Analysis of young driver crash data. Report to the Research Council of Oman, Muscat

Road traffic crashes are an alarming public health issue in Oman, despite ongoing improvements in traffic law enforcement practices and technology. One of the main target groups for road safety in Oman are young drivers aged 17-25 years. This report provides an overview of the characteristics of crashes in Oman involving young drivers (17-25 years) between 1st January 2009 and 31st December 2011. Although, young drivers aged 17-25 years comprise around 17% of all licence holders in Oman, they represented more than one third of all drivers involved in road traffic crashes in the country. A total of 11,101 young drivers (17-25 years) were involved in registered crashes during the study period. From this, 7,727 young drivers (69.6%) were found to be the cause of the crashes...

Licensing system in Oman and literature review. Report to the Research Council of Oman, Muscat

This document reviews the existing literature in the area of novice driver behaviour and the impact of Graduated Driver Licencing (GDL) as a key response to young driver management. The document focuses on consolidating the available research evidence and identifying existing gaps in the current knowledge. The chapter reviews novice driver crash risk, the factors that influence novice driver behaviour, countermeasures used to address the problem, the learner phase, the provisional phase, The Australian example of GDL, compliance with the road laws and parental involvement in the GDL process...

Heavy vehicle crash characteristics in Oman, 2009-2011

In recent years, Oman has seen a shift in the burden of diseases towards road accidents. The main objective of this paper, therefore, is to describe key characteristics of heavy vehicle crashes in Oman and identify the key driving behaviours that influence fatality risks. Crash data from January 2009 to December 2011 were examined and it was found that of the 22,543 traffic accidents that occurred within this timeframe, 3,114 involved heavy vehicles. While the majority of these crashes were attributed to driver behaviours, a small proportion was attributed to other factors. The results of the study indicate that there is a need for a more thorough crash investigation process in Oman. Future research should explore the reporting processes used by the Royal Oman Police, cultural influences on heavy vehicle operations in Oman, and improvements to the current licensing system.

A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010

BACKGROUND Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time. METHODS We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. FINDINGS In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2-7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5-7·0]), and alcohol use (5·5% [5·0-5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8-9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6-8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4-6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2-10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0·9% (0·4-1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania. INTERPRETATION Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children.

Road safety and pavement management: A case study of Tanzania

The implementation of pavement management seems to ignore road safety, with its focus being mainly on infrastructure condition. Safety management as part of pavement management should consider various means of reducing the frequency of vehicle crashes by allocating corrective measures to mitigate accident exposure, as well as reduce accident severity and likelihood. However, it is common that lack of accident records and crash contributing factors impedes incorporating safety into pavement management. This paper presents a case study for the initial development of pavement management systems considering data limitations for 3000 km of Tanzania’s national roads. A performance based optimization utilizes indices for safety and surface condition to allocate corrective measures. A modified Pareto analysis capable of accounting for annual performance and of balancing resources to achieve good surface condition and low levels of safety was applied. Tradeoff analysis for the case study found the need to assign 30% relevance to condition and 70% to road safety. Safety and condition deficiencies were corrected within 5 years with the majority of improvements dedicated to surface treatments and some geometric corrections. Large investments for correcting geometric issues were observed in years two and three if more money was made available.

A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Social influences on risky driving behaviours among young drivers in Oman

Young drivers represent approximately 20% of the Omani population, yet account for over one third of crash injuries and fatalities on Oman's roads. Internationally, research has demonstrated that social influences play an important role within young driver safety, however, there is little research examining this within Arab gulf countries. This study sought to explore young driver behaviour using Akers' social learning theory. A self-report survey was conducted by 1319 (72.9% male and 27.1% female) young drivers aged 17-25 years. A hierarchical regression model was used to investigate the contribution of social learning variables (norms and behaviour of significant others, personal attitudes towards risky behaviour, imitation of significant others, beliefs about the rewards and punishments offered by risky behaviour), socio-demographic characteristics (age and gender), driving experience (initial training, time driving and previous driving without supervision) and sensitivity to rewards and punishments upon the self-reported risky driving behaviours of young drivers. It was found that 39.6% of the young drivers reported that they have been involved in at least one crash since the issuance of their driving licence and they were considered ‘at fault’ in 60.7% of these crashes. The hierarchical multiple regression models revealed that socio-demographic characteristics and driving experience alone explained 14.2% of the variance in risky driving behaviour. By introducing social learning factors into the model a further 37.0% of variance was explained. Finally, 7.9% of the variance in risky behaviour could be explained by including individual sensitivity to rewards and punishments. These findings and the implications are discussed.

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.

