Analyzing the Prevalence of and Factors Associated with Road Traffic Crashes (RTCs) among Motorcyclists in Bangladesh.

Methods: A cross-sectional survey was conducted using a structured questionnaire involving 402 motorcyclists from four major southeastern towns, comprising 350 (86.07%) males and 52 (12.93%) females. The chi-square test was applied in bivariate analysis, and binary multivariable logistic regression was performed to determine the risk factors of road traffic crashes. Results: This study's findings revealed that the overall reported prevalence of road traffic crashes involving motorcycle drivers over one year was 68.66%. Multivariable logistic regression analysis revealed several factors that significantly impacted road traffic crashes. These factors included driving without a valid driving license, the young age (<20) of motorcyclists, driving in rainy weather, exceeding the speed limit, per-week working hours, smoking status, motorcycle ownership, the brand of motorcycle, and not wearing a helmet while driving. Conclusion: The study findings highlight the need for improving motorcycle safety by implementing measures such as imposing per-week work hour limits for riders, enforcing traffic regulations, and promoting helmet use among motorcycle drivers. The results of this study draw attention to the Bangladesh Road Transport Authority (BRTA) and motorcycle drivers in the country to decrease motorcycle crashes and the severity of injuries by implementing efficient guidelines and strategies for driving motorcycles. The findings of this study can assist policymakers and concerned authorities in taking the essential steps to lessen road traffic crashes among motorcyclists in Bangladesh.

Effect of Rural Trauma Team Development on the Outcomes of Motorcycle Accident-Related Injuries (Motor Registry Project): Protocol for a Multicenter Cluster Randomized Controlled Trial.

BACKGROUND: Injury is a global health concern, and injury-related mortality disproportionately impacts low- and middle-income countries (LMICs). Compelling evidence from observational studies in high-income countries shows that trauma education programs, such as the Rural Trauma Team Development Course (RTTDC), increase clinician knowledge of injury care. There is a dearth of such evidence from controlled clinical trials to demonstrate the effect of the RTTDC on process and patient outcomes in LMICs. OBJECTIVE: This multicenter cluster randomized controlled clinical trial aims to examine the impact of the RTTDC on process and patient outcomes associated with motorcycle accident-related injuries in an African low-resource setting. METHODS: This is a 2-arm, parallel, multi-period, cluster randomized, controlled, clinical trial in Uganda, where rural trauma team development training is not routinely conducted. We will recruit regional referral hospitals and include patients with motorcycle accident-related injuries, interns, medical trainees, and road traffic law enforcement professionals. The intervention group (RTTDC) and control group (standard care) will include 3 hospitals each. The primary outcomes will be the interval from the accident to hospital admission and the interval from the referral decision to hospital discharge. The secondary outcomes will be all-cause mortality and morbidity associated with neurological and orthopedic injuries at 90 days after injury. All outcomes will be measured as final values. We will compare baseline characteristics and outcomes at both individual and cluster levels between the intervention and control groups. We will use mixed effects regression models to report any absolute or relative differences along with 95% CIs. We will perform subgroup analyses to evaluate and control confounding due to injury mechanisms and injury severity. We will establish a motorcycle trauma outcome (MOTOR) registry in consultation with community traffic police. RESULTS: The trial was approved on August 27, 2019. The actual recruitment of the first patient participant began on September 01, 2019. The last follow-up was on August 27, 2023. Posttrial care, including linkage to clinical, social support, and referral services, is to be completed by November 27, 2023. Data analyses will be performed in Spring 2024, and the results are expected to be published in Autumn 2024. CONCLUSIONS: This trial will unveil how a locally contextualized rural trauma team development program impacts organizational efficiency in a continent challenged with limited infrastructure and human resources. Moreover, this trial will uncover how rural trauma team coordination impacts clinical outcomes, such as mortality and morbidity associated with neurological and orthopedic injuries, which are the key targets for strengthening trauma systems in LMICs where prehospital care is in the early stage. Our results could inform the design, implementation, and scalability of future rural trauma teams and trauma education programs in LMICs. TRIAL REGISTRATION: Pan African Clinical Trials Registry (PACTR202308851460352); https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=25763. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55297.

