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Background: Only a few cases of bilateral traumatic sternoclavicular dislocations have been reported in the literature. This injury is considered one of the rarest injuries of the human musculoskeletal system. Therefore, we present the first documented case of a cyclist with a third-degree open thoracic trauma (Gustilo–Anderson 3a) associated with a dislocated manubrium sterni fracture in the upper thoracic aperture, bilateral anterior dislocations of the sternoclavicular joints, rib fractures, and pleural ruptures. Case presentation: The patient, a 27-year-old Caucasian male, incurred this injury while participating in a professional cycling race at Nürburgring, Germany and received immediate interdisciplinary surgical treatment and has encountered no complications. We conducted a 1-year follow-up and present the clinical findings of this follow up. Additionally, we conducted a comprehensive review of the existing literature on this injury. Conclusions: Immediate interdisciplinary intervention, including surgical repair and meticulous postoperative care, facilitated successful patient recovery. This underscores the critical role of comprehensive trauma management in complex polytrauma cases. In conclusion, this case report highlights the rarity and complexity of a traumatic injury involving bilateral sternoclavicular dislocation, with this case being the first case reported with concomitant open thorax trauma. Our patient benefited greatly from immediate air-bound transportation to an interdisciplinary care provider, which houses both thoracic and trauma surgery departments. [ABSTRACT FROM AUTHOR]

Most maxillofacial traumas are caused by road traffic collisions and, in particular, by motorcycle accidents. Helmets represent an efficient protective tool in these traumas but they do not provide complete protection. The aim of this study was to perform an epidemiological analysis of facial fractures pattern in relation to the helmet type worn during the accident. The study was a retrospective analysis of 282 patients with a diagnosis of maxillofacial fracture caused by a motorcycle accident. The patients were divided in three groups based on helmet type (Group A: full-face helmet; Group B: modular [half-face] helmet; Group C: open-face helmet). For each group, fractures type and trauma severity, using the Comprehensive Facial Injury (CFI) scale, were recorded. Results showed that isolated midface fractures were strongly related to full-face helmet wearing (p < 0.001), while mandibular fractures and panfacial trauma/combined fractures were negatively correlated (p < 0.001). Mandibular fractures (p < 0.001) and panfacial trauma/combined fractures (p < 0.001) were strongly related to open helmet. Moreover, severe trauma (CFI 8.16) was recorded for open-face helmet wearing. In conclusion, full-face helmet wearing reduced the risk of facial fracture, in particular panfacial trauma/combined fractures, while open-face helmet wearing increased the risk of these fractures. [ABSTRACT FROM AUTHOR]

Road traffic accidents (RTAs) are critical global issue, resulting in over 1.3 million deaths annually, with the burden disproportionately affecting low and middle income countries like Nigeria. Thus, the objective of this paper is to develop a predictive model for Road Traffic Accident Involvement in Southwest Nigeria: A Case Study of Ekiti, Osun, and Oyo States using appropriate standard methods after collecting accident data from relevant agencies for a period of ten years (2014-2023). The results indicate a strong correlation between accident cases and the number of people involved, with fatal and minor accidents having the most significant effects. The model explains 75.5% of the variance in accident outcomes, offering insights into predictive trends that can inform road safety interventions. The study highlights the importance of data-driven approaches in mitigating RTAs and improving road safety management in the study region. Recommendations include stricter traffic law enforcement, enhanced road maintenance, and safety education initiatives to reduce the frequency and severity of accidents in the region. [ABSTRACT FROM AUTHOR]

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Golden jackal is one of the higher trophic level wild animals in rural Bengal. Their ecological significance is undeniable in regional ecosystems and biodiversity. But gradually they become threatened due to habitat contraction, road killing, poisoning and human persecution. The documentation of jackal death by road accident within the 12-km district highway which is a single lane bituminous road in Patshpur-I Community Development Block under Purba Medinipur district, India, reveals an unpredictable ecological circumstance (n-154). Jackals are killed by road accidents from 2022 to 2023. On behalf of this blameless situation, the present study conducted intensive observations, case studies and spatial-ecological analysis. The study also included stakeholder's perceptions to reach and relates the background of this fact. After observation and analysis, it has been found that the jackal deaths have a spatio-temporal signature and are connected with food and forage ground loss from their habitat-influenced area. Another outcome is that roadside habitat becomes an alternative food source and forage ground for them due to trench construction both alongside of the district highway and illegal dumping of meat wastes and domestic wastes. The seasonal biological activities of the jackals, local weather phenomena and car driver negligence are responsible for the accidental death of jackals along the district highway. Considering all the observed factors, the present study shared some reliable measures to control, protect and conserve this animal for balancing regional ecosystem as well as biodiversity in rural Bengal. [ABSTRACT FROM AUTHOR]

