Traffic Accidents Research Articles

Impact of socioeconomic determinants on road traffic accidents in Tunisia: insights from the dynamic ARDL and machine learning approaches

ABSTRACT Road traffic accidents are responsible for 1.35 million deaths, and road safety is the part of sustainable development goals, which aims to provide a safe, accessible, affordable, and sustainable transport system by 2030. Despite significant efforts made by the Tunisia government to reduce traffic accidents, there is still a need to understand the root causes of these accidents. This study examines the relationship between road traffic fatalities, economic growth, total mileage of highways, private vehicle ownership, and urbanization in Tunisia from 2000 to 2023. This study employs novel estimation techniques, including dynamic autoregressive distributed lag (DARDL) simulations and Kernel-based Regularized Least Squares (KRLS), to capture the counterfactual shocks in road traffic fatalities. The DARDL results revealed that 1% increase in economic growth, urbanization, and private car ownership leads to a 0.316%, 0.371% and 0.347% rise in road traffic accidents in the long-run, respectively. The KRLS results indicate that economic growth and private vehicle ownership have a positive marginal effect on road traffic fatalities. Specifically, an increase in private vehicle ownership consistently raises traffic fatalities across all percentiles. In contrast, the effect of total highway mileage is initially positive, leading to an increase in accidents, but turns negative in the later stages. Additionally, the frequency domain causality results show that economic growth granger causes road accident for frequencies corresponding to long-term (0.93–1.00) and medium-term (1.03–1.50) horizons. Urbanization granger causes road accident in the medium term (1.69 to 1.97) and short term (2.01 to 2.63). Private vehicle Granger-causes road accident for frequencies between 0.00 and 0.89 in the long run and between 1.03 and 1.73 in the medium term. The governments should include traffic education as part of syllabus from primary to higher studies. Government should create awareness about the loss due to road crashes.

Preventing the disaster: severe abdominal injury in child passengers of motor vehicle accidents often indicate even more serious trauma

PurposeThe purpose of this study was to assess severe abdominal injury in child passengers of different ages of motor vehicle accidents and analyze the concomitant pattern of injury regarding injury severity, trauma management and outcome.MethodData acquisition from Trauma Register DGU® (TR-DGU) in a 10-years period (2010–2020) of seriously injured children (max. AIS 2+ / intensive care) 0–15 years of age, as motor vehicle passengers (cMVP) (n = 1,035). Primarily treated in or transferred to a German Trauma Center. Matched pairs analysis with adult severely injured motor vehicle passengers (aMVP) (age 20–50 years, n = 26,218), matching 1:4 (child: adult), was performed to identify causes of mortality.ResultsThe study group (cMVP) included 1,035 children. The mean age was 9.5 years, 50.5% were male and the mean Injury Severity Score (ISS) was 18.7 points. 93.0% were transported from scene directly to the final trauma center. Transferred patients showed a higher ISS (26 vs. 18 points), higher rate of severe traumatic brain injury (TBI), a higher rate of serious abdominal injury and a higher mortality rate (12.5% vs. 7.4%). Most of the severe abdominal injuries occurred after the third year of age (first peak between 8 and 9 years; second peak 14–15 years). Serious injuries to the pelvis show a similar distribution but less often, the same applies to thoracical injuries. Severe brain and head injuries show an antiproportional distribution to the age groups with the highest rate in the 0–1 year old (78%) and the lowest in the 14–15 year old (40%). The highest mortality rate was shown in the youngest age groups, related to TBI (AISTBI ≥ 3; 62% in 0–1 years). The matched pairs analysis shows a higher mortality rate of cMVP compared to aMVP within the first 24 h after hospital admission and a significantly higher rate of shock and unconsciousness, while the intubation rate is significantly lower.ConclusionChild passengers of motor vehicle accidents are in need of a specific and age-related attention towards security systems. Severe injuries in children are rare, yet life threatening. The highest mortality rate is related to severe TBI, especially in the youngest children. But also severe abdominal as well as thoracic injuries their concomitant trauma need to be prevented and are indicators for even more severe injuries. It seems to be favorable for cMVP to be directly transported to designated special centers with sufficient capacity and competency to treat and manage severely injured children.

