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American Journal of Epidemiology Vol. 155, No. 5 : 398-405
Copyright © 2002 by The Johns Hopkins University School of Hygiene and Public Health

ORIGINAL CONTRIBUTIONS

Exploratory Spatial Analysis of Pilot Fatality Rates in General Aviation Crashes Using Geographic Information Systems

Jurek G. Grabowski1, Frank C. Curriero2, Susan P. Baker3 and Guohua Li1

1 Department of Emergency Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD.
2 Department of Biostatistics, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
3 Center for Injury Research and Policy, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Geographic information systems and exploratory spatial analysis were used to describe the geographic characteristics of pilot fatality rates in 1983–1998 general aviation crashes within the continental United States. The authors plotted crash sites on a digital map; rates were computed at regular grid intersections and then interpolated by using geographic information systems. A test for significance was performed by using Monte Carlo simulations. Further analysis compared low-, medium-, and high-rate areas in relation to pilot characteristics, aircraft type, and crash circumstance. Of the 14,051 general aviation crashes studied, 31% were fatal. Seventy-four geographic areas were categorized as having low fatality rates and 53 as having high fatality rates. High-fatality-rate areas tended to be mountainous, such as the Rocky Mountains and the Appalachian region, whereas low-rate areas were relatively flat, such as the Great Plains. Further analysis comparing low-, medium-, and high-fatality-rate areas revealed that crashes in high-fatality-rate areas were more likely than crashes in other areas to have occurred under instrument meteorologic conditions and to involve aircraft fire. This study demonstrates that geographic information systems are a valuable tool for injury prevention and aviation safety research.

accidents; aviation; geography; information systems; Monte Carlo method

Abbreviations: NTSB, National Transportation Safety Board; SD, standard deviation


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