Abstract
Introduction
As population densities increase, cities face increased pedestrian and cyclist traffic in the setting of infrastructure that was designed to prioritize cars, trucks, and buses. Fatalities for pedestrians and bicyclists are on the rise. Trauma centers collect unique data on traumatic accidents.
Objective
The identification of incident clusters using trauma registry data can aid in trauma prevention efforts in the local community. The complete spatial randomness hypothesis was used as the null hypothesis, assuming that incidents are randomly distributed. Exploratory spatial data analysis using the Getis-Ord Gi* statistic in ArcGIS Pro was used to identify statistically significant incident clusters.
Participants
All trauma activations during the years 2021 and 2022 at a single Level 2 trauma center involving pedestrians or bicyclists and motor vehicles. Data were collected retrospectively using the institution’s trauma registry.
Results
335 incidents involving cyclists and pedestrians were identified, 134 were included in the final analysis. 99 involved pedestrians (74%), 35 involved bicyclists. 14 individuals did not survive to hospital discharge (10%, all pedestrians). Exploratory spatial analysis of individual incidents using 0.5 mile map cells identified 18 statistically significant incident clusters.
Conclusion
Accidents involving pedestrians and bicyclists are not randomly distributed. The hot spots identified in this study correspond with high foot traffic areas, thought to be pedestrian friendly. Data from this study can be used to guide trauma prevention efforts and public health interventions to improve safety in the local community.
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