This past spring, during a peak time for COVID-19’s presence in the state, traffic safety partners from across Connecticut came together to examine the impact of Governor Lamont’s stay-at-home order on motor vehicle crashes in the state.
Motor vehicle crash (MVC) data from the Connecticut Crash Data Repository and daily vehicle miles traveled (DVMT) data from StreetLight’s Insight database from before and during the March 23, 2020 stay-at-home order were used. The period of January 1st to April 30th from 2017 to 2020 was selected for an interrupted time series design.
The analysis produced several significant results, including the difference not only in DVMT in 2020 compared to 2017-2019, but also within 2020 when comparing the pre-stay-at-home period (Jan 1 to Mar 22) to the post-stay-at-home period (Mar 23 to Apr 30). Differences in crash types were also revealed; single-vehicle crash types, both injurious and non-injurious increased while multi-vehicle crashes decreased. The most notable finding was the increase in fatal single-vehicle crashes (4.10 times) during the stay-at-home-period, a finding that was not found in crash data from the previous years.
The research team hypothesized these findings to be a combined result of increased driving speed and reduced traffic volume and police presence. Research on perception and cognitive processes involved in motor vehicle operation support this hypothesis, suggesting that decreased traffic volume is likely to increase speeding and other risky driving behaviors. Reductions in multi-vehicle crashes could be attributed to a smaller number of drivers on the road, as the results imply crash types changed because of the stay-at-home-order, but crash rates overall did not differ significantly. The authors suggest exploring traffic calming measures known to reduce speeding to counteract the increase in crashes during a similar emergency.
Citation: Doucette, M.L., Tucker, A., Auguste, M.E., et al. Initial impact of COVID-19’s stay-at-home order on motor vehicle traffic and crash patterns in Connecticut: an interrupted time series analysis. Injury Prevention. Published Online First: 28 October 2020. doi: 10.1136/injuryprev-2020-043945
The CTSRC’s Marisa Auguste and Andrew Tucker, Ph.D. were a part of the research team for this project. For more information about Ms. Auguste and Dr. Tucker’s projects, visit ctsrc.uconn.edu