Spatio-temporal analysis of road traffic accident fatality in Bangladesh integrating newspaper accounts and gridded population data

Abstract

Road traffic accidents pose serious threats to human lives and often cause premature deaths, disabilities, and socioeconomic impacts. The objective of this study is to analyze the fatal road traffic accidents in Bangladesh by performing a space–time characterization of fatality rates involving an innovative newspaper-based method in concert with gridded population data to construct a road traffic fatality database. Kernel density estimation, temporal data plots and space–time pattern mining tools that combine the Getis-Ord Gi* statistic with the Mann–Kendall test are used to describe spatio-temporal hotspots/coldspots and trends. Results show different patterns between the urban and rural areas of Bangladesh and higher rates of road traffic accidents occur in the metropolitan regions (Dhaka) and in a northern region centered on Sirajganj area. Most of the road traffic accidents took place in between 9:00 and 12:00 pm while the accident rates remain low between 12:00 and 3:00 am. Spacetime analysis results reveal a core region of persistently high rates along with four smaller regions with high and intensifying rates. The output of this study could be useful to reduce road traffic fatalities, injuries, increase awareness, and adopt necessary interventions for public safety through integrating both the local, regional, and central level decision makers of public transportation policy and issues in Bangladesh. The approach has potential to be translated to other developing countries.