The Impact of Aging Drivers and Vehicles on the Injury Severity of Crash Victims.

Against a general trend of increasing driver longevity, the injuries suffered by vehicle occupants in Spanish road traffic crashes are analyzed by the level of severity of their bodily injuries (BI). Generalized linear mixed models are applied to model the proportion of non-serious, serious, and fatal victims. The dependence between vehicles involved in the same crash is captured by including random effects.

Hospitalizations from covid-19: a health planning tool.

Objective: Estimate the future number of hospitalizations from Covid-19 based on the number of diagnosed positive cases.

Method: Using the covid-19 Panel data recorded in Spain at the Red Nacional de Vigilancia Epidemiológica, Renave (Epidemiological Surveillance Network), a regression model with multiplicative structure is adjusted to explain and predict the number of hospitalizations from the lagged series of positive cases diagnosed from May 11, 2020 to September 20, 2021. The effect of the time elapsed since the vaccination program starting on the number of hospitalizations is reviewed.

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.

Does longevity impact the severity of traffic crashes? A comparative study of young-older and old-older drivers.

Introduction: This article analyzes the effect of driver's age in crash severity with a particular focus on those over the age of 65. The greater frequency and longevity of older drivers around the world suggests the need to introduce a possible segmentation within this group at risk, thus eliminating the generic interval of 65 and over as applied today in road safety data and in the automobile insurance sector.

Method: We investigate differences in the severity of traffic crashes among two subgroups of older drivers -young-older (65-75) and old-older (75+), and findings are compared with the age interval of drivers under 65.

A discrete mixture regression for modeling the duration of non-hospitalization medical leave of motor accident victims.

Studies analyzing the temporary repercussions of motor vehicle accidents are scarcer than those analyzing permanent injuries or mortality. A regression model to evaluate the risk factors affecting the duration of temporary disability after injury in such an accident is constructed using a motor insurance dataset. The length of non-hospitalization medical leave, measured in days, following a motor accident is used here as a measure of the severity of temporary disability.

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).

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.

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

Sobriety checkpoints are not usually randomly located by traffic authorities. As such, information provided by non-random alcohol tests cannot be used to infer the characteristics of the general driving population. In this paper a case study is presented in which the prevalence of alcohol-impaired driving is estimated for the general population of drivers.

Beyond Value-at-Risk: GlueVaR Distortion Risk Measures.

We propose a new family of risk measures, called GlueVaR, within the class of distortion risk measures. Analytical closed-form expressions are shown for the most frequently used distribution functions in financial and insurance applications. The relationship between GlueVaR, value-at-risk, and tail value-at-risk is explained.

Factors affecting hospital admission and recovery stay duration of in-patient motor victims in Spain.

Hospital expenses are a major cost driver of healthcare systems in Europe, with motor injuries being the leading mechanism of hospitalizations. This paper investigates the injury characteristics which explain the hospitalization of victims of traffic accidents that took place in Spain. Using a motor insurance database with 16,081 observations a generalized Tobit regression model is applied to analyse the factors that influence both the likelihood of being admitted to hospital after a motor collision and the length of hospital stay in the event of admission.

Discrete distributions when modeling the disability severity score of motor victims.

Many European countries apply score systems to evaluate the disability severity of non-fatal motor victims under the law of third-party liability. The score is a non-negative integer with an upper bound at 100 that increases with severity. It may be automatically converted into financial terms and thus also reflects the compensation cost for disability.