis Hospital and Medical Center, Hartford, Connecticut, USA
  1. Correspondence to Dr Mitchell L Doucette, Department of Health Science, Eastern Connecticut State University, Willimantic, CT 06226, USA; doucettemi{at}easternct.edu

Abstract

Introduction Understanding how the COVID-19 pandemic has impacted our health and safety is imperative. This study sought to examine the impact of COVID-19’s stay-at-home order on daily vehicle miles travelled (VMT) and MVCs in Connecticut.

Methods Using an interrupted time series design, we analysed daily VMT and MVCs stratified by crash severity and number of vehicles involved from 1 January to 30 April 2017, 2018, 2019 and 2020. MVC data were collected from the Connecticut Crash Data Repository; daily VMT estimates were obtained from StreetLight Insight’s database. We used segmented Poisson regression models, controlling for daily temperature and daily precipitation.

Results The mean daily VMT significantly decreased 43% in the post stay-at-home period in 2020. While the mean daily counts of crashes decreased in 2020 after the stay-at-home order was enacted, several types of crash rates increased after accounting for the VMT reductions. Single vehicle crash rates significantly increased 2.29 times, and specifically single vehicle fatal crash rates significantly increased 4.10 times when comparing the pre-stay-at-home and post-stay-at-home periods.

Discussion Despite a decrease in the number of MVCs and VMT, the crash rate of single vehicles increased post stay-at-home order enactment in Connecticut after accounting for reductions in VMT.

  • motor vehicle � occupant
  • longitudinal
  • epidemiology

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Footnotes

  • Twitter @ML_Doucette, @wellofitall

  • Contributors All authors conceived of the study. MLD, AT and MEA coordinated data acquisition. MLD designed the study’s statistical approach and performed the data analysis. MLD, AT, MEA, AW, KB and CG contributed to an initial manuscript draft. All authors provided substantive feedback on all manuscript drafts. GL provided senior author leadership in study design and statistical decision making.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval This study is included in the IRB approved Connecticut Injury Surveillance System managed by the Injury Prevention Center at Connecticut Children’s.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data may be obtained from a third party and are not publicly available. MVC data from the Connecticut Transportation Safety Research Center are publicly available (https://www.ctcrash.uconn.edu). Data pertaining to estimated daily vehicle miles traveled were accessed through the company StreetLight Data under a licensed agreement and are not available upon request per agreement.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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