The efficacy of hazard perception training and education: A systematic review and meta-analysis.

BACKGROUND: Hazard perception (HP) has been argued to improve with experience, with numerous training programs having been developed in an attempt to fast track the development of this critical safety skill. To date, there has been little synthesis of these methods. OBJECTIVE: The present study sought to synthesise the literature for all road users to capture the breadth of methodologies and intervention types, and quantify their efficacy. DATA SOURCES: A systematic review of both peer reviewed and non-peer-reviewed literature was completed. A total of 57 papers were found to have met inclusion criteria. RESULTS: Research into hazard perception has focused primarily on drivers (with 42 studies), with a limited number of studies focusing on vulnerable road users, including motorcyclists (3 studies), cyclists (7 studies) and pedestrians (5 studies). Training was found to have a large significant effect on improving hazard perception skills for drivers (g = 0.78) and cyclists (g = 0.97), a moderate effect for pedestrians (g = 0.64) and small effect for motorcyclists (g = 0.42). There was considerable heterogeneity in the findings, with the efficacy of training varying as a function of the hazard perception skill being measured, the type of training enacted (active, passive or combined) and the number of sessions of training (single or multiple). Active training and single sessions were found to yield more consistent significant improvements in hazard perception. CONCLUSIONS: This study found that HP training improved HP skill across all road user groups with generally moderate to large effects identified. HP training should employ a training method that actively engages the participants in the training task. Preliminary results suggest that a single session of training may be sufficient to improve HP skill however more research is needed into the delivery of these single sessions and long-term retention. Further research is also required to determine whether improvements in early-stage skills translate to improvements in responses on the road, and the long-term retention of the skills developed through training.

Opportunities and challenges on hospital preparedness to handle motorcycle accidents in Busia County, Kenya: an exploratory qualitative study.

Introduction: motorcycles continue to be a popular mode of transport in Kenya. However, the related injuries cause significant morbidity and mortality and remain to be a major and neglected public health issue. This raised the crucial need for hospital preparedness in managing morbidities and in reducing mortalities. This formed the basis of this paper which aims to document the challenges and opportunities in the healthcare system in handling motorcycle accidents in a Kenyan border town in Busia County. Methods: we drew data from an exploratory qualitative study that was carried out in 2021. All six referral hospitals purposively included in the study. The study targeted a total of 25 top level facility managers as key informants on the facility level opportunities and challenges in handling motorcycle accidents. Descriptive data were analyzed using SPSS version 20. Results: the hospitals were not well prepared to handle motorcycle accidents. The major challenges were understaffing in critical care services; inadequate/lack of equipment to handle motorcycle injuries; inadequate/lack of infrastructure i.e. surgical wards, emergency rooms, inadequate space, functional theatre; lack/inadequate supplies; overstretched referral services arising from the hinge burden of motorcycle accidents in the area; inadequate specialized personnel to provide trauma/care services; mishandling of cases at the site of accident; inability of victims to pay related bills; inappropriate identification of victims at the facility; lack/inadequate on-job training. Some opportunities that currently exist include health system interventions which are not limited to employment of more professionals, improvement of infrastructure, provision of equipment and increase of budgetary allocation. Conclusion: the study reveals vast challenges that are faced by hospitals in managing patients. This calls for the government to step in and capitalize on the proposed opportunities by the health managers to be able to manage morbidities and bring down mortalities due to motorcycle accidents.

Characteristics and Injury Patterns in Traumatic Brain Injury Related to E-Scooter Use in Riga, Latvia: Multicenter Case Series.

