A mixed effects negative binomial analysis of road mortality determinants in Sub-Saharan African countries |
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| Affiliation: | 1. School of Transportation, Southeast University, No. 2 Sipailou, Nanjing 210096, China;2. Department of Economics, University of Massachusetts Amherst, Thompson Hall, 200 Hicks Way, MA 01003, USA;1. Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, 123 University Rd., Sec. 3, Douliu, Yunlin, Taiwan;2. Acer Incorporated, 26F, 116, Sec. 1, Xintai 5th Rd., Xizhi, New Taipei City, Taiwan;1. School of Civil Engineering, The University of Queensland, Brisbane, QLD 4072, Australia;2. Department of IT Management, Faculty of Management, University of Tehran, Tehran, Iran;3. Department of Civil and Environmental Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran;1. University “Alexandru Ioan Cuza”, Faculty of Psychology, Toma Cozma Street, No 3, Iasi 700554, Romania;2. Faculty of Health Sciences, Universidad Europea del Atlántico, C/Isabel Torres, 21, 39011 Santander, Spain;1. Central Queensland University, Appleton Institute for Behavioural Science, 44 Greenhill Road, Wayville, South Australia, Australia;2. University of South Australia, W2-53 Mawson Lakes Campus, Mawson Lakes, South Australia, Australia;1. The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden;2. Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden;3. Department of Computer and Information Science, Linköping University, Linköping, Sweden;1. Department of Defence, Defence Science and Technology Group, Land Division, Edinburgh, Australia;2. University of South Australia, School of Psychology, Social Work and Social Policy, Centre for Sleep Research, Adelaide, Australia;3. University of South Australia, School of Pharmacy and Medical Sciences, Adelaide, Australia;4. Behavioral Biology Branch, Center for Military Psychiatry and Neuroscience Research, Walter Reed Army Institute of Research, Silver Spring, United States;5. Monash University Accident Research Centre, Clayton, Australia |
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| Abstract: | This paper uses aggregate data for a panel of 23 Sub-Saharan African countries to explore the potential predictors of road traffic fatalities between 2001 and 2010. In addition to the Gross Domestic Product per capita, the set of covariates includes some demographic, safe driving behavior, health and infrastructure-related variables. Estimations from a mixed effects negative binomial regression suggest that the fraction of populations aged between 15 and 64 years, the size of the road network and seat belt laws significantly increase fatalities. However, populations of age 65 and above, hospital beds and physicians’ densities, and road audits significantly decrease these fatalities. Moreover, traffic fatalities are found to increase with the Gross Domestic Product per capita. The economic implications of this finding is not to lower the economic growth but to design policies and technologies that could prevent African countries from experiencing the same road tragedy observed in industrialized countries during their development process. |
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| Keywords: | Sub-Saharan Africa Traffic fatalities Mixed effects negative binomial model |
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