Many developing countries have high traffic accident rates due to the mixed traffic environment in which bicycles and motor vehicles travel in the same lanes. This paper examines the perceived risk among road users in mixed traffic. A questionnaire survey was used to obtain demographic information and self-reported risk perception among cyclists, motorcyclists, and drivers. Statistical analyses, including the T-test and ANOVA, were used to examine the relevant differences in risk assessment among the groups. The results demonstrate that the groups differ significantly in sociodemographic characteristics, driving experience, and travel characteristics. For self-reported perceived risk, the respondents' perceptions of road surface conditions, the potential of daydreaming while operating a vehicle, and distraction from passengers or riding companions exhibited significant differences between the groups. The research findings could be beneficial as a guide for policymakers in planning road safety awareness to reduce risk in mixed traffic environments. [ABSTRACT FROM AUTHOR]

Abstract Background Only a few cases of bilateral traumatic sternoclavicular dislocations have been reported in the literature. This injury is considered one of the rarest injuries of the human musculoskeletal system. Therefore, we present the first documented case of a cyclist with a third-degree open thoracic trauma (Gustilo–Anderson 3a) associated with a dislocated manubrium sterni fracture in the upper thoracic aperture, bilateral anterior dislocations of the sternoclavicular joints, rib fractures, and pleural ruptures. Case presentation The patient, a 27-year-old Caucasian male, incurred this injury while participating in a professional cycling race at Nürburgring, Germany and received immediate interdisciplinary surgical treatment and has encountered no complications. We conducted a 1-year follow-up and present the clinical findings of this follow up. Additionally, we conducted a comprehensive review of the existing literature on this injury. Conclusions Immediate interdisciplinary intervention, including surgical repair and meticulous postoperative care, facilitated successful patient recovery. This underscores the critical role of comprehensive trauma management in complex polytrauma cases. In conclusion, this case report highlights the rarity and complexity of a traumatic injury involving bilateral sternoclavicular dislocation, with this case being the first case reported with concomitant open thorax trauma. Our patient benefited greatly from immediate air-bound transportation to an interdisciplinary care provider, which houses both thoracic and trauma surgery departments.

Objectives Ensuring traffic safety is one of the elements of transport policy, it is also directly related to state security – it is a permanent obligation of the state administration to take measures to eliminate the causes of traffic incidents resulting in the loss of life or health of road users and other negative consequences of such accidents. The pedestrian, is particularly vulnerable to loss of life or health as a result of a traffic incident. The main purpose of the article was to identify and establish relationships between variables that significantly determine pedestrian safety at pedestrian crossings. The article takes into account historical data on traffic accidents involving pedestrians in a specific area (analysis), but enriches it with additional information on the specifics of specific pedestrian crossings and identifies relationships between selected variables. A critical analysis of the literature was also carried out. The results of the study are discussed in the last section of the paper, both quantitative and qualitative. Material and methods The article takes into account historical data on traffic accidents involving pedestrians in a specific area (analysis), but enriches it with additional information on the specifics of specific pedestrian crossings and identifies relationships between selected variables. A critical analysis of the literature was also carried out. The results were analyzed and Spearman's correlation strengths were determined. Results Method of analysis, also an analysis of incidents involving pedestrians in 16 selected cities with a population size of 20,000 to 50,000. 515 pedestrian crossings were analyzed. Conclusions Based on the results it was described which pedestrian crossings were the safest and which were the least safe.

Abstract Background Informing humanitarian action directly from community members is recognized as critical. However, collecting community insights is also a challenge in practice. This paper reports data collected among community members and Red Crescent volunteers in the occupied Palestinian territory. The aim was to test a data collection tool, situational judgment tests (SJTs), to collect insights in the community around three themes. Methods The SJTs covered violence prevention, road safety, and environmental pollution (waste), and were constituted of hypothetical scenarios to which respondents indicated how they would react. For each theme, the answers’ pattern provides insights for humanitarian action regarding which beliefs to address. A cross-sectional survey was conducted in January and February 2023 with 656 community members, and 239 Red Crescent volunteers. Results Data showed that violence is the theme for which the need is the highest among community members. Some responses varied according to the public (age, governorate, or disability level), suggesting actions could be tailored accordingly. Conclusions Despite many difficulties during data collection, this study show that the tool allowed to collect community insights, a crucial task to ensure adequate response to the challenges faced by community members and Red Crescent volunteers in occupied Palestine.

