Shannon Erdelyi

Reduction in Fatalities, Ambulance Calls, and Hospital Admissions for Road Trauma After Implementation of New Traffic Laws

OBJECTIVES We evaluated the public health benefits of traffic laws targeting speeding and drunk drivers (British Columbia, Canada, September 2010). METHODS We studied fatal crashes and ambulance dispatches and hospital admissions for road trauma, using interrupted time series with multiple nonequivalent comparison series. We determined estimates of effect using linear regression models incorporating an autoregressive integrated moving average error term. We used neighboring jurisdictions (Alberta, Saskatchewan, Washington State) as external controls. RESULTS In the 2 years after implementation of the new laws, significant decreases occurred in fatal crashes (21.0%; 95% confidence interval [CI]=15.3, 26.4) and in hospital admissions (8.0%; 95% CI=0.6, 14.9) and ambulance calls (7.2%; 95% CI=1.1, 13.0) for road trauma. We found a very large reduction in alcohol-related fatal crashes (52.0%; 95% CI=34.5, 69.5), and the benefits of the new laws are likely primarily the result of a reduction in drinking and driving. CONCLUSIONS These findings suggest that laws calling for immediate sanctions for dangerous drivers can reduce road trauma and should be supported.

The Association between Regional Environmental Factors and Road Trauma Rates: A Geospatial Analysis of 10 Years of Road Traffic Crashes in British Columbia, Canada

Background British Columbia, Canada is a geographically large jurisdiction with varied environmental and socio-cultural contexts. This cross-sectional study examined variation in motor vehicle crash rates across 100 police patrols to investigate the association of crashes with key explanatory factors. Methods Eleven crash outcomes (total crashes, injury crashes, fatal crashes, speed related fatal crashes, total fatalities, single-vehicle night-time crashes, rear-end collisions, and collisions involving heavy vehicles, pedestrians, cyclists, or motorcyclists) were identified from police collision reports and insurance claims and mapped to police patrols. Six potential explanatory factors (intensity of traffic law enforcement, speed limits, climate, remoteness, socio-economic factors, and alcohol consumption) were also mapped to police patrols. We then studied the association between crashes and explanatory factors using negative binomial models with crash count per patrol as the response variable and explanatory factors as covariates. Results Between 2003 and 2012 there were 1,434,239 insurance claim collisions, 386,326 police reported crashes, and 3,404 fatal crashes. Across police patrols, there was marked variation in per capita crash rate and in potential explanatory factors. Several factors were associated with crash rates. Percent roads with speed limits ≤ 60 km/hr was positively associated with total crashes, injury crashes, rear end collisions, and collisions involving pedestrians, cyclists, and heavy vehicles; and negatively associated with single vehicle night-time crashes, fatal crashes, fatal speeding crashes, and total fatalities. Higher winter temperature was associated with lower rates of overall collisions, single vehicle night-time collisions, collisions involving heavy vehicles, and total fatalities. Lower socio-economic status was associated with higher rates of injury collisions, pedestrian collisions, fatal speeding collisions, and fatal collisions. Regions with dedicated traffic officers had fewer fatal crashes and fewer fatal speed related crashes but more rear end crashes and more crashes involving cyclists or pedestrians. The number of traffic citations per 1000 drivers was positively associated with total crashes, fatal crashes, total fatalities, fatal speeding crashes, injury crashes, single vehicle night-time crashes, and heavy vehicle crashes. Possible explanations for these associations are discussed. Conclusions There is wide variation in per capita rates of motor vehicle crashes across BC police patrols. Some variation is explained by factors such as climate, road type, remoteness, socioeconomic variables, and enforcement intensity. The ability of explanatory factors to predict crash rates would be improved if considered with local traffic volume by all travel modes.