Background and Objectives: In recent years, electronic scooters (e-scooters) have gained popularity, whether for private use or as a publicly available transportation method. With the introduction of these vehicles, reports of e-scooter-related accidents have surged, sparking public debate and concern. The aim of this study was to analyze the epidemiological data, characteristics, and severity of traumatic brain injury (TBI) related to e-scooter accidents. Materials and Methods: This retrospective case series evaluated patients who were admitted to the three largest neurosurgery clinics in Riga, Latvia, from the time period of April to October in two separate years-2022 and 2023-after e-scooter-related accidents. The data were collected on patient demographics, the time of the accident, alcohol consumption, helmet use, the type of TBI, other related injuries, and the treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to e-scooter use, with a median age of 30 years (Q1-Q3, 20.25-37.25), four individuals under the age of 18, and the majority (64%) being male. In 23 cases, the injury mechanism was falling, in 5 cases, collision. None were wearing a helmet at the time of the injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (>1.2 g/L) in 75% of cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma: 50% had brain contusions, 43% traumatic subdural hematoma, and almost 30% epidural hematoma. Craniofacial fractures were evident in 71% of cases, and there were fractures in other parts of body in three patients. Six patients required emergency neurosurgical intervention. Neurological complications were noted in two patients; one patient died. Conclusions: e-scooter-related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and a lack of helmet use. Prevention campaigns to raise the awareness of potential risks and the implementation of more strict regulations should be conducted.

Risk of road traffic injury in Norway 1970-2022.

This paper describes changes in the risk of road traffic injury in Norway during the period from 1970 to 2022. During this period, the risk of fatal and personal injury declined by more than 70 % for most groups of road users. There are five main potential explanations of a decline in the risk of injury: (1) a reduced probability of accidents that have the potential for causing injury; (2) an improved protection against injury given that an accident has occurred; (3) improved medical care increasing the survival rate, given an injury (this would reduce the number of fatalities, but not the number of injuries); (4) a tendency for the reporting of injuries in official accident statistics to decline over time; (5) uncertain or erroneous estimates of the exposure to the risk of injury. The decline in the risk of road traffic injuries in Norway after 1970 can probably be attributed to a combination of reduced reporting of injuries in official statistics, improved protection against injury in accidents, and (for fatal injuries) improved medical care. Insurance data, available from 1992, do not indicate a reduction in the risk of accidents leading to insurance claims. Incomplete and possibly erroneous data for mopeds and motorcycles make it impossible to identify sources of changes in injury risk over time for these modes of transport.

The impact of COVID-19 restrictions on motorcycle crashes in Taiwan.

Taiwan is one of the countries with the highest motorcycle per capita globally, and motorcycle crashes are predominant among traffic crashes. This study examines the impact of coronavirus disease 2019 restrictions on motorcycle crashes. We analyzed the trend of motorcycle crashes in Taipei City from 2019 to 2020 using the dataset provided by the Department of Transportation, Taipei City Government, Taiwan. We found 47,108 and 51,441 motorcycle crashes in 2019 and 2020, involving 61,141 and 67,093 motorcycles, respectively. Mopeds had the highest risk in 2020, followed by heavy motorcycles [≥550 cubic capacity (cc)] and scooters compared to 2019. Food delivery motorcycle crashes increased for scooters (0.93% in 2019 to 3.45% in 2020, P < .0001) and heavy motorcycles (250 < cc < 550) (0.90% in 2019 to 3.38% in 2020, P < .0001). While fatalities remained under 1%, 30% to 51% of motorcyclists sustained injuries. Food delivery with scooters or heavy motorcycles (250 < cc < 550) was significantly associated with motorcyclist injuries and deaths. Compared with 2019, the adjusted odds ratios of motorcyclist injuries and deaths in 2020 were 1.43 (95% confidence interval = 1.05-1.94) for heavy motorcycles (≥550 cc) and 1.07 (95% confidence interval = 1.04-1.09) for scooters. This study shows that coronavirus disease 2019 restrictions was associated with elevated risks of crashes, injuries, and deaths among motorcyclists, reflecting the general preference for private transport over public transport. The popularity of food delivery services also contributed to increased motorcycle crashes.

Exploring the spatial relationship of e-bike and motorcycle crashes: Implications for risk reduction.

