Fatalities, accident data

Coury et al. (1999) Alberta—Canada Describe farm injury accidents and fatalities reported in Alberta (1976-1989) and also compare the data on injury accidents (1995) Farming Fatal and non-fatal... 

They are particularly limited for assessing the future risk of high consequence, low probability accidents. (A fatal accident rate based on data from single fatalities may not be a good predictor of risk of multiple fatal emergencies.)... 

One very detailed analysis of pedestrian crash, injury, and fatality risk that considered the different exposure measures was conducted by Keall (1995). For his analysis he combined travel exposure data from the 1989- 1990 New Zealand Travel Survey with pedestrian accident data from the New Zealand national Traffic Accident Report files for the period 1988-1991. The travel survey data for children 5-9 years old were obtained from interviews with the parents or other adults in the same household. Their casualty data as a function of the pedestrian age is plotted in Figure 15-2. If we look first at the absolute numbers of pedestrians injured or killed as a function of age and gender we see the expected high numbers of young (5-19 years old) pedestrians. We also see that more males than females are injured or killed. 

Six years of accident data (2007-2012) including fatal (fatality within 30 days as a result of the accident), serious (mjury healing beyond 8 days) and light (recovery within 8 days) injuiy accidents were gathered. Property damage accidents were not taken into consideration. 

Part 2 deals with detailed statistical analysis of accident data, in order to identify or understand road safety critical issues and develop accident models. The issue of the evolution of the nnmber of road fatalities in Poland, in relation to economic factors, is presented, along with an analysis aiming to identify the risk of road traffic injuries for pedestrians, cyclists, car occnpants and PTW riders in Rhone, France, based on a road trauma registry and travel snrveys. Fnrthermore, interesting accident prediction models for main rural roads in Hnngaiy are developed, with imminent and obvious practical applications. 

The collective U.S. and Canadian component of these 1,307 accidents was around 34% (i.e., 445 accidents), which contributed about 25% (6,077) of the worldwide 24,700 onboard fatalities [6]. A study of the 1959-2001 accident data indicates that the world commercial jet fleet accident rate (i.e., accidents per million departures) has been fairly stable for the period 1974-2001 [14]. Additional information on the subject is available in the literature [6,14]. 

The safety record of the smaller railroads can be investigated using FRA data. Table 15.3 shows accident and fatality-rate data for the years 1994-96 for three different sizes of railroads the large Class I railroads, the medium-size Class II railroads, and the small Class III railroads who are defined as having less than 400,000 employee-hours per year. In rough terms. Class III would be equivalent to those railroads shown in table 15.1 as moving less than 40,000 carloads a year. 

One approach is to compare the risks, calculated from a hazard analysis, with risks that are generally considered acceptable such as, the average risks in the particular industry, and the kind of risks that people accept voluntarily. One measure of the risk to life is the Fatal Accident Frequency Rate (FAFR), defined as the number of deaths per 108 working hours. This is equivalent to the number of deaths in a group of 1000 men over their working lives. The FAFR can be calculated from statistical data for various industries and activities some of the published values are shown in Tables 9.8 and 9.9. Table 9.8 shows the relative position of the chemical industry compared with other industries Table 9.9 gives values for some of the risks that people accept voluntarily. 

The OSHA incidence rate provides information on all types of work-related injuries and illnesses, including fatalities. This provides a better representation of worker accidents than systems based on fatalities alone. For instance, a plant might experience many small accidents with resulting injuries but no fatalities. On the other hand, fatality data cannot be extracted from the OSHA incidence rate without additional information. 

When organizations focus on the root causes of worker injuries, it is helpful to analyze the manner in which workplace fatalities occur (see Figure 1-4). Although the emphasis of this book is the prevention of chemical-related accidents, the data in Figure 1-4 show that safety programs need to include training to prevent injuries resulting from transportation, assaults, mechanical and chemical exposures, and fires and explosions. 

Dr. Wilse Webb performed a different analysis from Leger s using the data of fatal and total motor-vehicle accidents as reported by the National Safety Council in 1988 (6). He proposed a conservative estimate of 1225 fatalities, 45,000 disabling injuries, and 1.75 billion in total cost from these accidents. 

Webb cited data from the CARfile study of the U.S. Department of Transportation in 1985, which reported 1.4% of total accidents and 1.75% of fatal accidents were directly related to sleepiness (7). Lavie and Pollack studied 13,152 reports by the Israeli Police Department of hourly distribution of sleep-related motor vehicle accidents for 8 years, and found 390 injuries directly attributable to sleepiness (8). A special examiner at the scene assigned the reason for the accident. Lavie reported a highest yearly estimate of 1.0% motor vehicle accidents attributable to sleepiness (personal communication to Webb). 

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