A Bayesian network analysis of workplace accidents caused by falls from a height

This article analyses, using Bayesian networks, the circumstances surrounding workplace tasks performed using auxiliary equipment (ladders, scaffolding, etc.) that may result in falls. The information source was a survey of employees working at a height. We were able to determine the usefulness of this approach – innovative in the accident research field – in identifying the causes that have the greatest bearing on accidents involving auxiliary equipment: in these cases, the adoption of incorrect postures during work and a worker’s inadequate knowledge of safety regulations. Likewise, the duration of tasks was also associated with both these variables, and therefore, with the accident rate. Bayesian networks also enable dependency relationships to be established between the different causes of accidents. This information – which is not usually furnished by conventional statistical methods applied in the field of labour risk prevention – allow a causality model to be defined for workplace accidents in a more realistic way. With this statistic tool, the expert is also provided with useful information that can be input to a management model for labour risk prevention.     

Coexistence between People and Elephants in African Savannas

Abstract: The decline in the range and numbers of elephants as a result of expanding human activity in Africa is recognized as one of the continent's more serious conservation problems. Understanding the relationship between human settlement patterns and elephant abundance is fundamental to predicting the viability of elephant populations. The prevailing model of human-elephant interaction predicts a negative linear relationship between rising human density and declining elephant density at a coarse (national or subcontinental) scale. Using observed elephant densities and human population data, we tested this prediction in a study area of 15,000 km² in northwestern Zimbabwe. The results did not fit a linear model. Elephant and human coexistence occurs at various levels of human density, up to a threshold of human density beyond which elephant populations disappear. This threshold seems to be related to a particular stage in the process of agriculturally transformed land becoming spatially dominant over the natural woodland that constitutes elephant habitat. Within the contexts of conservation and sustainable development in African savannas, investigating spatial relationships between elephant and human abundance should be a priority topic for future research.