A Bayesian analysis of domestic fire response and fire injury
Year: 2024
Type: article
Study design: Observational Study
Abstract: In this article domestic fire response and fire injury was examined using a Bayesian analysis approach. A Bayesian model was developed to estimate the probability of non-fatal fire injury associated with a given fire response (escape, return to fire, fight the fire) under given circumstances of non-fatal fire injury (age band, gender, smoke alarm presence, type of domestic fire). The Bayesian model was developed using non-fatal fire injury data recorded by Merseyside Fire and Rescue Service between 2011 and 2022. Overall, more domestic fire injuries relating to attempting to fight the fire occurred in properties with a smoke detector (82 % of attempting to fight the fire injuries) compared to properties without a smoke detector (18 % of attempting to fight the fire injuries). Similarly, fire injuries sustained returning to the fire mainly occurred in properties with a smoke detector (75 % of returning to fire injuries) as opposed to properties without a smoke detector (25 % of returning to fire injuries).
Source: Fire Safety Journal
Authors: M. Taylor, J. Fielding, D. Reilly, V. Kwasnica
Institution: Liverpool John Moores University
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,660
OpenAlex ID: W4402537869