Assessing the Contributing Factors and Distributions of Road Traffic Accident in Arba Minch Town, Gamo Zone, Southern Ethiopia

Road Traffic Accident

Abstract

Road traffic accidents pose a persistent global challenge, with their frequency on the rise. This study aims to examine the contributing factors and spatial-temporal patterns of road traffic accidents in Arba Minch town, located in South Ethiopia. Employing a mixed-method approach, the research utilized descriptive research design for data collection and analysis. Information was gathered through field observations, key informant interviews, focus group discussions, and supplemented by road traffic accident records from Gamo zone and Arba Minch town transport and traffic police office. Spatial analysis techniques such as interpolation, kernel density estimation, and point pattern analysis were employed to assess the distribution of accidents and identify hot spot areas. The findings reveal a high incidence of road traffic accidents in Arba Minch town, with 207 incidents recorded between July 2018 and June 2023. These accidents were primarily attributed to drivers aged 18-30 with 2-10 years of driving experience, occurring predominantly during daytime hours and on Mondays, Thursdays, and Saturdays. Failure to yield to pedestrians, overspeeding, and excessive loading emerged as the primary causes of accident severity in Arba Minch town. Hot spot areas identified include Shecha Daget, around Arba Minch textile factory, Arba Minch University main campus, Arba Minch stadium, in front of Shecha square-Rafael church road, Nechsar Addisu Mesgid, and Sikela around Gamo square. The study underscores the urgent need for targeted traffic law enforcement measures in these identified areas to mitigate the risk of accidents in Arba Minch town.

Keywords: Black Spots/Hotspots, Distance Weighted Road Traffic Accident, Geographic  Information System, Inverse, Kernel Density Estimation