Identification and Modeling Human Factors Risks in Kenyan and Ugandan Aviation Operations

Abstract

Safety performance is much poorer in developing countries when one compares to other countries worldwide, despite the fact that the aviation crews in these countries are well trained with the aim of minimizing aviation accidents. Research on accident patterns in aviation is very important because the prediction of their occurrence is not possible after flight or after a collision. The need to identify significant human factor events causing local aviation accidents and incidents and to demonstrate aerobiological causes may provide direction for prevention. A study set out to identify and model human factors risk in Kenyan and Ugandan aviation operations. A document review analysis selected 42 regional final accident and incident investigation reports between 2000- 2017 for review. Results identified that most accidents in both countries were occurring at the landing phase with improper landing as the highest occurrences at 28%, followed by takeoff accidents with improper planning at 10% and lastly engine failure during flight at 10%.  MLogit model for Kenya showed significance at P<0.001, in the manner with which one flies, exceptional violation, supervisory violations and organizational processes. Findings showed that the region’s operations have unsafe acts as the highest category of active failures. The commonest unsafe acts were exceptional violations and skill based errors (manner or skill with which one flies).The study identified that most accidents in both countries were occurring at the landing phase with other significant ones at takeoff and during flight phase. In all it is recommended that the aviation training and its evaluation be progressively reevaluated by the respective authorities to increase individual’s skills and further reduce the emerging unsafe act.