INTRODUCTION: Electric bicycles, or e-bikes, have become very popular over the past decade. In order to reduce the risk of crashes, it is necessary to understand the contributing factors. While several researchers have examined these elements, few have considered the spatial heterogeneity between crashes and environmental variables, such as Points of Interest (POI). In addition, there is a scarcity of studies comparing the crash-related factors of e-bikes and motorcycles. Despite their differing speed and range capabilities, different POIs also tend to impact area/bandwidths differently because e-bikes cannot cover the same range that motorcycles can. METHOD: In this study, we compared e-bike and motorcycle crashes at 11 different types of POIs in Taipei from 2016 to 2020. Since crashes are sparse events and easily affected by the Modifiable Areal Unit Problem (MAUP), Kernel Density Estimation (KDE) was employed to transform crash points (count data) to crash risk surfaces (continuous data). Additionally, an advanced variant of Geographical Weighted Regression (GWR), Multiscale Geographically Weighted Regression (MGWR) utilized to predict crash risk because each predictor is allowed to have a different bandwidth. RESULTS: The results showed: (a) For e-bike crashes, the MGWR model outperformed the GWR and OLS models in terms of AIC values, while the MGWR and GWR performed similarly with regard to motorcycle crashes; (b) The analysis revealed e-bike and motorcycle crash risk to be associated with various types of POIs. E-bike crashes tended to occur more frequently in areas with more schools, supermarkets, intersections, and elderly people. Meanwhile, motorcycle crashes were more likely to occur in areas with a high number of restaurants and intersections. The search bandwidths of e-bikes are inconsistent and narrower than those of motorcycles.

Evaluating helmet-wearing of single-vehicle overspeeding motorcycle crashes: Insights from temporal instability in parsimonious pooled framework.

OBJECTIVE: A lower helmet-wearing rate and overspeeding in Pakistan are critical risk behaviors of motorcyclists, causing severe injuries. To explore the differences in the determinants affecting the injury severities among helmeted and non-helmeted motorcyclists in motorcycle crashes caused by overspeeding behavior, single-vehicle motorcycle crash data in Rawalpindi city for 2017-2019 is collected. Considering three possible crash injury severity outcomes of motorcyclists: fatal injury, severe injury and minor injury, the rider, roadway, environmental, and temporal characteristics are estimated. METHODS: To provide a mathematically simpler framework, the current study introduces parsimonious pooled random parameters logit models. Then, the standard pooled random parameters logit models without considering temporal effects are also simulated for comparison. By comparing the goodness of fit measure and estimation results, the parsimonious pooled random parameters logit model is suitable for capturing the temporal instability. Then, the non-transferability among helmeted and non-helmeted overspeeding motorcycle crashes is illustrated by likelihood ratio tests and out-of-sample prediction, and two types of models provide robust results. The marginal effects are also calculated. RESULTS: Several variables, such as age, cloudy and weekday indicators illustrate temporal instability. Moreover, several variables are observed to only show significance in non-helmeted models, showing non-transferability across helmeted and non-helmeted models. CONCLUSIONS: More educational campaigns, regulation and enforcement, and management countermeasures should be organized for non-helmeted motorcyclists and overspeeding behavior. Such findings also provide research reference for the risk-compensating behavior and self-selected group issues under overspeeding riding considering the usage of helmets.

Traffic flow detection method based on improved SSD algorithm for intelligent transportation system.

With the development of the new generation communication system in China, the application of intelligent transportation system is more extensive, which brings higher demands for vehicle flow detection and monitoring. Traditional traffic flow detection modes often cannot meet the high statistical accuracy requirement and high-speed detection simultaneously. Therefore, an improved Inception module is integrated into the single shot multi box detector algorithm. An intelligent vehicle flow detection model is constructed based on the improved single shot multi box detector algorithm. According to the findings, the convergence speed of the improved algorithm was the fastest. When the test sample was the entire test set, the accuracy and precision values of the improved method were 93.6% and 96.0%, respectively, which were higher than all comparison target detection algorithms. The experimental results of traffic flow statistics showed that the model had the highest statistical accuracy, which converged during the training phase. During the testing phase, except for manual statistics, all methods had the lowest statistical accuracy on motorcycles. The average accuracy and precision of the designed model for various types of images were 96.9% and 96.8%, respectively. The calculation speed of this intelligent model was not significantly improved compared to the other two intelligent models, but it was significantly higher than manual monitoring methods. Two experimental data demonstrate that the intelligent vehicle flow detection model designed in this study has higher detection accuracy. The calculation speed has no significant difference compared with the traditional method, which is helpful to the traffic flow management in intelligent transportation system.

