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Assessment of accident severity in the construction industry using the Bayesian theorem

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Aim: Construction is a major source of employment in many countries. In construction, workers perform a great diversity of activities, each one with a specific associated risk. The aim of this paper is to identify workers who are at risk of accidents with severe consequences and classify these workers to determine appropriate control measures. Methods: We defined 48 groups of workers and used the Bayesian theorem to estimate posterior probabilities about the severity of accidents at the level of individuals in construction sector. First, the posterior probabilities of injuries based on four variables were provided. Then the probabilities of injury for 48 groups of workers were determined. Results: With regard to marginal frequency of injury, slight injury (0.856), fatal injury (0.086) and severe injury (0.058) had the highest probability of occurrence. It was observed that workers with <1 year's work experience (0.168) had the highest probability of injury occurrence. The first group of workers, who were extensively exposed to risk of severe and fatal accidents, involved workers ≥50 years old, married, with 1–5 years' work experience, who had no past accident experience. Conclusion: The findings provide a direction for more effective safety strategies and occupational accident prevention and emergency programmes.
Rocznik
Strony
551--557
Opis fizyczny
Bibliogr. 36 poz.
Twórcy
  • Tabriz University of Medical Sciences, Iran
  • Tarbiat Modares University, Iran
  • Tarbiat Modares University, Iran
Bibliografia
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b89f49a7-f261-47c5-8cd2-e6648905b0d3
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