PW 1469 Approaches to identify hazardous locations for road safety in low-income settings

Background An estimated 23 166 people die from road traffic injuries each year in Bangladesh. Identifying the risk factors, including hazardous locations are the prime concern in addressing the toll of road traffic injuries, which is a major challenge in Bangladesh like other low-income settings. Objective The objective of this study was to explore the process of using road traffic crash data from multiple sources in identifying the hazardous locations with maximum accuracy for future policy direction. Methodology Desk review, physical observation and in-depth interviews were used to document necessary information for the study. Pre-tested structured checklist was used for the desk review and physical observation while semi-structure guideline was used for the in-depth interview. Road condition, engineering factors, epidemiological aspect of crashes, nature of nearby populations and existing safety measures were the key variables. The study was conducted between July and August 2016. Last 8 years’ data (2008–2015) of Ashuganj to Sylhet section of N/2 highway (95 kilometers) was reviewed. Findings It was found that approximately 25–35 people died each year on the selected section during the review period. Major engineering factors were risky curvature (39%); absence of bus bay (19%), sign markings (17%) and hard shoulder (13%); and obstacle for vegetation (12%). Around 42% of pedestrians were unaware about road safety while 29% of victims were engaged in daily activities besides the observed road section. 17% of all vehicles involved in crashes were found to be on high speed. 12 intersections on the observed section were found as hazardous location considering all risk factors. 92% of the identified hazardous locations were matched with the previously identified blackspots by the government using costly advance technologies. Conclusion The approaches used in this study are recommended for identifying hazardous locations to address road traffic crashes in low-income settings considering its cost-effectiveness.