Temporal trends of transport-related injuries on New Zealand roads.

AIM: This observational study aimed to investigate temporal trends in transport-related injuries in New Zealand by mode of transport and explore whether specific population groups and localities have a relatively higher incidence of injury. These trends provide insight into changes in injury patterns from road trauma. METHODS: A retrospective study of hospitalised road trauma in New Zealand was conducted between 1 July 2017 to 30 June 2021. Data were obtained from the National Minimum Dataset of hospital admissions, and the New Zealand Trauma Registry (NZTR). Road trauma was identified using ICD-10 coding, and major trauma using Abbreviated Injury Scale (AIS) coding. Analysis included road trauma by mode, ethnicity, rurality and population rates. Statistical analysis included Interrupted Time Series (ITS) analysis to account for the impact of COVID-19 on road trauma. RESULTS: Over the 4-year period there were 20,607 incidents of transport-related injury that resulted in admission to a New Zealand hospital. Of these, 14.5% (2,992) involved injuries that were classified as major trauma. Car occupants accounted for 62% of hospitalisations, followed by motorcyclists (23%), pedestrians (9%) and pedal cyclists (4%). Temporal trends showed no reduction in injuries from cars, pedal cyclists and pedestrian injuries, but an increase in motorcycling injuries. Maori had an age-standardised incidence rate almost 3.5 times higher than the rate for Asian peoples. CONCLUSION: The increases in motorcycling injuries and no changes in pedestrian and cycling injuries, as well as demographic variation, highlight the need to focus on vulnerable road users. Effective and targeted initiatives on vulnerable road users will support objectives to reduce deaths and serious injury on New Zealand roads. Enhanced exposure data is needed for vulnerable road users to account for mobility changes over time. Linked data across population-based datasets is an important asset that enhances our understanding of road traffic injuries and allows evidence-based countermeasures to be developed.

Extremity Injuries in Pillion Riders of Fatal 2-Wheeler Road Traffic Accidents: An Autopsy-Based Study.

ABSTRACT: The extremities are the important anatomical regions that are disproportionately injured during road traffic accidents in poor and medium-income countries. The data regarding extremity injuries, particularly in pillion passengers, are minimal globally. We analyzed the pattern of extremity injuries and their association with various parameters such as collision type, seating position, road type, and type of vehicle. This was a hospital-based cross-sectional study. The pillion riders of fatal motorized 2-wheeler road accident cases that were subjected to autopsy were studied over a period of 2 years. We analyzed 73 cases of pillion riders. Females (60%) were the most commonly affected group. The upper extremities were injured in 55 cases (75.3%) and the lower extremities in 49 cases (67.1%). The shoulder (41%), hand (31.3%), and elbow (23.2%) were the predominantly injured anatomical regions of the upper limb. In the lower extremity, knee (41%) and foot (21.9%) were mostly affected. Forty-nine (67.1%) and 48 (65.8%) cases had abrasions in the upper limbs and lower limbs, respectively, followed by lacerations and contusions. Upper extremity injuries are more common compared with lower extremity. The majority of the pillion riders were seated in a side-saddle position, and self-fall from the bike without any collision with other vehicles was the most common mode of injury. Thus, appropriate seating posture with safety gear can be used to reduce extremity injuries.

Injury Patterns of Electric-Scooter Related Trauma: A Systematic Review With Proportion Meta-Analysis.

