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With growing environmental concerns associated with gas-powered vehicles and busier city streets, micro-mobility modes, including traditional bicycles and new technologies, such as electric scooters (e-scooters), are becoming solutions. In 2018, e-scooter usage overtook other shared micro-mobility modes with over 38 million e-scooter trips taken. Concurrently, the societal concern regarding the safety of these devices is also increasing. To examine the types of injuries associated with e-scooters and bicycles, the National Electronic Injury Surveillance System (NEISS), a probability sample of US hospitals that collects information from emergency room (ER) visits related to consumer products, was utilized. Records from September 2017 to December 2018 were extracted, and those associated with powered scooters were identified. Injury distributions by age, sex, race, treatment, diagnosis, and location on the body were explored.

Pedal errors have been widely reported as a leading cause of unintended acceleration (UA) incidents for several decades. Many governmental and scientific studies have attempted to characterize the rate of pedal errors leading to UA incidents using data from the North Carolina Crash Database. These data, however, are limited for various reasons, including the absence of an in-depth investigation of causal factors contributing to the accident. To further examine the rate of UA incidents related to pedal error, we utilized the National Motor Vehicle Crash Causation Survey (NMVCCS), a nationally representative sample of 5,471 crashes that occurred between 2005 and 2007. Using a targeted keyword search, we identified 48 potential pedal errors (30 driver-admitted), providing a national estimate of 17,919 pedal errors. We then investigated accident characteristics across these specific cases, including demographics of the drivers, vehicle characteristics, and pre-crash critical events.

The risk of sustaining injury in rear impact collisions is correlated to collision severity as well as other factors such as restraint usage. The most recent National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) data available (1997 to 2011) were analyzed to identify accidents involving passenger vehicles that have experienced an impact with a principal direction of force (PDOF) between 5:00 and 7:00, indicating a rear impact collision. The Abbreviated Injury Scale (AIS) was used as an injury rating system for the involved vehicle occupants who were at least sixteen years old and were seated in the outboard seating positions of the front row. These data were further analyzed to determine injury risk based on resultant delta-V and restraint system use. Each body region (head, spine, thorax, abdomen, upper extremity, and lower extremity) was considered separately.

Approximately 600,000 fatalities occur each year as a result of pedestrians being impacted by motor vehicles (World Bank, 2008). Previous studies (Heller et al., 2009) have utilized databases such as the National Inpatient Sample (NIS) to gain a more thorough understanding of the common injury patterns that occur in real-world traffic collisions involving pedestrians in the United States. The NIS contains records on five to eight million hospital stays annually and provides a wealth of information regarding injuries to hospitalized pedestrian casualties in the U.S. Because of the large number of applicable records in the NIS and the randomized sampling procedure, the data can be used to complete analyses that are not possible with smaller databases such as the Pedestrian Crash Data Study (PCDS), which is not intended to be statistically representative of pedestrian crashes in general.

Over half of the 1.2 million annual traffic fatalities worldwide are pedestrians struck by motor vehicles [ 1 ]. Medical databases, such as the National Inpatient Sample (NIS), have been utilized to ascertain injury patterns in the general population of injured pedestrians [ 2 - 3 ]. However, the authors are not aware of any studies investigating how factors, such as physical impairments, intoxication, and pre-existing medical implants (e.g. hip replacement, artificial knee, etc.) affect the prevalence of pedestrian accidents or injury outcomes. Five to eight million inpatient hospitalization records are included in the NIS annually, and this large sample size allows for analyses that are not possible with smaller data sets on pedestrian injuries. The current study utilizes the NIS to evaluate how several factors such as blindness, deafness, intoxication, and pre-existing medical implants affect injury patterns when compared to the general population of hospitalized pedestrians.

The risk of sustaining injury in side collisions is correlated to collision severity as well as other factors such as restraint usage and occupant position relative to the impact. The most recent National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) data available (1997 to 2007) were analyzed to identify accidents involving passenger vehicles that have experienced an impact with a principal direction of force (PDOF) either between 8:00 and 10:00 or between 2:00 and 4:00, indicating a side impact collision. The Abbreviated Injury Scale (AIS) was used as an injury rating system for the involved vehicle occupants who were at least sixteen years old and were seated in the outboard seating positions of the front row. These data were further analyzed to determine injury risk based on resultant delta-V, restraint system use, and occupant position relative to the impact.

The risk of sustaining injury in frontal collisions is correlated to collision severity as well as other factors such as restraint usage and airbag deployment. Eleven years (1997 to 2007) of National Automotive Sampling System (NASS) data from the Crashworthiness Data System (CDS) were analyzed to identify accidents involving passenger vehicles that have experienced an impact with a principal direction of force (PDOF) between 11:00 and 1:00, indicating a frontal collision. The Abbreviated Injury Scale (AIS) was used as an injury rating system for the involved vehicle occupants who were at least sixteen years old and were seated in the outboard seating positions of the front row. These data were further analyzed to determine injury risk based on factors such as delta-V, restraint system use, and airbag deployment. Each body region (head, face, spine, thorax, abdomen, upper extremity, and lower extremity) was considered separately.

Each year, over half of the world's 1.17 million fatalities resulting from traffic collisions are pedestrians (World Bank, 2008). Mitigation of such fatalities and serious injuries requires a thorough understanding of the common injury mechanisms that occur in pedestrian impacts. Studying the frequency of injury to each body region and how injury patterns are related may provide additional insight into pedestrian injury mechanisms, which could be used to develop additional prevention strategies. There is a wealth of information regarding pedestrian collisions within national databases that have not been extensively used to investigate these issues to date. This paper presents a review of selected databases that contain information regarding injuries to pedestrians who have been involved in a motor vehicle collision, including the strengths and weaknesses of each in performing this type of analysis.

Review of field accident data is an important tool in understanding injuries in motor vehicle crashes (MVCs). Multiple databases are available that contain information about traffic-related traumatic injuries, many of which are not commonly used in traffic injury research. This work discusses some databases commonly used to evaluate field accident data and introduces additional databases (primarily hospital, medical, and trauma) that include traffic-related injuries. These data represent a new source of information about MVC traumas and often contain additional health information. The strengths and limitations of each database for evaluating vehicular injuries are compared and discussed.