People who use electric scooters to get around are more likely to crash and be injured than other road users, according to a recent study.
- Before 2018, the year in which electric scooters were introduced, a maximum of 13 injuries related to this means of transport were recorded per year.
- Since its use has become widespread in large cities, 595 injuries have been recorded in 2018 and 672 lesions in 2019.
They have taken over the sidewalks, roads and bike paths of major cities. “Electric scooters have become popular, but injuries to riders and bystanders have not been well characterized.” This was reported by researchers at the University of California, Los Angeles (UCLA). To determine the injuries associated with the use of this means of urban transport and estimate the injury rate per trip, they carried out work published in the journal PLOS One April 6.
For the purposes of their study, the scientists analyzed the medical records of people who had been involved in a road accident. The latter were treated in 180 clinics and two major hospitals in Los Angeles between January 1, 2014 and May 14, 2020. The identification, counting and description of the injuries were carried out using an algorithm. “We combine these numbers with municipal data on e-scooter use to report a usage-adjusted monthly rate of scooter-related injuries,” the authors said.
No more injuries with electric scooters
According to the results, the injury rate caused by an e-scooter is estimated at 115 injuries per 1 million trips, which is a higher rate than for other means of transport (motorcycle, bicycle, car, walking). The injuries concern the drivers of this machine but also pedestrians. Among the 1,354 people injured by electric scooters, 30% of them were admitted to the emergency room, 29% required advanced imaging, 6% were hospitalized and 2 died.
According to the researchers, accidents with e-scooters are more frequent. “However, the comparative severity of injury is unknown. Our methodology may prove useful for investigating other clinical conditions not identifiable by existing diagnostic systems,” reads the study’s conclusions.
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