Electric scooter (ES)-related injuries are increasing but poorly described. Clinicians need more information to be prepared for these patients. We supposed two prevalent patterns of patients: mildly injured (predominant upper-limb injuries) and severely injured (predominant head trauma). This study aims to understand the frequency of ES-related injuries and patients' characteristics despite the heterogeneity of data currently available. A systematic review with a proportion meta-analysis was conducted on studies with a multidisciplinary description of ES-related injuries in adult patients (PROSPERO-ID: CRD42022341241). Articles from inception to April 2023 were identified in MEDLINE, Embase, and Cochrane's databases. The risk of bias was evaluated using ROBINS-I. Twenty-five observational studies with 5387 patients were included in the meta-analysis, depending on reported data. Upper-limb (31.8%) and head (19.5%) injuries are the most frequent (25/25 studies included). When injured while riding, 19.5% of patients are intoxicated with drugs/alcohol, and only 3.9% use a helmet, increasing the possibility of severe injuries. About 80% of patients are victims of spontaneous falls. Half of the patients self-present to the ED, and 69.4% of cases are discharged directly from the ED. Studies' limitations include an overall moderate risk of bias and high heterogeneity. Electric scooter-related accidents are commonly associated with upper-limb injuries but often involve the head. Spontaneous falls are the most common mechanism of injury, probably related to frequent substance abuse and helmet misuse. This hot topic is not adequately investigated due to a lack of data. A prospective registry could fill this gap.

Are front crash prevention systems less effective at preventing rear-end crashes where trucks and motorcycles are struck?

OBJECTIVE: Automatic emergency braking (AEB) and forward collision warning (FCW) are effective at preventing rear-end crashes, but they may perform better in some rear-end crash scenarios than others. The goal of this study was to estimate the effects of front crash prevention systems equipped to passenger vehicles in crashes where another passenger vehicle, a medium/heavy truck, or a motorcycle is struck and compare effectiveness by struck vehicle type. METHODS: More than 160,000 two-vehicle rear-end crashes were identified where a passenger vehicle with or without FCW and AEB was the striking vehicle and another passenger vehicle, medium/heavy truck, or motorcycle was the struck vehicle. Poisson regression was used to estimate the effect of front crash prevention by struck vehicle type on rear-end crash rates per registered vehicle year, accounting for the state and year of the crash and the make, model year, class, and engine type of the striking vehicle. RESULTS: Front crash prevention was associated with a 53% reduction in rear-end crash rates when striking another passenger vehicle, which was significantly larger than the reductions of 38% when striking a medium/heavy truck and 41% when striking a motorcycle. Reductions in rear-end injury crash rates when striking a passenger vehicle also were larger than when striking a medium/heavy truck and when striking a motorcycle. DISCUSSION: If all passenger vehicles were equipped with FCW and AEB that were as effective in crashes striking a truck or motorcycle as they are in crashes with another passenger vehicle, over 5,500 additional crashes with medium/heavy trucks and 500 with motorcycles could potentially be prevented annually in the United States above what would be expected from current front crash prevention systems. Extending front crash prevention testing in consumer information programs to include motorcycle and truck targets could encourage auto manufacturers to improve performance in these crash scenarios.

Motorcycle-related crashes before and during the COVID-19 pandemic: A comparative retrospective observational study from the Middle East.

BACKGROUND: During the COVID-19 pandemic, there was a boom in the delivery sector, with a significant increase in the demand and number of motorcycle delivery drivers in Qatar, which made them vulnerable to injury. We aimed to evaluate the incidence, pattern, and outcome of patients injured by motorcycle-related crashes (MCC) before and during the pandemic. METHODS: A retrospective observational study included all adult patients admitted with motorcycle-related injuries before the pandemic (March 2018 to February 2020) and during the pandemic (March 2020 to March 2022). Comparative analyses were performed based on (work versus non-work related MCCs) and (pre- versus during the pandemic injuries). RESULTS: 510 patients with MCC were identified, of which 172 (33.7 %) were admitted in the pre-pandemic and 338 (66.3 %) during the pandemic. The mean age of patients was 29.2±7.8 years; 56 % were aged 20-29 years, and 99.4 % were males. Work-related MCCs were more frequent among the younger age group (60.9 % vs. 52.1 %; p=0.001) during the early evening, i.e., 6:00 to 9:00 p.m. (21.9 % vs. 13.9 %; p=0.004). However, non-work related MCC occurred more frequently between midnight and 3:00 am (20.2 % vs. 10.9 %; p=0.004), and such patients were more likely non-compliant for protective devices use (19.3 % vs. 6.1 %; p=0.001) and ride under the influence of alcohol (13.2 % vs. 7.4 %; p=0.03). During the pandemic, the proportion of alcohol consumers (13 % vs. 5.8 %; p=0.01) and work-related MCC (50.9 % vs. 22.7 %; p=0.001) increased significantly compared to the pre-pandemic period. CONCLUSION: The overall burden of MCC increased during the pandemic, and the frequency of MCC involving commercial drivers surged significantly during the pandemic period as opposed to the non-work MCC, which predominated in the pre-pandemic period. Work-related MCCs were more frequent among younger age groups, mainly involving South Asians with frequent accidents in the evening time. However, recreation-related MCCs occurred more frequently at midnight, and victims were non-compliant with the protective gear. Furthermore, there is a need for prospective studies to examine the broader scope of risk factors that are associated with the work-related MCC, especially involving food deliveries, and for focused safety programs for motorcycle delivery drivers and recreational motorcyclists.

