Author Identifier

Marcus Cattani

Document Type

Journal Article

Publication Title

Safety Science




School of Medical and Health Sciences




This is an Authors Accepted Manuscript version of an article published by Elsevier in Safety Science. The published version is available at :

Penney, G., Cattani, M., & Ridge, S. (2022). Enhancing fire service incident investigation–Translating findings into improved outcomes using PIAM. Safety Science, 145, article 105488.


Since 1927 more than 242 formal inquiries and reviews into Australian natural disasters, and 62 international post-incident investigations following firefighter fatalities or injuries during wildfire entrapment and burnover have been completed. Despite the significant number of completed inquires, evidence suggests emergency services continue to repeat mistakes of the past when preparing for, preventing, responding to, and recovering from disasters. Where ongoing mistakes occur, the interventions themselves (including analysis methods) must be questioned as the significant cost of repeated inquiries may divert funding from improving both the capabilities and capacities of the emergency services being investigated. The objective of this paper is to work towards addressing limitations of investigative processes within the context of Australian fire and emergency services. It does this by building upon the Incident Causation Analysis Model (ICAM), and proposes the resultant PESTLE Incident Analysis Model (PIAM). The PIAM is designed to enhance analysis of adverse incidents, and to assist emergency services both communicate and implement recommendations from post-incident investigations and analysis. The PIAM is validated using a historical firefighter entrapment. In doing so this paper demonstrates the suitability of the PIAM technique for both emergency service and more traditional occupational safety investigations, making the critical connection between research and practice that is essential within emergency services worldwide.



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Available for download on Friday, January 31, 2025