ABSTRACT
Smeed's equation is a widely used model for prediction of traffic fatalities but has been inadequate for use in developing countries. We applied regression analysis to time-series data on vehicles, exponential models for fatality prediction, producing an average absolute error of 20.9% for Qatar, 10.9% for population and traffic fatalities in the United Arab Emirates (UAE), Jordan and Qatar. The data were fitted to Jordan and 5.5% for the UAE. We found a strong linear relationship between gross domestic product and fatality rate.
Subject(s)
Accidents, Traffic/mortality , Automobiles/statistics & numerical data , Developing Countries/economics , Economic Development/trends , Population Growth , Regression Analysis , Accidents, Traffic/trends , Bias , Cause of Death , Humans , Jordan/epidemiology , Least-Squares Analysis , Linear Models , Population Surveillance , Predictive Value of Tests , Qatar/epidemiology , United Arab Emirates/epidemiologyABSTRACT
Smeed's equation is a widely used model for prediction of traffic fatalities but has been found inadequate for use in developing countries. We applied regression analysis to time-series data on vehicles, population and traffic fatalities in the United Arab Emirates [UAE], Jordan and Qatar. The data were fitted to exponential models for fatality prediction, producing an average absolute error of 20.9% for Qatar, 10.9% for Jordan and 5.5% for the UAE. We found a strong linear relationship between gross domestic product and fatality rate
