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This study follows an epidemiological approach to examine possible predictors of and current interventions for safety in aviation transportation in two regions with widely different safety records: New York (NY) representing several regions in the US, and Tanzania (Tz), representing several regions in Africa. For most transportation modes, NY has one of the best and Tz has among the worst safety records. This paper identifies some of the similarities and differences between the two regions in order to find ways to improve the safety record in Tz and to ensure that safety continues to improve in NY. Several US, African, and international public and private entities offer that safety is a serious and growing problem, with injuries accounting for approximately 1 in 8 deaths among males and 1 in 14 deaths among females worldwide (MacKenzie, 2000). In addition, they agree that with today’s market globalization, to promote the economy and quality of life of one’s own region, other struggling regions must also be enhanced. Local, national, and global connectivity is required for efficient commerce. Connectivity, in turn, requires ongoing security and safety. By improving transportation safety we may also find cost-effective ways to improve both the NY and Tz regions’ economies and living standards. NY is facing new economic, technological and safety challenges, such as those related to insufficient capacity in all modes of transportation. In NY, and across the US, congestion threatens safety, such as by runway incursions, and hampers economic growth by for example, increased delays or emissions pollution. “The great challenge is that of stimulating capacity growth through increased system efficiency, as infrastructure growth will likely be constrained” (Schubert, 2003). This paper examined some predictors of safety in a preliminary manner, with the assumption that each region’s problems and successes can inform the other. By describing factors such as international and government structures, safety culture, training and retention of the workforce, and statistical reports of accident data, we identify several safety predictors. We suggest that patterns of predictors may emerge that will solve the puzzle of why some regions continue to experience disproportionally high accident rates. Some predictors are common to all regions and modes, such as attempts to introduce and maintain a safety management system, a safety sub-culture, and implement advanced training. While technology improvements are necessary, they may not be sufficient to ensure transportation safety. Funding and government support remain challenges in both regions, although most officials and researchers agree that funding alone is insufficient to address all safety issues. Other predictors vary by context, modifiability and cost-effectiveness. Similarities in some of the accident rates can be found. Our theoretical approach includes examination of the study variables from an epidemiological perspective, where three major levels of variables are examined (see Table 1). In addition, we suggest that competing hypotheses, particularly within the ‘environment’ level of our model, may serve to explain some of the observed differences in accident rates by world region. We suggest that the persistence of high accident rates in East Africa in comparison to the US and specifically New York, is primarily related to the environmental level variable of economics (i.e. relative wealth) of each region. As a result of limited funding, the East African governments are constrained in terms of development of their infrastructure, regulations, policies, training and safety sub-cultures, safety management systems, and availability of technology and equipment. If availability of funding is the issue, and we consider that New York is more economically advantaged than Tanzania, then: In the more advantaged region, we assume that industry-leading technology and equipment would be more readily available and well-funded. Although we would expect to see accidents resulting from all three predictors in Table 1, in the more economically advantaged regions we expect a larger percentage of accidents resulting from the organizational and individual variables (i.e. policies and human factors issues). Additional resources for technologies and equipment may then only have relatively little impact on improving aviation safety in these advantaged regions. In the disadvantaged region, technology and hardware improvements would have a relatively larger impact on aviation safety, as the more fundamental infrastructure issues may be present.