scholarly journals WITHDRAWN: The Road Traffic Injury Treatment Network in Mainland China

2017 ◽  
Author(s):  
Wang Zhengguo ◽  
Zhang Lianyang ◽  
Zhang Liang ◽  
Zhao Wenjun
Keyword(s):  
Road Traffic ◽  
Mainland China ◽  
Road Traffic Injury ◽  
The Road ◽  
Treatment Network ◽  
Traffic Injury ◽  
Injury Treatment

Pedestrian Safety and the Built Environment

2015 ◽  
Vol 30 (4) ◽  
pp. 377-392 ◽  
Author(s):  
Philip Stoker ◽  
Andrea Garfinkel-Castro ◽  
Meleckidzedeck Khayesi ◽  
Wilson Odero ◽  
Martin N. Mwangi ◽  
...  
Keyword(s):  
Built Environment ◽  
Road Traffic ◽  
Pedestrian Safety ◽  
Road Traffic Injury ◽  
Built Environments ◽  
Traffic Crashes ◽  
Road Traffic Crashes ◽  
Urban And Regional Planning ◽  
The Road ◽  
Traffic Injury

Urban and regional planning has a contribution to make toward improving pedestrian safety, particularly in view of the fact that about 273,000 pedestrians were killed in road traffic crashes in 2010. The road is a built environments that should enhance safety and security for pedestrians, but this ideal is not always the case. This article presents an overview of the evidence on the risks that pedestrians face in the built environment. This article shows that design of the roadway and development of different land uses can either increase or reduce pedestrian road traffic injury. Planners need to design or modify the built environment to minimize risk for pedestrians.

scholarly journals Identification of factors affecting the road traffic injury rate

2020 ◽  
Vol 50 ◽  
pp. 735-742
Author(s):  
Gulnara Yakupova ◽  
Polina Buyvol ◽  
Vladimir Shepelev
Keyword(s):  
Road Traffic ◽  
Injury Rate ◽  
Road Traffic Injury ◽  
Factors Affecting ◽  
The Road ◽  
Traffic Injury

scholarly journals A COMBINATION OF GEOSPATIAL AND CLINICAL ANALYSIS IN PREDICTING DISABILITY OUTCOME AFTER ROAD TRAFFIC INJURY (RTI) IN A DISTRICT IN MALAYSIA

2016 ◽  
Vol XLII-4/W1 ◽  
pp. 361-365
Author(s):  
R. Nik Hisamuddin ◽  
R. Ruslan ◽  
N. Syed Hatim ◽  
S. M. Sharifah Mastura
Keyword(s):  
Motor Vehicle ◽  
Road Traffic ◽  
Clinical Analysis ◽  
Road Traffic Injury ◽  
P Value ◽  
The Road ◽  
Pediatric Age Group ◽  
Traffic Injury ◽  
On The Road ◽  
Discharge From Hospital

This was a Prospective Cohort Study commencing from July 2011 until June 2013 involving all injuries related to motor vehicle crashes (MVC) attended Emergency Departments (ED) of two tertiary centers in a district in Malaysia. Selected attributes were geospatially analyzed by using ARCGIS (by ESRI) software version 10.1 licensed to the institution and Google Map free software and multiple logistic regression was performed by using SPSS version 22.0. A total of 439 cases were recruited. The mean age (SD) of the MVC victims was 26.04 years (s.d 15.26). Male comprised of 302 (71.7%) of the cases. Motorcyclists were the commonest type of victims involved [351(80.0%)]. Hotspot MVC locations occurred at certain intersections and on roads within borough of Kenali and Binjai. The number of severely injured and polytrauma are mostly on the road network within speed limit of 60 km/hour. A person with an increase in ISS of one score had a 37 % higher odd to have disability at hospital discharge (95% CI: 1.253, 1.499, p-value < 0.001). Pediatric age group (less than 19 years of age) had 52.1% lesser odds to have disability at discharge from hospital (95% CI: 0.258, 0.889, p-value < 0.001) and patients who underwent operation for definitive management had 4.14 times odds to have disability at discharge from hospital (95% CI: 1.681, 10.218, p-value = 0.002). Overall this study has proven that GIS with a combination of traditional statistical analysis is still a powerful tool in road traffic injury (RTI) related research.