Exploring teamwork, trust, and emergency response competence in emergent ad-hoc immediate responder groups: an experimental simulation study

People in the immediate vicinity of an accident sometimes provide first aid as immediate responders and may form spontaneous groups to provide aid together. Previous research has found conflicting results where first aid is sometimes improved and sometimes unaffected by the cooperation in these groups. This study investigated the effect of competence and the teamwork factors leadership, coordination and swift trust on first aid team performance in immediate responder groups. Ad-hoc groups of three participants with mixed or low emergency response competence acted in a simulated traffic accident. Swift trust and emergency response competence increased first aid performance while leadership and coordination did not. Low competence groups were also found to overestimate their team performance while mixed competence groups were found to underestimate their team performance. Further research should investigate how to support swift trust within these groups and explore potential education interventions for improving the effect of teamwork.

The Role of Autopsy in Diagnosing Fatal Chest Injuries in Road Traffic Accidents: A Literature Review

The Role of Autopsy in Diagnosing Fatal Chest Injuries in Road Traffic Accidents: A Literature Review

Traffic Accidents in the Municipalities of North-Eastern Libya (Derna-Alqubba-Shahat-Albayda) Their Causes and Factors for Treating and Reducing Them

Traffic Accidents in the Municipalities of North-Eastern Libya (Derna-Alqubba-Shahat-Albayda) Their Causes and Factors for Treating and Reducing Them

Criteria for trauma team activation and staffing requirements for the management of patients with (suspected) multiple and/or severe injuries in the resuscitation room– a systematic review and clinical practice guideline update

PurposeOur aim was to update the evidence-based and consensus-based recommendations on criteria for trauma team activation (TTA) and staffing requirements for the management of patients with (suspected) multiple and/or severe injuries in the resuscitation room on the basis of available evidence. This guideline topic is part of the 2022 update of the German Guideline on the Treatment of Patients with Multiple and/or Severe Injuries.MethodsMEDLINE and Embase were systematically searched to August 2021. Further literature reports were obtained from clinical experts. Randomised controlled trials, prospective cohort studies, cross-sectional studies and comparative registry studies were included if they compared criteria for identifying severely injured patients requiring trauma team activation or different staffing components (e.g. team composition, training) for the management of patients with (suspected) multiple and/or severe injuries in the resuscitation room. We considered patient relevant outcomes such as mortality as well as prognostic accuracy outcomes. Risk of bias was assessed using NICE 2012 checklists. The evidence was synthesised narratively, and expert consensus was used to develop recommendations and determine their strength.ResultsTwenty-one new studies were identified. Potential trauma team activation criteria included vital signs (e.g. systolic blood pressure), type and extent of injury (e.g. central gunshot wound), mechanism of injury (e.g. traffic accident), interventions (e.g. chest tube), specific criteria for geriatric patients, and combined criteria (N = 20). Staffing requirements for the resuscitation room included specific training for orthopaedic trainees (N = 1). Two recommendations were modified, and six additional recommendations were developed. All but two recommendations achieved strong consensus.ConclusionThe key recommendations address the following topics: inter-professional trauma teams in the resuscitation room; trauma team activation for geriatric patients; and trauma team activation criteria based on physiological, anatomical, interventional, and mechanism of injury parameters.

Therapeutic path of Brazilians with spinal cord injury until rehabilitation

The start of rehabilitation directly affects the effectiveness of treatment. This is a quantitative, exploratory, analytical, and cross-sectional study, with 618 Brazilian adults with spinal cord injury (SCI). Participants were predominantly male (68.90%), with a mean age of 38.04 years (SD = 9.85), with higher education (49.50%), receiving social security benefits (63.60%), and with a monthly income of up to 3 minimum wages (55.10%). The main cause of SCI was traffic accident (40.80%) and 58.70% of the participants had paraplegia. Moreover, 19.40% had not undergone any rehabilitation and the mean time to start rehabilitation after SCI was 17.68 months (SD = 38.80). Participants with the highest level of education were 4.30 times more likely to undergo rehabilitation. The results suggest that those who were more educated and with higher income also had greater access to rehabilitation programs and sought these programs earlier. In contrast, those with less resources had fewer opportunities for rehabilitation. The optimization of referral systems in the health care network, outreach programs, and a greater supply of rehabilitation centers can increase access to rehabilitation among people with SCI.