Background: Informing humanitarian action directly from community members is recognized as critical. However, collecting community insights is also a challenge in practice. This paper reports data collected among community members and Red Crescent volunteers in the occupied Palestinian territory. The aim was to test a data collection tool, situational judgment tests (SJTs), to collect insights in the community around three themes. Methods: The SJTs covered violence prevention, road safety, and environmental pollution (waste), and were constituted of hypothetical scenarios to which respondents indicated how they would react. For each theme, the answers' pattern provides insights for humanitarian action regarding which beliefs to address. A cross-sectional survey was conducted in January and February 2023 with 656 community members, and 239 Red Crescent volunteers. Results: Data showed that violence is the theme for which the need is the highest among community members. Some responses varied according to the public (age, governorate, or disability level), suggesting actions could be tailored accordingly. Conclusions: Despite many difficulties during data collection, this study show that the tool allowed to collect community insights, a crucial task to ensure adequate response to the challenges faced by community members and Red Crescent volunteers in occupied Palestine. [ABSTRACT FROM AUTHOR]

This study develops a Finite Element Method (FEM) model to evaluate motorcyclist helmet performance, with a focus on stress distribution in the temporal bone region and its impact on brain protection. The model includes an ISI 4151 rated helmet coupled with equivalent head foam mass. Results show that Acrylonitrile Butadiene Styrene (ABS) shells reduce cortical bone impact by 97% through lateral load distribution, while Expanded Polystyrene (EPS) foam absorbs and protects the head. The study also incorporates lateral falls on flat and hemispherical anvils to assess helmet performance in real-life scenarios. These findings contribute to improved helmet design and safety for motorcyclists, enhancing overall rider protection. The analysis highlights the importance of ABS shells in minimising impact on cortical bones and the role of EPS foam in absorbing and mitigating head injury risks. The study's insights inform the development of advanced helmet materials and designs for enhanced safety in motorcycle riding. [ABSTRACT FROM AUTHOR]

Road accidents are on the rise worldwide, causing 1.35 million deaths per year, thus encouraging the search for solutions. The promising proposal of autonomous vehicles stands out in this regard, although fully automated driving is still far from being an achievable reality. Therefore, efforts have focused on predicting and explaining the risk of accidents using real-time telematics data. This study aims to analyze the factors, machine learning algorithms, and explainability methods most used to assess the risk of vehicle accidents based on driving behavior. A systematic review of the literature produced between 2013 and July 2023 on factors, prediction algorithms, and explainability methods to predict the risk of traffic accidents was carried out. Factors were categorized into five domains, and the most commonly used predictive algorithms and explainability methods were determined. We selected 80 articles from journals indexed in the Web of Science and Scopus databases, identifying 115 factors within the domains of environment, traffic, vehicle, driver, and management, with speed and acceleration being the most extensively examined. Regarding machine learning advancements in accident risk prediction, we identified 22 base algorithms, with convolutional neural network and gradient boosting being the most commonly used. For explainability, we discovered six methods, with random forest being the predominant choice, particularly for feature importance analysis. This study categorizes the factors affecting road accident risk, presents key prediction algorithms, and outlines methods to explain the risk assessment based on driving behavior, taking vehicle weight into consideration. [ABSTRACT FROM AUTHOR]

This paper presents an analytical approach to identifying the important characteristics of accident black spots on Moroccan rural roads. An association rule mining method is applied to extract road spatial characteristics associated with fatal accidents. The weighted severity index was calculated for each section, which was then used to determine the severity levels of black spots. The apriori algorithm is applied to find the correlation between road characteristics and the severity levels of black spots. Then, a general rule selection method is proposed to identify the rules strongly associated with each severity level. The results show that the proposed approach is effective in identifying the most important factors contributing to accidents. Furthermore, it shows that the combination of several road characteristics, such as road width, road surface, and bridge presence, may contribute to fatal accidents. The general rule selection found that wet, bad surfaces, and narrow shoulders were significantly associated with accidents on rural roads. The findings of the present study can help develop effective strategies to reduce road accidents and thus improve road safety in the country. [ABSTRACT FROM AUTHOR]

Globally, the quantity of road accidents is steadily decreasing annually. Even if the epidemic has recently had an effect, this number is still quite high. Therefore, every attempt should be made to reduce this number. The purpose of this article is to forecast the number of accidents that will transpire on various kinds of roads in Poland. For this purpose, monthly data on the total number of traffic accidents in Poland broken down by type of road were examined. Based on police data, a forecast was created for the years 2022--2040. A few neural network models were used to predict the frequency of accidents in Poland. The results show that we should keep expecting a high degree of stability in terms of the quantity of traffic accidents. On the one hand, the construction of new highways and the increase in the number of cars on Polish roads have an effect on this. The number of random samples utilized in the processes of learning, testing, and validation affects the results. In the case of 70-15-15, the average projected number of accidents for 2022-2024 should be: motorway - 827, expressway - 1136, 2 one-way carriageway - 5451, single carriageway -3067 and 1 carriageway 2 directions - 28048, respectively. For 80-10-10, these values should be respectively: motorway - 1057, expressway - 1141, 2 one-way carriageway - 5486, single carriageway -2745 and 1 carriageway 2 directions - 28039. As you can see, the values are similar. [ABSTRACT FROM AUTHOR]

