Risk management has been widely advocated as a rational means for environmental decision making, assisting us in dealing with the wide array of dangers that we face in our uncertain world, ranging from pathogens in drinking water to terrorist attacks. Done well, risk management is inherently precautionary in the sense that it should make use of effective risk assessment to predict, anticipate, and prevent harm, rather than merely reacting when harm arises.Some of the insights that have supported the movement toward making better use of available evidence for medical decision making, particularly in the field of diagnostic screening, have important but usually overlooked insights for environmental decision making. In particular, the use of four key concepts used for judging the quality of evidence in medical diagnosis-sensitivity, specificity, positive predictive value, and negative predictive value-are relevant to the assessment of environmental hazards, especially those that have low probabilities of occurrence. Applying these concepts rigorously allows us to see more clearly both the value and the limitations of the precautionary approach, as well as to reveal more quantitatively the logical flaw in the notion of "zero risk." The key question, we suggest, is not whether to be precautionary, but how precautionary we ought to be in specific cases, in relation to the quality of our screening evidence.
Interpreting Evidence about HazardsOur premise can be illustrated by considering an analogy with airport security. Suppose that we have acquired impressive new scanning technology with the following detection capabilities: a) when someone is carrying a dangerous weapon, 99.5% of the time it will respond positively, and b) when someone is not carrying such a weapon, 98% of the time it will respond negatively. If our best intelligence indicates that about 1 in 10,000 passengers screened will be carrying a detectable, dangerous weapon, we can ask how well the screening evidence will allow us to manage this risk. In particular, we can ask, if we get a positive result how likely is that detection to be correct? Given the properties described, common intuition will lead us to expect that this detection should be reliable.The answer to our question depends on considering that, on average, we will need to screen 9,999 unarmed passengers to find the 1 who is carrying a weapon. The characteristics described provide for a false-positive rate of 2% (98% of the time unarmed passengers will show up as negative). This means that, on average, we will get 199.98 or, effectively, 200 false positives detected for every true positive. Consequently, the answer about how likely it is that a positive detection will be correct turns out to be only 0.5% (1 in 201).Of course, these numbers are hypothetical, but they likely overestimate both the realistic capability of such technology and the frequency of passengers truly carrying weapons. The frequency of the hazard we are seeking to detect is a critical determinant of the ability of any scr...