FIGURE 2.1 Change in statistical distribution of cocaine consumption over time.

Source: Adapted from Everingham and Rydell (1994).

This type of systems research, better supported by data, has potential to provide a more complete picture of patterns and consequences of drug use.

Alcohol researchers have used the analysis of consumption distributions to conduct a fruitful—if still unresolved—debate about the relative efficacy of two alternative targeting strategies for drug policy (Edwards et al., 1994; MacCoun, 1998; Rose, 1992). One strategy is to disproportionately target the heaviest users, because they account for such a large share of total consumption and, as a consequence, are at higher risk of causing harm to themselves and others. Others argue that there may be greater aggregate benefit from reducing consumption among casual users; they pose fewer risks individually, but they typically outnumber heavy users by a wide margin.12


In the public health literature, this latter notion is referred to as the “prevention paradox”; see Rose (1992). A strong version was proposed by Ledermann (1956), who hypothesized that there was a fixed relationship between the mean and variance of the alcohol distribution, so that reductions in the mean would bring about reductions at the extremes. This strong version has been rejected empirically (Skog, in Edwards et al., 1994)

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