BACKGROUND: Our objective is to evaluate the cost-effectiveness of investments in bike lanes using New York City's (NYC) fiscal year 2015 investment as a case study. We also provide a generalizable model, so that localities can estimate their return on bike lane investments. METHODS AND FINDINGS: We evaluate the cost-effectiveness of bike lane construction using a two-stage model. Our regression analysis, to estimate the marginal addition of lane miles on the expansion in bike ridership, reveals that the 45.5 miles of bike lanes NYC constructed in 2015 at a cost of $8 109 511.47 may increase the probability of riding bikes by 9.32%. In the second stage, we constructed a Markov model to estimate the cost-effectiveness of bike lane construction. This model compares the status quo with the 2015 investment. We consider the reduced risk of injury and increased probability of ridership, costs associated with bike lane implementation and maintenance, and effectiveness due to physical activity and reduced pollution. We use Monte Carlo simulation and one-way sensitivity analysis to test the reliability of the base-case result. This model reveals that over the lifetime of all people in NYC, bike lane construction produces additional costs of $2.79 and gain of 0.0022 quality-adjusted life years (QALYs) per person. This results in an incremental cost-effectiveness ratio of $1297/QALY gained (95% CI -$544/QALY gained to $5038/QALY gained). CONCLUSIONS: We conclude that investments in bicycle lanes come with an exceptionally good value because they simultaneously address multiple public health problems. Investments in bike lanes are more cost-effective than the majority of preventive approaches used today. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
BACKGROUND: Our objective is to evaluate the cost-effectiveness of investments in bike lanes using New York City's (NYC) fiscal year 2015 investment as a case study. We also provide a generalizable model, so that localities can estimate their return on bike lane investments. METHODS AND FINDINGS: We evaluate the cost-effectiveness of bike lane construction using a two-stage model. Our regression analysis, to estimate the marginal addition of lane miles on the expansion in bike ridership, reveals that the 45.5 miles of bike lanes NYC constructed in 2015 at a cost of $8 109 511.47 may increase the probability of riding bikes by 9.32%. In the second stage, we constructed a Markov model to estimate the cost-effectiveness of bike lane construction. This model compares the status quo with the 2015 investment. We consider the reduced risk of injury and increased probability of ridership, costs associated with bike lane implementation and maintenance, and effectiveness due to physical activity and reduced pollution. We use Monte Carlo simulation and one-way sensitivity analysis to test the reliability of the base-case result. This model reveals that over the lifetime of all people in NYC, bike lane construction produces additional costs of $2.79 and gain of 0.0022 quality-adjusted life years (QALYs) per person. This results in an incremental cost-effectiveness ratio of $1297/QALY gained (95% CI -$544/QALY gained to $5038/QALY gained). CONCLUSIONS: We conclude that investments in bicycle lanes come with an exceptionally good value because they simultaneously address multiple public health problems. Investments in bike lanes are more cost-effective than the majority of preventive approaches used today. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Authors: João Costa; Joana Alarcão; Francisco Araujo; Raquel Ascenção; Daniel Caldeira; Francesca Fiorentino; Victor Gil; Miguel Gouveia; Francisco Lourenço; Alberto Mello E Silva; Filipa Sampaio; António Vaz Carneiro; Margarida Borges Journal: Eur Heart J Qual Care Clin Outcomes Date: 2021-03-15
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