The role of public policy in reducing moped and scooter injuries in South Carolina.

INTRODUCTION: Mopeds and electric scooters have grown in popularity in recent years. A South Carolina (SC) law was passed on November 19, 2018, aimed to regulate mopeds and scooters. This study aims to evaluate whether this SC law was associated with a decrease in the moped injury rate in a Level 1 Trauma Center. METHODS: A retrospective review of trauma registry data was used to identify a cohort of patients 14 years and older who came to a Level 1 trauma center for a moped/scooter accident between January 2014 - December 2022. The proportion of moped injuries before and after the passing of the law was calculated. The chi-square test and Wilcoxon Rank Sum test were used to compare differences in proportions for categorical factors and continuous factors, respectively. RESULTS: A total of 350 moped injury cases were identified. There was a significant decrease in the moped injury rate after the passing of the 2018 SC law (0.9 % vs 1.8 %, p<0.001). Additionally, those treated post-law implementation were significantly older (47.4 vs 43.2 years, p = 0.013) and more likely to be male (95.5 % vs 87.9 %, p = 0.025) than those treated pre-law. Patients treated post-law were significantly more likely to be uninsured (45.1 % vs 42.7 %, p = 0.009) and less likely to have commercial (16.2 % vs 20.1 %, p = 0.009), or government (29.7 % vs 35.6 %, p = 0.009) health insurance compared to those treated pre-law. There was no significant difference between the two groups in Glascow Coma Scale, Injury severity score, Trauma Injury Severity Score, or rate of fatalities. CONCLUSION: After the implementation of a SC law, we found that the local proportion of injuries due to moped and scooter accidents was significantly lower than pre-law proportions. These findings suggest that public policies aimed at increasing regulations for mopeds may decrease the rate of injury, but not severity, from moped use.

Near-crash risk identification and evaluation for takeout delivery motorcycles using roadside LiDAR.

The proliferation of motorcycles in urban areas has raised concerns regarding traffic safety. However, traditional sensors struggle to obtain precise high-resolution trajectory data, which hinder the accurate identification and quantification of near-crash risks for takeout delivery motorcycles. To fill this gap, this study presents a novel approach utilizing roadside light detection and ranging (LiDAR) to identify and evaluate the risk of near crashes of takeout delivery motorcycles. First, a trajectory amendment method incorporating speed and steering angle was introduced to enhance the accuracy and continuity of the trajectory prediction. Second, a trajectory prediction method combining the steering intention and a repulsive force model was proposed for near-crash risk prediction. Subsequently, a near-crash identification method was developed that relied on the closest distance and risk radius. Finally, near-crash risk fields were constructed to quantify risk levels by leveraging velocity, position, and weight. The experimental results demonstrated 92.10 % accuracy in intention prediction, with mean absolute error (MAE) and root mean square error (RMSE) values of 0.53 m and 0.45 m, respectively. In addition to its higher accuracy, the proposed method makes it easier to quantify near-crash risk and supports a proactive approach for visualizing and analyzing traffic safety.

Substance use and type of Road Traffic Injury in Mexico City.

