cost estimation of road traffic injuries among iranian motorcyclists using the willingness to pay method

conclusions willingness to pay can be affected by experiencing an accident, the distance of the daily trip, and helmet use. the cost of traffic injuries among motorcyclists shows that this rate is much higher than the global average. thus, expenditure should be made on effective initiatives such as the safety of motorcyclists. results the mean wtp was 888,110 irr (iranian rial) among motorcyclists. the statistical value of life was estimated according to 4694 death cases as 3,146,225,350,943 irr, which was equivalent to usd 104,874,178 based on the dollar free market rate of 30,000 irr (purchasing power parity). the cost of injury was 6,903,839,551,000 irr, equivalent to usd 230,127,985 (based upon 73,325 injured motorcyclists in 2013, a daily traffic volume of 311, and a daily payment of 12,110 irr for 250 working days). in total, injury and death cases came to 10,050,094,901,943 irr, equivalent to usd 335,003,163. willingness to pay had a significant relationship with having experienced an accident, the length of the daily trip (in km), and helmet use (p < 0.001). background motorcycle riders are amongst some of the most vulnerable road users. the burden of motorcycles injuries from low and middle income countries is under-reported. objectives in this study, the cost of traffic injuries among motorcyclists was calculated using the willingness to pay (wtp) method in iran in 2013. patients and methods in a cross-sectional study, 143 motorcyclists were randomly selected. the research questionnaire was prepared based on the standard wtp method [stated preference (sp), contingent value (cv) and revealed preference (rp) models] taking into consideration perceived risks, especially those in iran. data were collected by a scenario for motorcyclists. the criteria for inclusion in the study consisted of having at least a high school education and being in the age range of 18 - 65 years. the final analysis of the wtp data was performed using the weibull model.