Mapping Road Traffic Crashes in Sfax Governorate (Tunisia)

Sfax is one of the Tunisian governorates with a large number of road accidents, injuries and fatalities every year. This study aimed to analyze and map traffic accidents in this governorate. We analyzed the spatial distribution of accidents, their distribution by cause, by type of road, by size of traffic, by months of the year and days of the week. Accidents were correlated with several variables such as population numbers and densities, motorization rate, length and structure of the road network, and the amount of traffic. On the cartographic level, we have built a database, through which we have produced a series of thematic maps to argue this analysis. Through cartographic production, we also aimed to help road users, decision-makers and researchers in this area and in the field of transport. This work showed that Sfax occupies, among the other Tunisian governorates, an advanced position in gravity. Various human, climatic and technical factors explained this situation, of which human factors were the most important, and contributed to almost 90% of accidents. The current situation of accidents in Sfax requires a series of measures and actions to alleviate and mitigate the gravity of this phenomenon.

Injuries Associated with Auto-Tricycle Crashes in an African City: Incidence and Pattern

Purpose: The aim of this study was to determine the incidence and pattern of injuries resulting from auto-tricycle crashes among patients in a tertiary referral centre in Ghana. Methods: Data were retrospectively extracted from hospital records of patients who got involved in auto-tricycle crashes and presented to the Accident and Emergency Centre of the Komfo Anokye Teaching Hospital (KATH), over a one-year period using a structured questionnaire. The gathered data were then entered into an electronic database and then analysed with SPSS version 20.0. Results: The incidence of injury following auto-tricycle crashes over the one-year period was 5.9% (95% CI: 4.9% - 7.0%) with a case fatality rate (FR) of 3.8% (95% CI: 1.3% - 8.7%). All the mortalities resulted from head and neck injuries and none of the patients involved wore a crash helmet. Only 5% of those studied wore crash helmets and were all drivers. Closed fractures accounted for 58% of the injuries, followed by open fractures, 28%. The most commonly fractured bones were the tibia/fibula, followed by the femur and then radius/ulna. The most common mechanism of injury was auto-tricycle toppling over (29%). Passengers were the most injured (48%), followed by drivers (37%) and pedestrians (15%). Most (72%) injuries among participants involved a single body part. On the injury severity scale, most (61%) of patients had minor trauma and 38% had major trauma. Conclusion: Auto-tricycle crashes account for 5.9% of injuries at the study site with a case fatality rate of 3.8%. Passengers had a higher injury rate (48%) than drivers (37%). Fractures of the tibia/fibula were most commonly associated with auto-tricycle crashes. Injuries to the head and neck were responsible for the deaths in the study participants and non-use of a crash helmet was associated with mortalities.

Workers Survived from Commuting Road Crashes:Who Are They?

Commuting road crashes are road traffic crashes that involve workers while travelling in the course of work.The more worker travels,the higher the probability of the occurrence of commuting road crashes.The aim of this study was to determine baseline sociodemographic,employment and injury and characteristics of injured workers who survived from commuting road crash.Eligible 200 workers who were involved in commuting road crash were identified and invited to be part of this study.Sociodemographic,employment and injury-related questions were distributed to identified and consented injured workers.Majority(79.5%)of the respondents were aged 25 years old or older,male(86.0%),married or divorced(63.5%),and attained secondary and below education level at secondary or below(66.0%).Most of the injured workers consisted of blue-collar workers(69%),had fracture injury(93.0%),and had injury to their lower limbs(48.5%).A higher percentage(63.5%)of injured workers had returned to work compared to those who were still not working(36.5%)after involved in commuting road crash.Commuting road crashes are common to blue collar workers as they are more prone to use motorcycles to commute due to cheaper price compare to other type of transportation such as car.

