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Background: Cost-benefit analysis is a useful tool for priority setting in road safety. The value of statistical life (VOSL) is a metric used to estimate the benefits of road interventions in cost-benefit analyses. The International Road Assessment Program (iRAP), for example, created a rule-of-thumb to calculate VOSL benefits of road infrastructure when performing cost-benefit assessments in countries where data on VOSL are sparse. Aim: To evaluate the rapid assessment metric developed by iRAP and provide suggestions for improvement in these methods. Methods: We replicated iRAP calculations in order to make a critical assessment of the sources, results and conclusions. Conclusions: We found the iRAP metric a good example for highlighting some relevant aspects that should be considered in any VOSL estimation in order to enhance its use as a guiding principle for assessing road interventions. Specifically, we recommend the explicit disclosure of the assumptions, the use of sensitivity analysis and the avoidance of omitted variables bias. [ABSTRACT FROM AUTHOR]

Introduction: Road traffic injuries are the leading cause of death in children over age five. Most of these deaths occur in low- and middle-income countries. Vulnerable road users, such as motorcyclists and their passengers, are at higher risk. Helmets have significantly decreased morbidity and mortality for motorcyclists; however, they are often unused. The second phase of the Bloomberg Philanthropies Initiative for Global Road Safety was launched in 2015 to improve road safety in 10 cities. This study focuses on child passenger helmet use data from that study to understand the prevalence of helmet use and factors that are associated with helmet use.Methods: The 10 cities selected were Accra, Addis Ababa, Bandung, Bangkok, Bogota, Fortaleza, Ho Chi Minh City, Mumbai, Sao Paulo, and Shanghai. Eight rounds of roadside observational data were collected from February 2015 to April 2019. Observers noted correct child motorcycle passenger helmet use and other site observations including weather patterns, traffic volume, and road surface conditions. A multivariable Poisson regression model was used to examine correct helmet use trends over time. A multivariable logistic regression model was fitted for correct child passenger helmet use in all cities controlling for weather, observation time, number of passengers, and driver's correct helmet use.Results: This dataset contained 99,846 motorcycle child passenger observations across the 10 cities. The highest prevalence of correct child passenger helmet use was in Sao Paulo at 97.33%. Six cities had under 25% correct helmet use for child passengers. Examining helmet use over time, only five cities had a significant increase, four cities had no change, and Ho Chi Minh City demonstrated a decrease. In the multivariable regression model, child passengers had higher odds of wearing helmets in adverse weather conditions, early mornings, if the driver wore a helmet, and if there were fewer passengers.Conclusions: The prevalence of correct child passenger helmet utilization shows large variation globally and is concerningly low overall. Enhanced enforcement in combination with media campaigns may have contributed to increasing helmet use prevalence over time. Further research is needed to understand reasons for low child passenger helmet use in most cities. [ABSTRACT FROM AUTHOR]