Road traffic accidents (RTAs) are critical global issue, resulting in over 1.3 million deaths annually, with the burden disproportionately affecting low and middle income countries like Nigeria. Thus, the objective of this paper is to develop a predictive model for Road Traffic Accident Involvement in Southwest Nigeria: A Case Study of Ekiti, Osun, and Oyo States using appropriate standard methods after collecting accident data from relevant agencies for a period of ten years (2014-2023). The results indicate a strong correlation between accident cases and the number of people involved, with fatal and minor accidents having the most significant effects. The model explains 75.5% of the variance in accident outcomes, offering insights into predictive trends that can inform road safety interventions. The study highlights the importance of data-driven approaches in mitigating RTAs and improving road safety management in the study region. Recommendations include stricter traffic law enforcement, enhanced road maintenance, and safety education initiatives to reduce the frequency and severity of accidents in the region.

Road traffic accidents are of major concern and could be reduced by better education. This paper describes the development of a virtual reality (VR) app that mimics the effects of alcohol on a driver. It was developed using Unity (version 2019.3.14), smartphone and Google Cardboard™. The user experiences a car following a predetermined route that is lined with trees and objects (traffic lights, road signs and other cars) which they need to spot and react to. By using graphical filters and time delays the driver has a feeling of being under the influence of alcohol. Twenty volunteers (18–60 years old; mean age ± sd 25.5 ± 11.6) participated in its evaluation. Data were collected on concentration times, reaction speed and observation of objects in both the alcohol simulated (impaired) and non-simulated (unimpaired) runs. Data were analysed using paired t-test. The result showed that people spent longer concentrating on objects in the impaired vs unimpaired run (10.72 ± 5.07 vs 5.30 ± 4.22 s n:20; p < 0.0001). The average reaction speed to objects in the unimpaired run was lower than in the impaired run (1.44 ± 0.66 vs 2.66 ± 0.28 s n:20; p < 0.001). Seventeen out of twenty subjects spotted all the required objects in the unimpaired whereas only seven out of twenty spotted all the objects in the impaired run (p < 0.001). The authors have shown that an inexpensive VR app can be used to demonstrate to users the effect that alcohol can have on concentration, reaction speeds and observational skills. [ABSTRACT FROM AUTHOR]

Background: Childhood fractures are frequent. The aim of this study was to evaluate their epidemiological and clinical peculiarities in our context. Materials and Methods: This was a retrospective study that focused on the files of children with a fracture. They were aged 0–15 years and received between January 2011 and December 2015 at the Emergency Department of the National Teaching Hospital of Cotonou. Results: Two hundred and eighty fractures were recorded in 257 children. The average age was 8.24 years (7 days–15 years). Older children (6–10 years) were the most affected with 33.8% of cases. The predominance was male (sex ratio = 2.3:1). The aetiologies were dominated by road traffic accidents (45.1%) followed by domestic accidents (42.7%). Fractures were predominant in the lower limbs (52.1%). The most affected segments were the leg (25.4%) and the femur (23.6%). The fracture was open in 13.9% of cases. Conclusion: Childhood fractures interest preferentially the older boys. Then, road traffic accidents are the most frequent circumstances of occurrence in our context. Measures to prevent the main causes of these fractures must be taken, in order to reduce their frequency and ensure the development of children.

There are few road accident studies that use heart rate as an indicator of driver fatigue. This study offers a mathematical regression analysis to discover which independent variables (driving speed, driving duration, body mass index, gender, and types of roads) are significant in influencing the heart rate and how these parameters interact to indicate driver fatigue. The analysis is conducted using a Box-Behnken design by Design Expert software. The results revealed that the values of Prob>F for all variables were less than 0.01%, indicating that all variables influence heart rate significantly. The heart rate increased when driving speed, driving duration, and body mass index (BMI) increased. A similar pattern was observed as the driving path shifted from urban to a moderately difficult uphill/downhill road. However, the pulse rate was reduced when a female driver was replaced by a male driver. The model's accuracy was evaluated by comparing the output data obtained from actual road driving with software prediction. First, the prediction interval of both techniques' output data was within 95%, meeting the minimum quantitative criteria of a 90% predictive interval. Subsequently, the residual errors were less than 10%. The regression model will be useful to shed light on traffic safety measures for preventing fatigue-related road accidents. [ABSTRACT FROM AUTHOR]

