State or market? How to effectively decrease alcohol-related crash fatalities and injuries

Background It is estimated that more than 270 000 people die yearly in alcohol-related crashes globally. To tackle this burden, government interventions, such as laws which restrict blood alcohol concentration (BAC) levels and increase penalties for drunk drivers, have been implemented. The introduction of private-sector measures, such as ridesharing, is regarded as alternatives to reduce drunk driving and related sequelae. However, it is unclear whether state and private efforts complement each other to reduce this public health challenge. Methods We conducted interrupted time-series analyses using weekly alcohol-related traffic fatalities and injuries per 1 000 000 population in three urban conglomerates (Santiago, Valparaíso and Concepción) in Chile for the period 2010–2017. We selected cities in which two state interventions—the ‘zero tolerance law’ (ZTL), which decreased BAC, and the ‘Emilia law’ (EL), which increased penalties for drunk drivers—were implemented to decrease alcohol-related crashes, and where Uber ridesharing was launched. Results In Santiago, the ZTL was associated with a 29.1% decrease (95% CI 1.2 to 70.2), the EL with a 41.0% decrease (95% CI 5.5 to 93.2) and Uber with a non-significant 28.0% decrease (95% CI −6.4 to 78.5) in the level of weekly alcohol-related traffic fatalities and injuries per 1 000 000 population series. In Concepción, the EL was associated with a 28.9% reduction (95% CI 4.3 to 62.7) in the level of the same outcome. In Valparaíso, the ZTL had a −0.01 decrease (95% CI −0.02 to −0.00) in the trend of weekly alcohol-related crashes per 1 000 000 population series. Conclusion In Chile, concomitant decreases of alcohol-related crashes were observed after two state interventions were implemented but not with the introduction of Uber. Relationships between public policy interventions, ridesharing and motor vehicle alcohol-related crashes differ between cities and over time, which might reflect differences in specific local characteristics