The Rare Presentation of Traumatic Intracranial Hypotension: A Case Report

AbstractCerebrospinal fluid (CSF) provides buoyant support to the brain and spinal cord. According to the Monroe-Kellie doctrine, confined space in the cranium causes any change in CSF volume contributing to significant intracranial pressure changes, which cause a variety of pathologies and symptoms. We, hereby, present a case of a 33-year-old gentleman who after a motorcycle road traffic accident came to us complaining of persistent headache and neck pain with subdural hematoma (SDH) like presentation, clinically and radiologically, but was reevaluated and diagnosed as traumatic intracranial hypotension and successfully managed surgically after that. Hygromas are believed to be compensatory enlargement of the subdural space due to the loss of CSF volume. The true mechanism of the development of SDH or hygroma due to intracranial hypotension is yet to be hypothesized but provisionally described by a rupture of the bridging veins by being pulled away from the dura because of the low intracranial pressure (ICP) and brain descent. Many prior cases in the literature are shown to have treated the patient with immediate burr hole and decompression of SDH, but this paradoxically worsens the patient due to further lowering of ICP. The causes of prolonged postconcussion headaches are often unidentified, of which intracranial hypotension caused by a CSF leak is potentially under-recognized. In such cases, bilateral SDH with mass effect must be ruled out of any CSF leak before attempting the lifesaving decompressive surgery, as it may paradoxically lead to further morbidity and mortality of the patient.

The Role of Mobile Phone Distraction in Road Traffic Accidents

Studies have indicated that death as a result of road traffic accidents will rise to fifth position globally by 2030. This has generated much concern among road safety professionals, traffic engineers and policy makers. Several factors such as over speeding, drink-drive, distraction, fatigue, overloading, brake failure, pot holes, poor geometric design, poor visibility, and so on are some of the causes of road traffic accident. Currently, the use of mobile phone while driving has been shown to be one of the leading causes of driver’s distraction. Therefore, this paper presents a review on the audio and visual activities involving mobile phone while driving and their contributions to road traffic accident. Based on the articles consulted during this work, it has been shown that both the audio and visual activities involving mobile phone usage during driving have significant influence on driver’s performance by increasing reaction time, shortening headway, changing lane position and so on. However, these negative driving behaviours were shown to be riskier during visual activities like texting and accessing social media application such as Facebook, Telegram, WhatsApp, and so on.

Analysis of Road Traffic Accidents Trend in Rift Valley Region Kenya: Causing Factors and Preventive Measures

Analysis of Road Traffic Accidents Trend in Rift Valley Region Kenya: Causing Factors and Preventive Measures

Integrating Cultural Norms and Behavioral Risk Factors into Traffic Accident Mitigation: A Hybrid MCDM Approach for Libya

Integrating Cultural Norms and Behavioral Risk Factors into Traffic Accident Mitigation: A Hybrid MCDM Approach for Libya

An Intelligent Driver Tracking and Driving Analysis Reporting System

As the number of vehicles on the roads increases day by day, the number of traffic accidents also increases. According to Turkish Statistical Institute (TÜİK) 2023 data, 88.9% of these accidents are caused by driver errors. These mistakes of drivers usually occur because they are careless, tired, sleepy, or busy with a different task while driving. At this point, the need for the use of smart systems in vehicles has begun. Intelligent vehicle systems have been developed to warn drivers during these behaviors. These systems aim to provide the driver with a safer driving experience. Looking at the literature, studies have been done on this subject and embedded systems have been developed. The general purpose of these studies is to ensure safe driving by warning the driver while driving. The proposed intelligent driver tracking and driving analysis reporting system in this study is designed mostly for companies in the freight and passenger transportation sector. In order to prevent traffic accidents caused by driver error, the aim is to conduct a driving analysis of commercial vehicle drivers and report them to the transportation company, thus minimizing traffic accidents by choosing more careful drivers or ensuring that the drivers are more careful. The proposed system consists of two cameras placed inside the vehicle, facing with the driver and traffic, recording video throughout the drive. The video recording is uploaded to the driving analysis reporting software, two separate videos are passed through two separate models and the results are displayed in a meaningful format. While carrying out the project, two different models are created. While the first of these models detects the driver's behavior such as sleepiness, making a phone call, or smoking, the second analyzes whether the vehicle complies with the speed limits and traffic lights. These analyses are presented in the form of reports with a user-friendly interface. In this way, it is aimed to ensure a safer traffic flow by preventing accidents caused by drivers.

Functional outcomes of patients presenting with traumatic hip dislocations at a tertiary care center: a descriptive observational study.

