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Am J Epidemiol. 2018 Feb 1;187(2):224-232. doi: 10.1093/aje/kwx233.

Ridesharing and Motor Vehicle Crashes in 4 US Cities: An Interrupted Time-Series Analysis.

Author information

1
Penn Injury Science Center, University of Pennsylvania, Philadelphia, Pennsylvania.
2
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
3
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
4
Department of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.

Abstract

Uber, the world's largest ridesharing company, has reportedly provided over 2 billion journeys globally since operations began in 2010; however, the impact on motor vehicle crashes is unclear. Theoretically, ridesharing could reduce alcohol-involved crashes in locations where other modes of transportation are less attractive than driving one's own vehicle while under the influence of alcohol. We conducted interrupted time-series analyses using weekly counts of injury crashes and the proportion that were alcohol-involved in 4 US cities (Las Vegas, Nevada; Reno, Nevada; Portland, Oregon; and San Antonio, Texas). We considered that a resumption of Uber operations after a temporary break would produce a more substantial change in ridership than an initial launch, so we selected cities where Uber launched, ceased, and then resumed operations (2013-2016). We hypothesized that Uber's resumption would be associated with fewer alcohol-involved crashes. Results partially supported this hypothesis. For example, in Portland, Uber's resumption was associated with a 61.8% reduction (95% confidence interval: 38.7, 86.4) in the alcohol-involved crash rate (an absolute decrease of 3.1 (95% confidence interval: 1.7, 4.4) alcohol-involved crashes per week); however, there was no concomitant change in all injury crashes. Relationships between ridesharing and motor vehicle crashes differ between cities over time and may depend on specific local characteristics.

KEYWORDS:

accidents; alcohol drinking; interrupted time-series analysis; motor vehicles; traffic; transportation

PMID:
28633356
PMCID:
PMC6248466
[Available on 2019-02-01]
DOI:
10.1093/aje/kwx233

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