Prevalence and characteristics of road traffic injuries among young drivers in Oman, 2009-2011

Objectives Studies from different parts of the world have indicated that the impact of road traffic incidents disproportionally affects young adults. Few known studies have been forthcoming from Arabian Gulf countries. Within Oman, a high proportion of the population is under the age of 20. Coupled with the drastic increase of motorization in recent years there is a need to understand the state of road safety among young people in Oman. The current research aimed to explore the prevalence and characteristics of road traffic injuries among young drivers aged 17-25 years. Methods Crash data from 2009-2011 was extracted from the Directorate General of Traffic, Royal Oman Police (ROP) database in Oman. The data was analyzed to explore the impact of road crashes on young people (17-25 years), the characteristics of young driver crashes and how these differ from older drivers and to identify key predictors of fatalities in young driver crashes. Results Overall, young people were over-represented in injuries and fatalities within the sample time period. While it is true that many young people in crashes were driving at the time, it was also evident that young people were often a victim in a crash caused by someone else. Thus, to reduce the impact of road crashes on young people, there is a need to generally address road safety within Oman. When young drivers were involved in crashes they were predominantly male. The types of crashes these drivers have can be broadly attributed to risk taking and inexperience. Speeding and night time driving were the key risk factors for fatalities. Conclusion The results highlight the need to address young driver safety in Oman. From these findings, the introduction of a graduated driver licensing system with night time driving restrictions could significantly improve young driver safety.

Proposed vehicle impact speed: Severe injury probability relationships for selected crash types

Speed is recognised as a key contributor to crash likelihood and severity, and to road safety performance in general. Its fundamental role has been recognised by making Safe Speeds one of the four pillars of the Safe System. In this context, impact speeds above which humans are likely to sustain fatal injuries have been accepted as a reference in many Safe System infrastructure policy and planning discussions. To date, there have been no proposed relationships for impact speeds above which humans are likely to sustain fatal or serious (severe) injury, a more relevant Safe System measure. A research project on Safe System intersection design required a critical review of published literature on the relationship between impact speed and probability of injury. This has led to a number of questions being raised about the origins, accuracy and appropriateness of the currently accepted impact speed–fatality probability relationships (Wramborg 2005) in many policy documents. The literature review identified alternative, more recent and more precise relationships derived from the US crash reconstruction databases (NASS/CDS). The paper proposes for discussion a set of alternative relationships between vehicle impact speed and probability of MAIS3+ (fatal and serious) injury for selected common crash types. Proposed Safe System critical impact speed values are also proposed for use in road infrastructure assessment. The paper presents the methodology and assumptions used in developing these relationships. It identifies further research needed to confirm and refine these relationships. Such relationships would form valuable inputs into future road safety policies in Australia and New Zealand.

Pavement management: Capturing surface treatment effectiveness

Acquiring detailed knowledge of surface treatments effectiveness is required to improve performance-based decisions for allocating resources to preserve and maintain pavements on any road network. Measurement of treatment effectiveness is a complex task that requires historical records of treatments with observations of before and after performance trends. Lack of data is often an obstacle that impedes development and incorporation of surface maintenance treatments into pavement management. This paper analyzes the effect of surface treatments on asphalt paved arterial roads for several control sections of New Brunswick. The method uses a Transition Probability Matrix to capture main effects by mapping mean trends of surface improvement and pavement structure decay. It was found that surface treatments have an immediate effect reducing the rate of loss of structural capacity. Pavements with international roughness index (IRI) smaller than 1.4 m/km did not seem to benefit from surface treatments. Those with IRI higher than 1.66 m/km gained from 6 to 8 years of additional life. Reset value for surface treatments fall between 1.18 and 1.29 m/km. This paper aims to serve to practitioners seeking to capture and incorporate effectiveness of surface treatments (i.e., crack-sealing) into Pavement Management.

Molecular diversity of Chickpea chlorotic dwarf virus in Sudan: High rates of intra-species recombination – a driving force in the emergence of new strains

In Sudan Chickpea chlorotic dwarf virus (CpCDV, genus Mastrevirus, family Geminiviridae) is an important pathogen of pulses that are grown both for local consumption, and for export. Although a few studies have characterised CpCDV genomes from countries in the Middle East, Africa and the Indian subcontinent, little is known about CpCDV diversity in any of the major chickpea production areas in these regions. Here we analyse the diversity of 146 CpCDV isolates characterised from pulses collected across the chickpea growing regions of Sudan. Although we find that seven of the twelve known CpCDV strains are present within the country, strain CpCDV-H alone accounted for ∼73% of the infections analysed. Additionally we identified four new strains (CpCDV-M, -N, -O and -P) and show that recombination has played a significant role in the diversification of CpCDV, at least in this region. Accounting for observed recombination events, we use the large amounts of data generated here to compare patterns of natural selection within protein coding regions of CpCDV and other dicot-infecting mastrevirus species.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Thin nanoporous metal-insulator-metal membranes

Insulating nanoporous materials are promising platforms for soft-ionizing membranes; however, improvement in fabrication processes and the quality and high breakdown resistance of the thin insulator layers are needed for high integration and performance. Here, scalable fabrication of highly porous, thin, silicon dioxide membranes with controlled thickness is demonstrated using plasma-enhanced chemical-vapor-deposition. The fabricated membranes exhibit good insulating properties with a breakdown voltage of 1 × 107 V/cm. Our calculations suggest that the average electric field inside a nanopore of the membranes can be as high as 1 × 106 V/cm; sufficient for ionization of wide range of molecules. These metal–insulator–metal nanoporous arrays are promising for applications such soft ionizing membranes for mass spectroscopy.