Limited data are available in Mexico on the prevalence of alcohol and drug use and the possible differences in their effects on types of road traffic injury (RTI), such as those involving pedestrians, drivers or passengers of motorcycles or other motor vehicles, and the association between substance use and driving behaviors, for preventive purposes. The sample comprised 433 adult RTI patients, admitted to the emergency department (ED) of a public hospital in Mexico City (January to April 2022). Breath Alcohol Concentration (BAC) was measured using a breath tester, and six types of drugs (amphetamines, barbiturates, benzodiazepines, cannabis, cocaine, and methamphetamine) were assessed using a saliva screen test. RTI patients also self-reported their alcohol and drug use in the six hours prior to the accident. Approximately 62% of respondents had been involved in a motorcycle crash. One in three patients self-reported or had traces of a substance in their saliva or breath. The most common substance was alcohol (23.6%), followed by cannabis and stimulants (10.9%). One in five patients reported having used a cell phone ten minutes before the injury. One in three had not been using any safety device, the only behavior exacerbated by substance use. We found a high prevalence of substance use in the sample of RTI patients admitted to the ED, regardless of the type of the RTI, together with high cell phone rates. Motorcycle passengers under the influence were particularly likely not to have been wearing a helmet.

Analysis of increased motorcycle accidents during the COVID-19 pandemic: a single-center study from Türkiye.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic has led to a unique set of circumstances, straining health-care systems and affecting the way of life in societies around the world. Measures such as social isolation, travel restrictions, and workplace closures have led to an increase in motorcycle use. Consequently, motorcycle accidents have become a significant problem during this period. This study presents detailed research conducted to examine motorcycle accidents during the COVID-19 pandemic and to understand the causes and consequences of the increase in these accidents. METHODS: This research evaluated records from a single health examination and used various models to analyze motorcycle acci-dents within a specified time period. Additionally, retrospective analyses were conducted to examine associations between motorcycle use and crashes in our country before and after the pandemic. The records of 386 patients who were injured in motorcycle accidents and followed up, received treatment, and were recorded at Biruni University Hospital between November 2015 and April 2023 were retrospectively examined. Noted details included the victims' age, gender, injury mechanism, injury site, injury severity, helmet use, presence and location of fractures, time distribution of the accident, and the severity of other important tissue injuries. The relationship between the injury site, fractures, and accident details, and the "Injury Severity Score" (ISS) was also investigated. RESULTS: Among the 386 injured victims in motorcycle accidents, 333 were male and 53 were female. Of these, 168 (43.5%) were motorcycle drivers, 137 (35.5%) were motorcycle couriers, and 81 (21%) were pedestrians. A total of 186 (48%) injuries occurred before the pandemic (November 2015-March 2020), while 200 (52%) were sustained during the pandemic. The study indicates a noticeable increase in motorcycle injuries, particularly among motor couriers, especially during the pandemic quarantine periods. Post hoc analysis revealed that motor couriers had significantly lower ISS compared to other professions (p=0.009 and p=0.045, respectively). Motorcyclists who wore helmets were found to have significantly lower ISS than those who did not wear helmets (p<0.05). Furthermore, it was found that the ISS was positively correlated with the number of bone fractures, total soft tissue injury, and significant clinical characteristics (r=0.758, r=0.756, and p<0.001, respectively). CONCLUSION: This clinical study's findings demonstrate that the measures implemented during the pandemic to limit society's mobility have led to an increase in motorcycle accidents. Notably, there has been a significant rise in the number of accidents, particularly involving individual motorcycle use and motorcycle courier services.

Classifying Motorcyclist Behaviour with XGBoost Based on IMU Data.

Human behaviour detection is relevant in many fields. During navigational tasks it is an indicator for environmental conditions. Therefore, monitoring people while they move along the street network provides insights on the environment. This is especially true for motorcyclists, who have to observe aspects such as road surface conditions or traffic very careful. We thus performed an experiment to check whether IMU data is sufficient to classify motorcyclist behaviour as a data source for later spatial and temporal analysis. The classification was done using XGBoost and proved successful for four out of originally five different types of behaviour. A classification accuracy of approximately 80% was achieved. Only overtake manoeuvrers were not identified reliably.