Prevalence and Factors Associated with Mortality among Chest Injury Patients Admitted at Muhimbili National Hospital in Dar es Salaam, Tanzania

Introduction: Accidents represent a significant proportional of non-communicable disease in the current century, and chest injury is common. However, management and outcome of these injuries is poor in low resource setting like Tanzania. The aim of this study was to determine the prevalence and factors associated with mortality among chest injury patients at a tertiary level health facility in Tanzania. Method: A prospective Cross-Sectional study of chest injuries among trauma patients attended at Muhimbili National Hospital between September 2019 and February 2020. Results: A total of 282 trauma patients were seen, out of which 51/282 (18.1%) sustained chest injury. Road Traffic Crashes were the leading cause of chest injury 41/51 (80.4%). Majority 17/51 (33.3%) presented with lung contusion, followed by pneumohemothorax and rib fractures each 8/51 (15.7%). Most of the patients 27/51 (52.9%) were managed by tube thoracostomy and 42.1% conservatively. Mortality was 11/51 (21.6%). Independent factors associated with mortality were: Associated injuries (Odds Ratio (OR) 0.07, 95% CI 0.01 - 1.16, p = 0.02), Multimodal analgesia (Odds Ratio (OR) 0.22, 95% CI 0.05 - 0.98, p = 0.05), more than 24 hours to treatment (Odds Ratio (OR) 5.53, 95% CI 1.25 - 24.3, p = 0.02), Bilateral chest involvement (Odds Ratio (OR) 4.61, 95% CI 1.12 - 18.7, p = 0.02), and Invasive ventilation (Odds Ratio (OR) 31.5, 95% CI 4.47 - 53.8, p = 0.00). Conclusion: Chest injuries prevail significantly among trauma patients in Tanzania, mostly due to road traffic crashes. Injury preventive measures especially for road traffic crashes need to be reinforced, and establishment of chest injury management protocol in Tanzania.

An epidemiological study on tbe road traffic accidents from hills of north India

Road traffic injuries are increasingly being reported as an important cause of morbidity and disability worldwide.Various epidemio-logic factors related to road traffic crash cases were examined to identify potential targets for future preventative strategies.This hospital-based descriptive study collected relevant information by use of a predesigned and pretested questionnaire given to total of 401 consecutive individuals that received nonfatal injuries from road traffic crashes who reported to the Indira Gandhi Medical College Hospital in Shimla,India between June 2005 to May 2006.The percentage of cases corresponding to preselected catego-ries were compared using chi-square analyzes to determine statistical significance.A majority of the injured victims included in this study were between 20-49 years of age,with a male to female ratio of 5.3:1.The largest numbers of victims were employees and occupants of transport vehicles.Human error was the most reported cause of crash,and the most common mode of crash was skid-ding and/or rolling down.The highest proportion of crashes occurred on curved roads.The most at-risk population in Shimla,India for receiving nonfatal traffic-related injuries is males between 20 and 49 years of age who utilize transport vehicles.As the majority of nonfatal injuries occur in passengers of light transport vehicles(LMVs)in accidents at road curves,road safety strategies should target these locations and the drivers of these vehicles in order to most effectively protect their occupants.

Influence of geometric design characteristics on safety under heterogeneous traffic flow

This paper focuses on analysing the influence of geometric design characteristics on traffic safety using bi-directional data on a divided roadway operated under heterogeneous traffic conditions in India. The study was carried out on a four lane divided inter-city highway in plain and rolling terrain. Statistical modelling approach by Poisson regression and Negative binomial regression were used to assess the safety performance as occurrence of crashes are random events and to identify the influence of the geometric design variables on the crash frequency. Negative binomial regression model was found to be more suitable to identify the variables contributing to road crashes. The study enabled better understanding of the factors related to road geometrics that influence road crash frequency. The study also established that operating speed has a significant contribution to the total number of crashes. Negative binomial models are found to be appropriate to predict road crashes on divided roadways under heterogeneous traffic conditions.