Introduction: trauma-related disorders following a road accident have both a health and an economic impact. Methods: we conducted a prospective study to determine the prevalence of these disorders, and to identify risk factors in subjects victims of road accidents and hospitalized in the Department of Orthopedic Surgery and Traumatology of the University Hospital Center of Sfax-Tunisia. Results: a total of sixty-ten subjects were included in this study. The prevalence of acute stress disorder was 37.1% and was associated with female sex, low educational level, previous medical and surgical history, passivity during the accident, severity of injuries and the presence of anxious and depressive symptoms. Post-traumatic stress disorder was observed in 40% of subjects and was associated with urban residential environment, passivity during the accident and anxious and depressive symptoms. Low scores for functional coping strategies and high scores for dysfunctional coping strategies were significantly associated with both disorders. Low educational level, urban residential environment, high levels of anxiety and depression, and denial coping strategy appear to be independent risk factors for acute stress and posttraumatic stress disorder. Conclusion: It is therefore important to determine the profile of people at greater risk of post-traumatic stress disorder, to enable early diagnosis in victims of road accidents. [ABSTRACT FROM AUTHOR]

A surprising number of people die on Polish highways every year. Despite the fact that number is decreasing year after year, it is still rather considerable. Due to the epidemic, the costs of the road accidents were significantly lowered, but they still remain fairly large. Understanding the roads where the majority of accidents happen and the anticipated number of accidents in the next years are necessary to lower this number. The purpose of the article was to forecast the number of accidents that would happen on Polish roads based on the kind of roads. To do this, annual accident statistics from the Police's statistics for the years 2001-2021 were reviewed, and a forecast for the years 2022-2031 was produced. It is clear that either the accident rate is increasing or it is steady. Predictions also suggest that a large increase in accidents on Polish roads may be expected given the current situation. [ABSTRACT FROM AUTHOR]

Background: Childhood fractures are frequent. The aim of this study was to evaluate their epidemiological and clinical peculiarities in our context. Materials and Methods: This was a retrospective study that focused on the files of children with a fracture. They were aged 0–15 years and received between January 2011 and December 2015 at the Emergency Department of the National Teaching Hospital of Cotonou. Results: Two hundred and eighty fractures were recorded in 257 children. The average age was 8.24 years (7 days–15 years). Older children (6–10 years) were the most affected with 33.8% of cases. The predominance was male (sex ratio = 2.3:1). The aetiologies were dominated by road traffic accidents (45.1%) followed by domestic accidents (42.7%). Fractures were predominant in the lower limbs (52.1%). The most affected segments were the leg (25.4%) and the femur (23.6%). The fracture was open in 13.9% of cases. Conclusion: Childhood fractures interest preferentially the older boys. Then, road traffic accidents are the most frequent circumstances of occurrence in our context. Measures to prevent the main causes of these fractures must be taken, in order to reduce their frequency and ensure the development of children. [ABSTRACT FROM AUTHOR]

Road accidents are one of the leading causes of death worldwide. The present study analysed the pattern of road accident deaths in India from the year 2014 till the year 2022. The data was taken from the government website, and we have split it into training and testing datasets. The training dataset was from the year 2014 to 2020, and the forecasting was done for the years 2021 and 2022. We have used the SARIMA model to forecast the number of road accidents in India for the years 2021 and 2022. The accuracy of the SARIMA model in forecasting the number of road accidents in India is also established in the present study. The study has insights for policymakers and administrators. Some of the policies that can be enforced to decrease the number of road accidents in India are better road infrastructure for vehicles across India, enforcement of safety regulations, easy access to trauma care centres, strictly following the speed limits on the road and so on. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between ambient temperature, weather conditions, and types of road accidents in Qazvin province, Iran. The research addresses a significant societal challenge of road accidents, particularly in developing countries like Iran. The objectives are to analyze the correlation between temperature and accident types and to develop a predictive model using data mining techniques. The study employs a quantitative approach, analyzing over 15,000 accident records from 2010 to 2020. The findings reveal a connection between the temperature variable and the type of road accidents as well as weather conditions. Additionally, data mining analysis identifies a predictable pattern among temperature variables, types of road accidents, and weather conditions. Implications of the study underscore the importance of considering temperature and weather conditions as secondary factors influencing accidents. The predictive model can aid decision-makers in formulating effective strategies to reduce accidents. Understanding the relationship between temperature, weather, and accident types enables the design of targeted interventions to enhance road safety. This research contributes valuable insights to accident reduction efforts and emphasizes the significance of addressing environmental variables in road safety planning and policy-making.Moreover, the results of the data mining pattern analysis indicate that car overturning accidents in various weather conditions are the primary type of accidents, followed by chain accidents. However, the types of accidents vary based on different weather conditions and temperatures. The study highlights the intricate connection between weather conditions, temperature, and types of road accidents. By utilizing data mining techniques, the research provides a predictive model for accident patterns, offering valuable insights to enhance road safety strategies.