scholarly journals Comparison of Road Traffic Death and Injury Rates at Pedestrian Crossings in Europe

2021 ◽  
Vol 16 (2) ◽  
pp. 16-29
Author(s):  
Julius Uhlmann
Keyword(s):  
Great Britain ◽  
Death Rate ◽  
Road Traffic ◽  
Injury Rate ◽  
Road Traffic Injury ◽  
European Countries ◽  
Injury Rates ◽  
The Road ◽  
Traffic Injury ◽  
Accident Statistics

For this study, accident statistics of 14 European countries were analysed for the number of fatalities and injuries occurring at pedestrian crossings from 2015 to 2017. The road traffic death rate (killed per 1 million inhabitants) and the road traffic injury rate (injured per 1 million inhabitants) at pedestrian crossings were calculated and compared. It was found that there are large differences between the European countries: The road traffic death rate at pedestrian crossings is the lowest in Great Britain and Germany and the highest in Poland and Lithuania. Statistical analysis showed a significant correlation between road traffic death and injury rates at pedestrian crossings.

scholarly journals Identification of Road Traffic Injury Risk Prone Area Using Environmental Factors by Machine Learning Classification in Nonthaburi, Thailand

2021 ◽  
Vol 13 (7) ◽  
pp. 3907
Author(s):  
Morakot Worachairungreung ◽  
Sarawut Ninsawat ◽  
Apichon Witayangkurn ◽  
Matthew N. Dailey
Keyword(s):  
Machine Learning ◽  
Environmental Factors ◽  
Injury Risk ◽  
Road Traffic ◽  
Road Traffic Injury ◽  
Machine Learning Algorithms ◽  
Factors Affecting ◽  
Road Traffic Injuries ◽  
The Road ◽  
Traffic Injury

Road traffic injuries are a major cause of morbidity and mortality worldwide and currently rank ninth globally among the leading causes of disease burden regarding disability-adjusted life years lost. Nonthaburi and Pathum Thani are parts of the greater Bangkok metropolitan area, and the road traffic injury rate is very high in these areas. This study aimed to identify the environmental factors affecting road traffic injury risk prone areas and classify road traffic injuries from an environmental factor dataset using machine learning algorithms. Road traffic injury risk prone areas were set as the dependent variables for the analysis, with other factors that influence road traffic injury risk prone areas being set as independent variables. A total of 20 environmental factors were selected from the spatial datasets. Then, machine learning algorithms were applied using a grid search. The first experiment from 2017 in Nonthaburi and Pathum Thani was used for training the model, and then, 2018 data from Nonthaburi and Pathum Thani were used for validation. The second experiment used 2018 Nonthaburi data for the training, and 2018 Pathum Thani data were used for the validation. The important factors were grocery stores, convenience stores, electronics stores, drugstores, schools, gas stations, restaurants, supermarkets, and road geometrics, with length being the most critical factor that influenced the road traffic injury risk prone model. The first and second experiments in a random forest model provided the best model environmental factors affecting road traffic injury risk prone areas, and machine learning can classify such road traffic injuries.

Claimant Lawyer Use in Road Traffic Injury Compensation Claims

2020 ◽  
Vol 43 (1) ◽  
Author(s):  
Clare E Scollay ◽  
Janneke Berecki-Gisolf ◽  
Becky Batagol ◽  
Genevieve M Grant
Keyword(s):  
Empirical Investigation ◽  
Road Traffic ◽  
Road Traffic Injury ◽  
Access To Justice ◽  
Compensation Scheme ◽  
Factors Associated ◽  
The Road ◽  
Traffic Injury ◽  
Compensation Claims ◽  
Do So

In injury compensation schemes, claimants engage lawyers to navigate the claiming process, access benefits, and resolve disputes. As a result, lawyers can play a central role in facilitating claimant access to entitlements, and shaping claimant experiences and outcomes. This article presents findings from the largest empirical investigation of lawyer use in a single compensation scheme: using evidence from almost 50,000 claims in the road traffic injury scheme in Victoria, Australia, the socio-demographic, crash, injury, and recovery factors associated with lawyer use are identified, and explanations for these relationships explored. The analysis shows that some claimants who struggle to access lawyers in other contexts are supported to do so in this scheme. The findings highlight opportunities for improving access to justice within and outside compensation settings.

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