Article ID: | iaor20108287 |
Volume: | 43 |
Issue: | 1 |
Start Page Number: | 421 |
End Page Number: | 428 |
Publication Date: | Jan 2011 |
Journal: | Accident Analysis and Prevention |
Authors: | Sukhai Anesh, Jones Andrew P, Love Barnaby S, Haynes Robin |
Keywords: | transportation: road, time series & forecasting methods, behaviour |
The annual road traffic fatality (RTF) burden of 43 deaths per 100000 inhabitants in South Africa (SA) is disproportionately high in comparison to the world average of 22 per 100000 population. Recent research revealed strong geographical variations across district councils in the country, as well as a substantial peak in mortality occurring during December. In this study, the factors that explain temporal variations in RTFs in SA are examined. Using weekly data from the period 2002–2006 for the country's nine provinces, non‐linear auto‐regression exogenous (NARX) regression models were fitted to explain variations in RTFs and to assess the degree to which the variations between the provinces were associated with the temporal variations in risk factors. Results suggest that a proportion of the variations in weekly RTFs could be explained by factors other than the size of the province population, with both temporal and between‐province residual variance remaining after accounting for the modelled risks. Policies directed at reducing the effects of the modifiable risks identified in our study will be important in reducing RTFs in SA.