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Epidemiology of helicopter accidents: Trends, rates, and covariates

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  • Churchwell, Jared S.
  • Zhang, Katherine S.
  • Saleh, Joseph H.

Abstract

The objective of this work is to provide a better understanding of helicopter accidents and to identify important areas for different stakeholders to focus their attention and resources for accident prevention. To this end, we undertook Record Linkage of two federal data sources: the FAA civil helicopter registration data and the NTSB accident data. First, the analysis of accident rates and trends shows little progress in accident prevention over the last decade. Second, we find that helicopter accident rates vary significantly by number of main rotor blades, with the four- and six-bladed helicopters having the safest track record. Third, we show that accident rates vary by engine types when controlling for the number of blades. For example, the combination of reciprocating engine and three-bladed (3B) helicopters is associated with one of the highest accident rates. We further examine differences in accident rates between single and twin-engine helicopters, controlling for engine type and number of blades. The worst-in-class in terms of rates are the 5B and 6B single-engine turboshaft helicopters, whereas the worst-offenders in terms of contributing to the total count of accidents are the single-engine 2B reciprocating and turboshaft helicopters. The 4B single-engine turboshaft occupy a safety sweet spot and have the lowest accident rates of all single-engine helicopters. We provide risk ratios for pairwise comparisons and 95% confidence intervals for all accident rates, and discuss possible confounders for these results. The issues here examined lend themselves to a rich set of technical and operational implications, and they deserve careful attention from helicopter operators, regulators, and manufacturers. Any serious effort to improve helicopter safety will entail action on multiple safety levers, including design, operational, and policy-related ones. These actions should be evidence-based and they require better helicopter accident investigations and better data.

Suggested Citation

  • Churchwell, Jared S. & Zhang, Katherine S. & Saleh, Joseph H., 2018. "Epidemiology of helicopter accidents: Trends, rates, and covariates," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 373-384.
    • Handle: RePEc:eee:reensy:v:180:y:2018:i:c:p:373-384
    DOI: 10.1016/j.ress.2018.08.007
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    References listed on IDEAS

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    1. Marais, Karen B. & Robichaud, Matthew R., 2012. "Analysis of trends in aviation maintenance risk: An empirical approach," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 104-118.
    2. Jan-Erik Vinnem, 2014. "Offshore Risk Assessment vol 1," Springer Series in Reliability Engineering, Springer, edition 3, number 978-1-4471-5207-1, January.
    3. Saleh, J.H. & Marais, K.B. & Bakolas, E. & Cowlagi, R.V., 2010. "Highlights from the literature on accident causation and system safety: Review of major ideas, recent contributions, and challenges," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1105-1116.
    4. Jan-Erik Vinnem, 2014. "Offshore Risk Assessment vol 2," Springer Series in Reliability Engineering, Springer, edition 3, number 978-1-4471-5213-2, January.
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    Cited by:

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    2. Iaiani, Matteo & Casson Moreno, Valeria & Reniers, Genserik & Tugnoli, Alessandro & Cozzani, Valerio, 2021. "Analysis of events involving the intentional release of hazardous substances from industrial facilities," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    3. Xu, Zhaoyi & Saleh, Joseph Homer & Subagia, Rachmat, 2020. "Machine learning for helicopter accident analysis using supervised classification: Inference, prediction, and implications," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    4. Rachmat Subagia & Joseph Homer Saleh & Jared S Churchwell & Katherine S Zhang, 2020. "Statistical learning for turboshaft helicopter accidents using logistic regression," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-21, January.
    5. Martin Folch-Calvo & Francisco Brocal-Fernández & Cristina González-Gaya & Miguel A. Sebastián, 2020. "Analysis and Characterization of Risk Methodologies Applied to Industrial Parks," Sustainability, MDPI, vol. 12(18), pages 1-35, September.

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