Effectiveness of enforcement levels of speed limit and drink driving laws and associated factors -Exploratory empirical analysis using a bivariate ordered probit model

The contemporary traffic safety research comprises little information on quantifying the simultaneous association between drink driving and speeding among fatally injured drivers. Potential correlation between driver＇s drink driving and speeding behavior poses a substantial methodological concern which needs investigation. This study therefore focused on investigating the simultaneous impact of socioeconomic factors, fatalities, vehicle ownership, health services and highway agency road safety policies on enforce- ment levels of speed limit and drink driving laws. The effectiveness of enforcement levels of speed limit and drink driving laws has been investigated through development of bivariate ordered probit model using data extricated from WHO＇s global status report on road safety in 2013. The consistent and intuitive parameter estimates along with statisti- cally significant correlation between response outcomes validates the statistical suprem- acy of bivariate ordered probit model. The results revealed that fatalities per thousand registered vehicles, hospital beds per hundred thousand population and road safety pol- icies are associated with a likely medium or high effectiveness of enforcement levels of speed limit and drink driving laws, respectively. Also, the model encapsulates the effect of several other agency related variables and socio-economic status on the response outcomes. Marginal effects are reported for analyzing the impact of such factors on in- terrnediate categories of response outcomes. The results of this study are expected to provide necessary insights to elemental enforcement programs. Also, marginal effects of explanatory variables may provide useful directions for formulating effective policy countermeasures for overcoming driver＇s speeding and drink driving behavior.

Driver sleepiness,fatigue,careless behavior and risk of motor vehicle crash and injury:Population based case and control study

Background： A few studies have been conducted to determine the relationship between road motor vehicle crashes （MVC） and serious injuries related to tiredness, fatigues and sleeping. Aim： To determine the effects of aggressive behaviour, driver sleepiness and fatigue on MVC and related injuries among Turkish population. Design and setting： Population-based case and control study conducted at the accident emergency departments of hospitals and roads. Subjects： 515 car drivers involved in crashes with injury were admitted to hospital and 1030 car drivers involved while driving on public roads as control group during the study period. Methods： The Manchester driver behaviour questionnaire （DBQ） measured the aberrant driving behaviours leading to accidents. Participants completed a fatigue severity scale （FSS） and Stanford Sleeping questionnaire an epworth scale with items related to socio-demographic information, driving experiences, adherence to traffic laws （such as speed limits and seat belt）, and drivers＇ driving records. Results： In a representative sampling, participant＇s age ranged from 25 to 65 and the mean and standard deviation were 36.5 _＋ 7.8 for cases and 37.0 4- 8.0 for controls. There was a significant difference in both group of drivers regarding BMI, level of education, marital status, driving experience, seat belt use, excessive speed limits, physical activity number of sleeping hours, mobile phone use, and cigarette smoking habit （p = 0.017）. Also, there was a significant higher mean score on all the DBQ violation questions among case group in comparison with the control group （p 〈 0.001）. Further, cases had higher prevalence of Epworth sleeping disorders （p 〈 0.001） and fatigue severity （p - 0.003） compared to control drivers. Multivariate logistic regression revealed that excessive speed, fatigue, lapses, errors, Stanford sleepiness score, violations, mobile phone use and Epworth sleepiness scale were significantly associated with injury involvement in vehicle crash, after adjusting for driving experience and annual mileage. Conclusion： The current study confirmed that drivers with chronic fatigue, acute sleepiness, and careless driver behavior may significantly increases the risk of road crash which can be lead to serious injury.

An optimization model for improving highway safety

This paper developed a traffic safety management system （TSMS） for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is limited, it is important to identify the best combination of safety improvement projects to provide the most benefits to society in terms of crash reduction. The factors included in the proposed optimization model are annual safety budget, roadway inventory, roadway functional classification, historical crashes, safety improvement countermeasures, cost and crash reduction factors （CRFs） associated with safety improvement countermeasures, and average daily traffics （ADTs）. This paper demonstrated how the proposed model can identify the best combination of safety improvement projects to maximize the safety benefits in terms of reducing overall crash frequency. Although the proposed methodology was implemented on the county paved road network of Wyoming, it could be easily modified for potential implementation on the Wyoming state highway system. Other states can also benefit by implementing a similar program within their jurisdictions.