Optimising the cost-effectiveness of speed limit enforcement cameras.

ABSTRACT

BACKGROUND: Using the 140 speed cameras in New York City (NYC) as a case study, we explore how to optimise the number of cameras such that the most lives can be saved at the lowest cost. METHODS: A Markov model was built to explore the economic and health impacts of speed camera installations in NYC as well as the optimal number and placement. Both direct and indirect medical savings associated with speed cameras are weighed against their cost. Health outcomes are measured in terms of quality-adjusted life years (QALYs). RESULTS: Over the lifetime of an average NYC resident, the existing 140 speed cameras increase QALYs by 0.00044 units (95% credible interval (CrI) 0.00027 to 0.00073) and reduce costs by US$70 (95% CrI US$21 to US$131) compared with no speed cameras. The return on investment would be maximised where the number of cameras more than doubled to 300. This would further increase QALY gains per resident by 0.00083 units (95% CrI 0.00072 to 0.00096) while reducing medical costs by US$147 (95% CrI US$70 to US$221) compared with existing speed cameras. Overall, this increase in cameras would save 7000 QALYs and US$1.2 billion over the lifetime of the current cohort of New Yorkers. CONCLUSION: Speed cameras rank among the most cost-effective social policies, saving both money and lives.