Prevalence of alcohol-impaired drivers based on random breath tests in a roadside survey in Catalonia (Spain)

Differences in the risk profiles of drunk and drug drivers: Evidence from a mandatory roadside survey

BACKGROUND

The study assesses the prevalence rates of alcohol- and drug-involved driving in Catalonia (Spain).

METHOD

Drivers were randomly selected for roadside testing using a stratified random sampling procedure representative of all vehicles circulating on non-urban roads. Mandatory alcohol and drug tests were performed during autumn 2017. A sample of 6860 drivers were tested for alcohol use, of these 671 were also tested for drugs. Standard procedures were employed by traffic officers to detect alcohol and drug use. Alcohol breath tests were performed with breathalyser devices and on-site drug screening systems were used to test for drugs.

RESULTS

The prevalence of alcohol use above the legal limit and drug use were 1.2 % (95 % CI: 0.9-1.5 %) and 8.3 % (95 % CI: 5.8-11.2 %), respectively. The most frequent drugs detected were THC (5.6 %, 95 % CI: 3.7-8.0 %), cocaine (3.5 %, 95 % CI: 2.0-5.5 %) and amphetamines (1.6 %, 95 % CI: 0.6-3.4 %). Alcohol use was detected more frequently on conventional roads, at weekends and during night-time hours. Drug use was detected more frequently in young males during daytime hours.

CONCLUSIONS

Driver risk profiles associated with alcohol use and drug use differ. Positive alcohol use is not a predictor of drug use when controlling for all other factors.

Semi-autonomous vehicles: Usage-based data evidences of what could be expected from eliminating speed limit violations

The use of advanced driver assistance systems and the transition towards semi-autonomous vehicles are expected to contribute to a lower frequency of motor accidents and to have a significant impact for the automobile insurance industry, as rating methods must be revised to ensure that risks are correctly measured. Telematics information and usage-based insurance research are analyzed to identify the effect of driving patterns on the risk of accident. This is used as a starting point for addressing risk quantification and safety for vehicles that can control speed. The effect of excess speed on the risk of accidents is estimated with a real telematics data set. Scenarios for a reduction of speed limit violations and the consequent decrease in the expected number of accident claims are shown. If excess speed could be eliminated, then the expected number of accident claims could be reduced to half of its initial value, applying the average conditions of the data used in this study. As a consequence, insurance premiums also diminish.

Prevalence of drug use among drivers based on mandatory, random tests in a roadside survey

Background

In the context of road safety, this study aims to examine the prevalence of drug use in a random sample of drivers.

Methods

A stratified probabilistic sample was designed to represent vehicles circulating on non-urban roads. Random drug tests were performed during autumn 2014 on 521 drivers in Catalonia (Spain). Participation was mandatory. The prevalence of drug driving for cannabis, methamphetamines, amphetamines, cocaine, opiates and benzodiazepines was assessed.

Results

The overall prevalence of drug use is 16.4% (95% CI: 13.9; 18.9) and affects primarily younger male drivers. Drug use is similarly prevalent during weekdays and on weekends, but increases with the number of occupants. The likelihood of being positive for methamphetamines is significantly higher for drivers of vans and lorries.

Conclusions

Different patterns of use are detected depending on the drug considered. Preventive drug tests should not only be conducted on weekends and at night-time, and need to be reinforced for drivers of commercial vehicles. Active educational campaigns should focus on the youngest age-group of male drivers.

Copula-based regression modeling of bivariate severity of temporary disability and permanent motor injuries

The analysis of factors influencing the severity of the personal injuries suffered by victims of motor accidents is an issue of major interest. Yet, most of the extant literature has tended to address this question by focusing on either the severity of temporary disability or the severity of permanent injury. In this paper, a bivariate copula-based regression model for temporary disability and permanent injury severities is introduced for the joint analysis of the relationship with the set of factors that might influence both categories of injury. Using a motor insurance database with 21,361 observations, the copula-based regression model is shown to give a better performance than that of a model based on the assumption of independence. The inclusion of the dependence structure in the analysis has a higher impact on the variance estimates of the injury severities than it does on the point estimates. By taking into account the dependence between temporary and permanent severities a more extensive factor analysis can be conducted. We illustrate that the conditional distribution functions of injury severities may be estimated, thus, providing decision makers with valuable information.

Biomolecules and Biomarkers Used in Diagnosis of Alcohol Drinking and in Monitoring Therapeutic Interventions

BACKGROUND

The quantitative, measurable detection of drinking is important for the successful treatment of alcohol misuse in transplantation of patients with alcohol disorders, people living with human immunodeficiency virus that need to adhere to medication, and special occupational hazard offenders, many of whom continually deny drinking. Their initial misconduct usually leads to medical problems associated with drinking, impulsive social behavior, and drunk driving. The accurate identification of alcohol consumption via biochemical tests contributes significantly to the monitoring of drinking behavior.

METHODS

A systematic review of the current methods used to measure biomarkers of alcohol consumption was conducted using PubMed and Google Scholar databases (2010-2015). The names of the tests have been identified. The methods and publications that correlate between the social instruments and the biochemical tests were further investigated. There is a clear need for assays standardization to ensure the use of these biochemical tests as routine biomarkers.

FINDINGS

Alcohol ingestion can be measured using a breath test. Because alcohol is rapidly eliminated from the circulation, the time for detection by this analysis is in the range of hours. Alcohol consumption can alternatively be detected by direct measurement of ethanol concentration in blood or urine. Several markers have been proposed to extend the interval and sensitivities of detection, including ethyl glucuronide and ethyl sulfate in urine, phosphatidylethanol in blood, and ethyl glucuronide and fatty acid ethyl esters in hair, among others. Moreover, there is a need to correlate the indirect biomarker carbohydrate deficient transferrin, which reflects longer lasting consumption of higher amounts of alcohol, with serum γ-glutamyl transpeptidase, another long term indirect biomarker that is routinely used and standardized in laboratory medicine.