Spatial Distribution of Road Traffic Accident at Hawassa City Administration, Ethiopia

  • Shamenna AkliluToma
  • Bedane Ashenafi Senbeta
  • Bedane Ashenafi Senbeta
  • Ali Anteneh Bezabih
Keywords: Hawassa, RTAs, clustering, hotspot, Getis-Ord Gi*, Moran’s I

Abstract

BACKGROUND፡ Globally, road traffic accidents (RTAs) are the leading killer of young people and are projected to be the 7th leading cause of death by 2030. This study is aimed at analyzing the spatial distribution of road traffic accident and identifying hotspot areas across Kebeles (smallest administrative division in Ethiopia) of Hawassa city administration in Ethiopia.
Method: Secondary data on daily traffic accident record from October 2013 to June 2018 was obtained from Hawassa city administration police department. The spatial clustering and hotspots identification were carried through Moran’s I and Getis- Ord Gi* statistics. Data analysis was conducted using GeoDa 1.16.0.0 and ArcGIS 10.2 softwares.
RESULTS: Drivers within age group of 18-30 years, who were hired by private business owners and who had no driving license committed the highest number of traffic accidents. The majority of traffic accidents were caused due to careless driving, failure to give priority for pedestrian, high speed and driver failure to give priority for each other. In addition, about 82.01% of traffic accidents were recorded on asphalts road and 11.51% by gravel road. Spatial clustering of road traffic accidents for accidents occurred on gravel road and in sunny weather conditions found to be significant. Different hotspot areas were identified for gravel type of road and sunny weather condition.
CONCLUSION: The concerned government bodies involved in policymaking are recommended to give special attention to young driver who were hired by private business owners. Interventions to mitigate the occurrence of traffic accident would take in to account the identified hotspot areas.

Published
2021-07-01
Section
Articles

Journal Identifiers


eISSN: 1029-1857
print ISSN: 1029-1857