Traumatic hip dislocations (THD) often result from high-energy trauma and are frequently associated with fractures of the femoral head, shaft, or acetabulum. Effective management, including timely hip relocation, is essential for favorable outcomes. However, limited literature exists on the functional outcomes of THD, especially in resource-limited settings like Nepal. This study aimed to evaluate the functional outcomes of patients with complex THDs treated at a tertiary care centre in Nepal. This descriptive observational study included 80 patients with complex THDs treated between October 2012 and July 2023. Eligible patients had follow-ups ranging from 6months to over five years. Data on patient demographics, injury characteristics, treatment details, and functional outcomes were collected. The Harris Hip Score (HHS) was used to assess functional outcomes, with scores categorized as "good" (≥ 80) or "poor" (< 80). Statistical analysis used logistic regression to identify factors associated with better functional outcomes. In this study of 80 patients with traumatic hip dislocations (THD), the majority were male (82.5%) and aged under 40years (53.8%), with road traffic accidents being the predominant cause (73.8%). Most injuries involved posterior dislocations (87.5%), and 76.3% had associated acetabular fractures. Good functional outcomes, defined as a Harris Hip Score (HHS) ≥ 80, were achieved in 83.8% of cases, while 16.3% had poor outcomes. Logistic regression analysis revealed several significant factors associated with better outcomes: a hospital stays of less than three weeks (OR 4.67, 95% CI 1.08-20.21, p = 0.04), anterior dislocation (OR 12.17, 95% CI 1.12-131.70, p = 0.04), and follow-up duration of less than five years (OR 0.07, 95% CI 0.01-0.43, p = 0.00). However, acetabular fractures had a significantly lower likelihood of good outcomes (OR 0.28, 95% CI 0.08-0.96, p = 0.04). Timely management of traumatic hip dislocations, such as early discharge and treatment of associated fractures, is vital for achieving favorable functional outcomes, as reflected in the Harris Hip Score. These findings offer valuable insights for optimizing care in resource-limited settings and highlight the necessity for long-term follow-up, especially for patients with more complex injuries.

Localized inverse design in conservation laws and Hamilton-Jacobi equations

Consider the inverse design problem for a scalar conservation law, i.e., the problem of finding initial data evolving into a given profile at a given time. The solution we present below takes into account localizations both in the final interval where the profile is assigned and in the initial interval where the datum is sought, as well as additional a prioriconstraints on the datum’s range provided by the model. These results are motivated and can be applied to data assimilation procedures in traffic modeling and accidents localization.

Short-term effectiveness of expert adolescent lateral femoral nail fixation for femoral shaft fractures in older children and adolescents

To investigate short-term effectiveness of using expert adolescent lateral femoral nail (EALFN) in treating femoral shaft fractures in older children and adolescents. A retrospective analysis was conducted on the clinical data of 17 patients with femoral shaft fractures who met the inclusion criteria and were admitted between July 2020 and June 2024. All fractures were fixed with EALFN after reduction. There were 11 males and 6 females, with a mean age of 13.3 years (range, 11-16 years). The average body weight was 51.2 kg (range, 40-84 kg), and the average height was 162.1 cm (range, 150-172 cm). The causes of injury included traffic accidents ( n=9), falling from height ( n=1), and simple falls ( n=7). One patient had an open fracture treated with an external fixator and experienced delayed fracture healing. The remaining patients were closed fractures, with an average time from injury to operation of 5.8 days (range, 2-10 days). Operation time and postoperative hospital stay were documented. During follow-up, X-ray films were taken to observe the fracture healing, and the bilateral femoral length, femoral neck-shaft angle, widest femoral neck diameter (FND), and articular trochanteric distance (ATD) were measured at last follow-up. Hip function was assessed using the Harris score. The differences in the all indicators between the healthy and affected sides were compared. The operation time ranged from 65 to 130 minutes (mean, 94.1 minutes). Postoperative hospital stay ranged from 5 to 40 days (mean, 16.7 days). All patients were followed up 7-36 months (mean, 14.4 months). One patient exhibited delayed fracture healing during follow-up. The distal locking nail was removed at 6 months after operation, and partial weight-bearing was initiated following dynamic fracture stabilization. The fracture healing was achieved, and the intramedullary nail was removed at 24 months after operation. The other fractures healed with the healing time of 6-20 months (mean, 9.6 months), and the intramedullary nails were removed. During follow-up, no femoral fracture, abnormal development of the greater trochanter, or ischemic necrosis of the femoral head occurred. At last follow-up, there was no significant difference in femoral length, femoral neck-shaft angle, FND, ATD, or Harris score between the affected and healthy sides ( P>0.05). For older children and adolescents with femoral neck fractures, the application of EALFN fixation aligns more closely with the principles of intramedullary central fixation and rapid rehabilitation. This approach is associated with fewer complications and superior short-term effectiveness.

