Causal models for road accident fatalities in Yemen.
An identification of the causes of road accident fatalities is becoming more important with the growth of technology, population, number of vehicles and the need for their use. Many authors have addressed the problem in the past but no universal findings have been obtained. The problem tends to be different under different environments and for different geographical regions. The aim of this paper is to develop a model for the analysis and forecasting of road accident fatalities in Yemen considering data restrictions. The proposed data has a particular structure of accident occurrence that has not been reported in any existing research using data in other countries. The available data for the period 1978-1995 is used to build models to understand the nature and extent of the causes of fatalities. Part of the data is used for model building and part of it for test purposes. The issues of correlation and causality have been addressed and multiple collinearity is investigated and dealt with. Two alternative models are proposed based on both statistical grounds and that of practicality in viable decision making. The influence of consuming a locally grown stimulant called Qat on road users has been addressed and it is found that it increases the risk of accidents. This is not the common understanding within the authorities in Yemen as growing and consuming Qat is unregulated.
Ameen JRM
Division of Mathematics and Statistics, School of Technology, University of Glamorgan, Pontypridd, UK.
Naji
J A
JA
D000063:Accidents, Traffic / Q000401:mortality* / Q000517:prevention & control* / Q000706:statistics & numerical data; D015984:Causality; D005544:Forecasting; D006801:Humans; D015233:Models, Statistical; D012044:Regression Analysis; D015006:Yemen / Q000453:epidemiology