Roadside sobriety testing is an intervention in which police stationed at temporary checkpoints stop motorists in order to conduct a brief sobriety test. Scientific studies provide substantial evidence that the approach reduces rates of alcohol-involved crashes, and general deterrence theory provides a clear mechanism by which the presence of checkpoints will reduce crash rates over the extent of a city. However, despite this strong empirical and theoretical support, and the potential for roadside sobriety testing to greatly reduce rates of alcohol-involved crashes, the approach is underutilized in the United States and important aspects are poorly understood. Critically, police departments have no empirical guidance regarding the optimal spatial configurations (the physical location of checkpoints within cities), temporal configurations (the days and times at which checkpoints are conducted), and site configurations (the number of sobriety tests and duration of the checkpoints) that will maximize reductions in alcohol-involved crashes and minimize law enforcement costs.
The specific aims of this study are to (i) assess the immediate effect and rate of sustained impact over time of individual roadside sobriety testing checkpoints on alcohol-involved crashes within cities, (ii) assess the effect of individual roadside sobriety testing checkpoints on alcohol-involved crashes at multiple spatial scales, and (iii) identify optimal configurations of roadside sobriety testing checkpoints, p, to minimize travel time, t, to alcohol-involved crashes within cities. To achieve these aims we will access detailed checkpoint and crash data from the Australian state of Queensland, a jurisdiction where roadside sobriety testing is widely used and where checkpoint data are available at a spatial and temporal resolution and over a geographic extent that is not possible in the US. Because all roadside sobriety testing programs affect alcohol-involved crashes through the same theoretical mechanism, results will be generalizable to the United States. Selecting all 15 Queensland cities with populations between 10,000 and 500,000, we will calculate counts of checkpoints and crashes at two spatial scales (within cities, and within small Census units nested within the cities). We will use censored regression analyses to assess temporal relationships within cities, and Bayesian conditional autoregressive analyses to assess spatial relationships within Census units and across the extent of cities. We will then use a location-allocation heuristic to identify optimal configurations of checkpoints within cities, and will enumerate the predicted trade-off between benefits (crashes averted) and costs (checkpoints). Based on the results of these analyses, we will produce recommendations to US police departments regarding the optimal spatial, temporal, and site configurations of roadside sobriety checkpoints that minimize burdens on scarce police resources, maximize the effectiveness of existing programs, encourage wider use of roadside sobriety testing, and ultimately reduce rates of alcohol-involved crashes.
The proposed research will assess whether and how different configurations of roadside sobriety testing checkpoints affect rates of alcohol-involved crashes within cities. This information is critical because, although it is clear that jurisdictions with roadside sobriety testing programs have lower rates of alcohol-involved crashes, available evidence provides no guidance for local law enforcement as to where and when they should locate individual checkpoints to maximally reduce crash rates. The results of this study will inform recommendations regarding the best place and time to locate checkpoints within cities, and will therefore directly inform improvements to an intervention with demonstrated public health benefit.
