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Risk Profiling from the European Statistics on Accidents at Work (ESAW) Accidents' Databases: A Case Study in Construction Sites.


ABSTRACT: The number of accidents and victims in the construction sector has not decreased significantly despite the increasingly stricter laws and regulations. The analysis of accidents, as well as their root causes and determinants can certainly contribute to the development of more effective preventive interventions. The present study proposes a methodology for the analysis and synthesis of data provided by accidents statistics with the goal of defining specific risk profiles based on the accidents determinants, their variables, and how they interact with one another in influencing the occurrence of an accident. For this purpose, a procedure capable of extracting this type of information from the European Statistics on Accidents at Work (ESAW) database was developed. In particular, data processing and aggregation are performed by means of the synergic use of the Matrix of Descriptors (MoD) and cluster analysis. To validate such a procedure, the analysis of fatalities due to electrical shocks was carried out. The results achieved allowed us to elicit valuable information for both safety managers and decision makers. The proposed methodology can facilitate a systemic analysis of accidents databases reducing the difficulties in managing reports and accident statistics.

SUBMITTER: Lombardi M 

PROVIDER: S-EPMC6926752 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Risk Profiling from the European Statistics on Accidents at Work (ESAW) Accidents' Databases: A Case Study in Construction Sites.

Lombardi Mara M   Fargnoli Mario M   Parise Giuseppe G  

International journal of environmental research and public health 20191127 23


The number of accidents and victims in the construction sector has not decreased significantly despite the increasingly stricter laws and regulations. The analysis of accidents, as well as their root causes and determinants can certainly contribute to the development of more effective preventive interventions. The present study proposes a methodology for the analysis and synthesis of data provided by accidents statistics with the goal of defining specific risk profiles based on the accidents det  ...[more]

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