from Part IV - Uncertainty modeling and risk measurement
Published online by Cambridge University Press: 05 June 2012
How can we choose a probabilistic risk acceptance criterion, a probabilistic safety goal, or specify how changes of risk baseline should influence other design and operational decisions? Basically, we have to compare risks from different, perhaps very different activities. What quantities should be compared? There is an ocean of literature on this subject. The story begins with the first probabilistic risk analysis, WASH-1400, and books which come quickly to mind are [Shrader-Frechette, 1985], [Maclean, 1986], [Lowrance, 1976] and [Fischhoff et al., 1981]. A few positions, and associated pitfalls, are set forth below. For convenience we restrict attention to one undesirable event, namely death.
Single statistics representing risk
Deaths per million
The most common quantity used to compare risks is ‘deaths per million’. Covello et al. [Covello et al., 1989] give many examples of the use of this statistic. Similar tables are given by the British Health and Safety Executive [HSE, 1987]. The Dutch government's risk policy statement [MVROM, 1989] gives a variation on this method by tabulating the yearly risk of death as ‘one in X’.
Table 18.1 shows a few numbers taken from Table B.1 of [Covello et al., 1989], ‘Annual risk of death in the United States’. By each ‘cause’ the number of deaths per year per million is given.
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