Abstract
Road traffic injuries (RTIs) are a major public health challenge, accounting for significant
injury, economic and psycho-social burden to societies across the world. While decreases
are projected for many high-income countries (HICs) over the next decade or so, staggering
increases in the burden of mortality and morbidity are forecast for low- and middle-income
countries (LMICs). The unique contextual influences on RTIs in LMICs are, however, not well
understood. Conceptual frameworks applied mostly to HICs also do not provide adequate
recognition of the unique contextual influences of LMICs.
Accordingly, the research in this thesis adopts a predominantly geographical approach to
incorporate a large range of physical and social environmental effects, and which are
aggregated at different spatial and spatial-temporal scales to understand the contextual
influences to road traffic injuries (RTIs) in the South African (S.A) setting. In this regard, four
studies are presented; these include: a geographical epidemiology and risk analysis at the
district council level and for time, space and population aggregations; an integrated spatialtemporal
analysis at the province-week level; a fine-scale geographical analysis at the police
area level; and a small area analysis at the suburb level for the city of Durban.
In addition to important effects relating to alcohol and travel exposure, findings have
shown most environmental influences on RTIs in S.A to be development-related, including
effects relating to social and area deprivation, violence and crime, and rurality. With the
exception of rurality, the above effects showed a positive association with the occurrence
of RTIs in S.A. The findings have implications for alignment and possible integration of road
safety policies and practices with other developmental policies in the country. In addition,
this research has shown that geographical approaches may provide a useful analytical
framework for understanding the complexity and interacting influences within broader
systems-based approaches; and especially those of the contextual environment that are
particularly relevant for LMIC settings