Road accidents are on the rise worldwide, causing 1.35 million deaths per year, thus encouraging the search for solutions. The promising proposal of autonomous vehicles stands out in this regard, although fully automated driving is still far from being an achievable reality. Therefore, efforts have focused on predicting and explaining the risk of accidents using real-time telematics data. This study aims to analyze the factors, machine learning algorithms, and explainability methods most used to assess the risk of vehicle accidents based on driving behavior. A systematic review of the literature produced between 2013 and July 2023 on factors, prediction algorithms, and explainability methods to predict the risk of traffic accidents was carried out. Factors were categorized into five domains, and the most commonly used predictive algorithms and explainability methods were determined. We selected 80 articles from journals indexed in the Web of Science and Scopus databases, identifying 115 factors within the domains of environment, traffic, vehicle, driver, and management, with speed and acceleration being the most extensively examined. Regarding machine learning advancements in accident risk prediction, we identified 22 base algorithms, with convolutional neural network and gradient boosting being the most commonly used. For explainability, we discovered six methods, with random forest being the predominant choice, particularly for feature importance analysis. This study categorizes the factors affecting road accident risk, presents key prediction algorithms, and outlines methods to explain the risk assessment based on driving behavior, taking vehicle weight into consideration.

The aim of this article is to study the economic and legal means of preventing road accidents abroad, and to determine the possibility and feasibility of incorporating positive foreign experiences into national legislation and legal practice. The subject of research is the economic and legal means of preventing road accidents abroad. The methodology of the publication is based on an organic combination of philosophical, general scientific and specific legal research methods. Taking into account the subject matter, the methodology of comparative jurisprudence is used to a greater extent. Results. The study of foreign experience in the application of economic and legal means of traffic accident prevention gives an idea of the general trends in strengthening the role of economic means of encouraging drivers to observe traffic rules, namely: legal regulation of the dependence of the amount of the fine on the amount of the offender's wages and other income; increasing insurance payments for drivers who systematically violate traffic rules; economic incentives for drivers who observe certain rules during the year; systematic investments in the development of road infrastructure, innovative AI means of traffic regulation, development of public transport; expansion of the network of toll motorways to relieve public roads. It is emphasized that borrowing the experience of foreign countries in the specific field of public relations without scientific substantiation and without taking into account the peculiarities of national traditions, legal consciousness and legal culture cannot solve the key problems of ensuring road safety and preventing road accidents in Ukraine.

Background: Low-and middle-income countries (LMICs) have the greatest road traffic crashes burden, with about 93% of global fatalities occurring in such countries. This situation is partly due to the high level of psychosocial work hazards to which professional drivers are exposed. Therefore, this review aims to map evidence on the psychosocial work factors that influence risky driving behaviours and road traffic crashes in LMICs. Methods: Four main databases (PubMed, Central, Dimensions and JSTOR), in addition to google and google scholar, were searched for records. In all, 6537 records were retrieved and finally, through experts' consultations and a vigorous screening process, 54 studies were included in this review. Included studies sampled 30,272 drivers from 23 LMICs. Results: The reviewed studies found that job strain, efforts-reward imbalance, payments based on performance, lack of social support from supervisors and co-workers, lack of job control from job autonomy and skill discretion, long driving hours, lonely driving, irregular job schedules like shift work and overtime, work-family conflicts, job insecurity and lack of safety motivation are the main psychosocial work factors influencing risky driving behaviours and road traffic crashes among professional drivers in LMICs. Conclusion: Though more quality studies are needed to explore the psychosocial work factors of professional drivers in LMICs, there is a need for occupational health and safety policies for improved working conditions like reduction in workload and long driving hours, access to healthcare and improved psychosocial safety climate.

Road safety is one of the most important global social issues. According to data from the United Nations, every year, around 1.2 million people worldwide die as a result of road accidents; that is, on average, one person dies every 30 seconds. Children and teenagers make up 40% of the fatalities. An additional 30–50 million people are injured as a result of these accidents; some of them become permanently disabled. The main types of accident risks are well documented; they concern a large range of factors, most often related to the behavior of drivers, especially in terms of speed. This article ranks the European Union countries in 2004 and 2018 by their levels of road safety. Four groups of countries are distinguished: very high, moderate, low, and very low levels of road safety.

