Investigation of road infrastructure and traffic density attributes at high-risk locations for motorcycle-related injuries using multiple correspondence and cluster analysis in urban Tanzania

Abstract

Rapid growth in use of motorcycles combined with limited road infrastructures has increased the burden of road traffic crashes and injuries in low-and middle-income countries. The aim of this study was to assess whether high-risk locations for motorcycle-related injuries identified from police crash data registers for the period 2016 to 2017 share similar road infrastructure and traffic density attributes in Dar es Salaam city. Analysis was performed using multiple correspondence and hierarchical cluster analysis. Three distinct clusters for motorcycle injury hotspots were identified. Clusters 1 and 2 were associated with more fatal and severe injuries and were characterized by overrepresentation of trunk roads, unseparated two-way roads, mixture of road users and commercial and residential areas compared to Cluster 3. Cluster3 was associated with less severe injuries compared to clusters 1 and 2 (p < 0.001). Cluster 3 was characterized by overrepresentation of feeder/street roads, separated two-way roads and presence of traffic control measures. The clusters of hotspots differed by road infrastructure and traffic density attributes. Clusters 1 and 2 were characterized by more dangerous road environments, while cluster 3 was characterized by road environments with less severe outcomes. These findings can assist in prioritizing preventive strategies for motorcycle- related injuries.