Using cluster analysis to investigate consumption patterns in cases positive to ketamine: a national 7-year study.

The use of ketamine has increased; however, actual consumption patterns and ketamine-related deaths remain poorly understood. This study aimed to (1) cluster the consumption patterns of individuals who consume ketamine and (2) investigate their associations with manner and cause of death. A retrospective study was conducted on all cases positive to ketamine at death, retrieved from the Institute of Forensic Medicine between 2013 and 2019. A total of 414 individuals tested positive for ketamine in various samples, including blood, pleural effusion, hair, and others, with 294 individuals having detectable ketamine in their blood samples, which were subsequently clustered. The most prevalent patterns identified were ketamine plus alcohol (49.5%), ketamine plus new psychoactive substances (39.1%), and ketamine plus methamphetamine (24.4%). Drug intoxication was the most reported cause of death, followed by traffic accidents. Cluster 1 exhibited moderate ketamine concentrations (1.7µg/mL), a high prevalence of polydrug use (85%), and an increased risk of suicide. Cluster 4 displayed very low ketamine concentrations (0.13 µg/mL) but similarly high rates of polydrug use (85%) and an elevated risk of accidental death. The concurrent use of ketamine and alcohol, primarily categorized within cluster 3, accounted for nearly half of the deaths resulting from drug intoxication or traffic accidents. Our study underscores the potential dangers of using ketamine as one of multiple substances. Our study also emphasized the critical role that consumption patterns and dosages play in determining the potential lethal outcomes associated with ketamine. In the future, medical applications of ketamine must consider patients' use of other substances and inform them of the associated risks.

Riding with distraction: Exploring the intention and behaviour of smartphone use while riding among motorcyclists in Vietnam.

Riding with distraction: Exploring the intention and behaviour of smartphone use while riding among motorcyclists in Vietnam.

Tp-yolov8: a lightweight and accurate model for traffic accident recognition

Tp-yolov8: a lightweight and accurate model for traffic accident recognition

Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion

Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vigilant. We call this driver sleepiness. This results in numerous unfavourable circumstances that negatively impact people’s life. The identification of driver fatigue and the appropriate handling of such information is the primary objective of this study. Ongoing developments in AI (artificial intelligence) as well as ML (machine learning) within ADAS (Advanced Driver Assistance Systems) have made the application of Internet-of-Things (IoT) technology in driver action recognition necessary. These advancements are dramatically changing the driving experience. This study suggests a novel method for machine learning-based automatic driving change-based drowsiness detection. In this instance, the multi-body sensor detects the driver’s EEG signal and gathers information for brain activity analysis. The wavelet time frequency transform model has been used to examine this signal in order to classify patterns of brain activity. A multi-layer convolutional programmed transfer VGG-16 neural network was then used to classify this examined pattern. This classified signal will cause the automatic driving mode to change. In terms of prediction accuracy, sensitivity, specificity, RMSE, ROC, experimental analysis has been performed for a variety of EEG signal datasets. The goal of this work is to reduce the risks that come with driving while drowsy which will improve road safety and reduce incidents that are related to fatigue.

Drive Sentinel: A System that Watches Over and Protects Drivers

With the rapid increase in automobile usage, road accidents have also risen, highlighting the need for an effective accident prevention and detection system. This system detects driver drowsiness and yawning using facial analysis and alerts the user to prevent accidents. Additionally, a microcontroller continuously monitors vehicle parameters. The system doesn’t solely record the vehicle parameters data of the automobile periodically, but also actively monitors for any sudden vehicle accident detection. This system aims to alert the nearby medical center about the accident to provide immediate medical aid. The attached accelerometer in the vehicle senses the tilt of the vehicle to understand the seriousness of the accident. Upon detection, it sends real-time alerts via GSM and GPS to emergency contacts and the nearest medical center. Key Words: Raspberry Pi, Drowsiness alert, Accident Detection alert, GPS, GSM, Accelerometer