A surprising number of people die on Polish highways every year. Despite the fact that number is decreasing year after year, it is still rather considerable. Due to the epidemic, the costs of the road accidents were significantly lowered, but they still remain fairly large. Understanding the roads where the majority of accidents happen and the anticipated number of accidents in the next years are necessary to lower this number. The purpose of the article was to forecast the number of accidents that would happen on Polish roads based on the kind of roads. To do this, annual accident statistics from the Police's statistics for the years 2001-2021 were reviewed, and a forecast for the years 2022-2031 was produced. It is clear that either the accident rate is increasing or it is steady. Predictions also suggest that a large increase in accidents on Polish roads may be expected given the current situation.

AbstractThe COVID19 pandemic has significantly affected the performance of the transport sector and its overall intensity. Reduced mobility has a large impact on the number of road accidents. The aim of this study is to forecast the number of road accidents in Poland and to assess the impact of the COVID19 pandemic on the variation in road crashes. For this purpose, day-wise historical crash data from 2011 onwards have been collected and analysed. Based on real historical field data, the future has been forecasted for both pandemic and nonpandemic variants. Forecasting of the number of accidents has been carried out using selected time series models and exponential models. Based on obtained data, it can be stated that pandemic resulted in a decrease in number of road accidents in Poland with ranges of reduction varying from 11% to 30% based on different days of week. Most visible decrease is observed on 3 days viz. Monday, Wednesday, and Saturday. Further, the projections show that in view of the current situation one may expect further decrease in the number of road accidents in Poland.

In Tunisia, the motor insurance industry represents the most important category of damage insurance. In this branch, the fundamental problem is the evolution of the road accident phenomenon. The claim experience in motor insurance is measured in terms of accident frequency. Certainly, the determination of the factors that contribute to the explanation of the loss ratio allows for the improvement of the motor insurance sector. The objective of this study was to analyze the main determinants of claims reported by drivers to their Tunisian insurance companies, as well as the causes of satisfaction of the insured with their insurers. The results show that drivers' behavior is one of the key factors in the causes of claims and that the level of risk coverage helps define the relationship between an insured and his insurer. [ABSTRACT FROM AUTHOR]

BACKGROUND: Traffic road crashes are the leading cause of fatal crashes at work. The circumstances of work-related road accidents have been a regular focus of study, but there is still a lack of knowledge about commuting accidents. OBJECTIVE: The aims of this study were to estimate the overall incidence of commuting accidents for non-physician professionals in a major French university hospital, by gender and different professional categories, and to assess its evolution over a 5-year period. METHODS: A descriptive analysis was performed on 390 commuting accidents from 2012 to 2016 extracted from the university hospital's occupational health service. Incidences of commuting accidents were calculated according to gender, occupational categories, and years. Crude relative risk (RR) for the association of commuting accidents with gender, occupational categories, and year of the accident was also estimated using log-binomial regressions. RESULTS: The annual incidence ranged from 354 to 581 accidents per 100,000 employees. Compared with administrative staff, the relative risk (RR) for commuting accidents for service agents was 1.6 (95% confidence interval (CI): 1.1–2.4) and for auxiliary nurses and childcare assistants was 1.3 (95% CI: 1.0–1.9). Nursing executives had a non-significantly lower RR of 0.6 (95% CI: 0.3–1.5). CONCLUSION: The increased risk observed for the auxiliary nurses and childcare assistants and for the service agents may be related in part to the fatigue caused by work schedules, long commuting distances, physical work, and psychological burden. [ABSTRACT FROM AUTHOR]

The diurnal temperature range (DTR) is a significant indicator of climate change, and a previous study has shown its impact on human health. However, research investigating the influence of DTR on road traffic accidents is scarce. Thus, this study aims to evaluate the impact of changes in DTR on road traffic accidents. The present study employs two methods to address the complexities of road accidents. Firstly, panel data from 20 cities and counties in Taiwan are utilized, and the autoregressive distributed lag (ARDL) model is employed for estimation. Secondly, distributed lag non-linear models (DLNMs) are used with quasi-Poisson regression analysis to assess the DTR's lagged and non-linear relationships with road accidents using time series data from six Taiwanese metropolitan cities. The study results indicate that a decrease of 1 °C in DTR raises long-term road traffic accidents by 17.1%. In the short term, the impact of declining DTR on road accidents is around 4%. Moreover, the effect of low DTR values differs in each city in Taiwan. Three cities had high levels of road accidents, as evidenced by an increase in the relative risk value; two cities had moderate responses; and one city had a relatively lower response compared to high DTR values. Finally, based on the cumulative relative risk estimations, the study found that a low diurnal temperature range is linked to a high road traffic accident rate, especially during the lag-specific 0–5 months. The findings of this study offer fresh evidence of the negative impact of climate factor on road traffic accidents. [ABSTRACT FROM AUTHOR]

