Ibrahim M Abdalla1. 1. Department of Statistics, College of Business and Economics, United Arab Emirates University, Al-Ain, P.O. Box 17555, United Arab Emirates. i.abdalla@uaeu.ac.ae
Abstract
INTRODUCTION: This paper examines crash and safety statistics from the Emirate of Dubai in an attempt to identify factors responsible for making this population at greater risk of crashes compared to other countries. PROBLEM: In developing countries such as the United Arab Emirates (U.A.E.), motor-vehicle-related mortalities frequently exceed those of the industrialized nations of North America and Europe. METHOD: Fatality and injury data used in the analysis mainly come from Dubai Emirate police reports and from other relevant international sources. Groups of the population are identified according to associated risk and exposure factors. Influence and strength of the most common risk factors are quantified using relative risk, the Lorenz curve, and the Gini index. Further analysis employed logit modeling, and possible predictors available in Dubai police reports, to estimate probability and odds ratios associated with drivers that are deemed responsible for causing traffic accidents. RESULTS: Traffic fatality risk was found to be higher in Dubai, compared to some developed nations, and to vary considerably between different classes of road users and groups of the resident population. The likelihood of a driver causing an accident is considerably higher for those driving goods vehicles, but it is also associated with other factors. IMPACT: Results provide epidemiological inferences about traffic mortality and morbidity, and suggest priorities and appropriate measures for intervention, targeting resident population.
INTRODUCTION: This paper examines crash and safety statistics from the Emirate of Dubai in an attempt to identify factors responsible for making this population at greater risk of crashes compared to other countries. PROBLEM: In developing countries such as the United Arab Emirates (U.A.E.), motor-vehicle-related mortalities frequently exceed those of the industrialized nations of North America and Europe. METHOD: Fatality and injury data used in the analysis mainly come from Dubai Emirate police reports and from other relevant international sources. Groups of the population are identified according to associated risk and exposure factors. Influence and strength of the most common risk factors are quantified using relative risk, the Lorenz curve, and the Gini index. Further analysis employed logit modeling, and possible predictors available in Dubai police reports, to estimate probability and odds ratios associated with drivers that are deemed responsible for causing traffic accidents. RESULTS: Traffic fatality risk was found to be higher in Dubai, compared to some developed nations, and to vary considerably between different classes of road users and groups of the resident population. The likelihood of a driver causing an accident is considerably higher for those driving goods vehicles, but it is also associated with other factors. IMPACT: Results provide epidemiological inferences about traffic mortality and morbidity, and suggest priorities and appropriate measures for intervention, targeting resident population.