Three Essays on Traffic Crashes: Global Health Burdens and Policy Implementations



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The three studies that compose this dissertation explore important issues relating to road traffic accidents in three different geographical areas in the world. The first study in Dallas County, Texas examines community-level social inequity and the risk of pedestrian crashes. Using spatio-temporal Bayesian models, the study identifies the disproportional burden of pedestrian-vehicle crash injuries and fatalities at the community level. However, multilevel models show the disproportional burdens to be statistically suppressed when the information of crash locations is included in the analysis. Findings show that individual crash-level risk factors are more strongly associated with fatal pedestrian crashes than community-level risk factors. The policy implications of the study suggest that municipalities can decrease fatal crashes by installing and maintaining street lights. The second study evaluates the community-based traffic safety program in South Korea. Employing a synthetic control method, the program is found to reduce the number of traffic accidents and injuries, but not the number of traffic accident deaths. All estimated effects are tested with a permutation method and verified by statistical significance. The third study focuses on road traffic accidents in Lagos State, Nigeria. The average travel distance for a car crash victim to reach medical care is established by measuring the distances from a potential crash point to the nearest hospital. Findings show that victims injured at the major-minor road intersections travel shorter distances than ones at the major-residential road intersections. In addition, the average travel distance in suburban areas is almost three and half times longer than in urban areas.



Traffic accidents, Public health--United States, World health, Bayesian field theory