The present publication aims to conduct a legal analysis of the mutual influence of road accidents and the national economy, which is manifested at different levels of relevant public relations. The research subject is road accidents and the national economy. The publication’s methodology relies on an organic combination of well-known laws and techniques of dialectics (the transition of quantitative changes into qualitative, unity and struggle of opposites, and the negation of negation), general scientific methods of research (techniques of the logical method, comparative method, techniques of the sociological method, systemic and structural-functional methods), and special legal methods (legal statistics, formal-legal method, methods of comparative jurisprudence and legal modeling). Results. Road safety is inextricably linked with economic processes taking place in a particular state. In addition, as economic indicators affect the number of road accidents so the dynamics and consequences of road accidents significantly affect the national economy. The most important economic factors affecting the number of road accidents are as follows: underdeveloped road infrastructure, outdated vehicle fleet, poor financial and logistic support of law enforcement agencies, insufficient number of traffic enforcement cameras, and other innovative means of preventing road accidents. The priority in traffic accident prevention is the maximum automation of means ensuring road safety: coverage of all key traffic intersections with traffic enforcement cameras, equipment of modern cars with automatic speed limit systems and alcohol intoxication testers, which automatically block the ignition system, the development of a fleet of AI-based self-driving cars and automated traffic control systems. Other economic and administrative means of road accident prevention are equally important, i.e., financial incentives for compliance with traffic rules, development and improvement of public transport efficiency, and investments in multi-level road infrastructure to reduce traffic congestion in available highways and transport interchange.

Road accidents occurred everywhere along the expressway, especially at the inter-urban expressway, due to its high accessibility to wide-ranging highway networks. This study uses dataset from Shah Alam Expressway from 2013 to 2017 to determine the pattern of road accidents which includes the identification of high-risk locations at the expressway as well as the attributes to the accidents at those locations. In order to determine the high-risk location, the weightage point method and accident crash frequency method have been adopted. From the two methods applied, three popular identical sites have been identified as high-risk locations at both the westbound and eastbound. For the west bound, segments 19, 46 and 63 are considered as high risk whereas for the east bound, the high-risk locations are at segments 19, 46 and 60. Most of the accidents at the high-risk locations for west and east bounds caused no injury to road users and happened during daytime. Appropriate countermeasures should be done by local authorities in order to reduce accidents at the above-mentioned area. However, special countermeasures should be considered for segments 8, 28, 31 and 32 at the west bound whereby road accidents frequently happened during nighttime at these locations. On the other hand, a special scheme and countermeasure can be implemented for segment 46 at the eastbound where motorcyclists played a major involvement in road accidents at this location. Future research may consider applying some spatial statistics for detailed analysis to the accident dataset.

Every year, a large number of traffic accidents occur on Polish roads. However, the pandemic of recent years has reduced the number of these accidents, although the number is still very high. For this reason, all measures should be taken to reduce this number. This article aims to forecast the number of road accidents in Poland. Thus, using Statistica software, the annual data on the number of road accidents in Poland were analyzed. Based on actual past data, a forecast was made for the future, for the period 2022-2040. Forecasting the number of accidents in Poland was conducted using selected neural network models. The results show that a reduction in the number of traffic accidents is likely. The choice of the number of random samples (learning, testing and validation) affects the results obtained.

Despite the significant efforts made by the government to reduce traffic accidents in the UAE, there is still a need to understand the root causes of these accidents. Therefore, this research paper investigates the various causes of road accidents in Abu Dhabi city, including circumstantial factors, demographic characteristics, traffic violations, accident faults, and driver behavior. The study employs a GIS statistical approach, namely spatial autocorrelation analysis, to identify the hotspots of traffic accidents in the city for the year 2014. Additionally, a questionnaire survey was conducted in 2017 among drivers involved in road accidents in Abu Dhabi City, which was divided into six major categories: accident-related, seatbelt-related, speed-related, policy-related, and general socio-related. The responses of 1,072 drivers were analyzed using logistical regression models, revealing careless driving as the primary reason for city road accidents. The study also found that age and driving experience had a significant impact on accident probability, indicating that middle-aged drivers were more likely to be involved in accidents and that the risk rate decreased as driving experience increased. The study concludes with suggestions for preventive measures to improve traffic safety in Abu Dhabi City. Finally, the study evaluated the hypothesis that most accidents occur near central business districts using 2014 crash data for Abu Dhabi city. The findings demonstrate the effectiveness of the Getis-Ord Gi* statistic method in pinpointing and ranking high-density vehicle crash areas near the central business district of Abu Dhabi urban settings.