The epidemiology of aircraft fire in commuter and air taxi crashes.
BACKGROUND
Aircraft fire is recognized as an important risk factor for occupant fatality in aviation crashes, but its epidemiology has not been adequately studied.


OBJECTIVE
This study examines factors related to the occurrence of aircraft fire, ignition sources, and factors influencing rescue and firefighting in commuter and air taxi crashes.


METHODS
Commuter and air taxi crashes in 1983-88 that involved aircraft fire were analyzed using National Transportation Safety Board (NTSB) data, including NTSB supplemental forms on fire and on rescue and firefighting.


RESULTS
Aircraft fire was recorded in 17% of the 888 commuter and air taxi crashes. Factors associated with increased likelihood of fire in these crashes were non-airport location (adjusted relative risk 2.7, 95% confidence interval 1.8-4.1), twin-engine aircraft (RR 2.5, 95% Cl 1.6-3.9), and nighttime (RR 1.7, 95% Cl 1.1-2.5). Fire was more common in Beech 18's than other twin-engine airplanes. The majority (59%) of fires occurred during impact sequence, and an additional 17% occurred after the aircraft came to rest. The engine was identified as the ignition source in 59% of the crashes, followed by hot surface (18%), short circuit (9%), and sparks (9%). Fire sensing and extinguishing systems were installed in only 19% of the aircraft. Rescue and firefighting efforts were hampered most commonly by terrain (48%), weather (47%), and darkness (38%).


CONCLUSIONS
Typically induced by impact and started at the engine, aircraft fire is most likely when a crash occurs at night, in a non-airport location, and in instrument meteorological conditions. These high-risk circumstances also often thwart rescue and firefighting efforts.
Li
G
G
Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
Baker
S P
SP
Dodd
R S
RS
D000060:Accidents, Aviation / Q000517:prevention & control / Q000706:statistics & numerical data*; D005390:Fires / Q000517:prevention & control / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D014481:United States