Aims: Effects of differing drug policies are difficult to evaluate, because time trends in the spread of heroin use, the most problematic illicit drug world-wide, are unknown in almost all countries. We aimed to develop a simple method to estimate these dynamics with data that can be gathered from patients in substitution treatment within a single day.
Design: We tested the assumption that being in substitution treatment on any day depends solely upon individual time since onset of regular heroin use (following a 'general inclusion function'). We used data from the case register for substitution treatments in the canton of Zurich (1992--2004), comprising 9518 patients, to model a 'general inclusion function'. Applying this function, we calculated 30 incidence curves for heroin dependence, each with data of one of 30 randomly chosen treatment days between 1992 and 2004.
Findings: Incidence modelling led to 30 similar curves, and therefore our hypothesis was corroborated. Additionally, our approach also revealed a restricted access to substitution treatment in the early 1990s and a decline in demand due to the introduction of heroin-assisted treatment from 1994 onwards.
Conclusions: In the canton of Zurich, the probability of being in substitution treatment can be described by a 'general inclusion function', and therefore dynamics of heroin epidemics can be estimated based on data of a single treatment day. Adaptation of our function to areas with a more restricted access to substitution treatment may permit these estimations also in other regions or countries. Thus, our approach facilitates the urgently needed assessment of the effects of different drug policies.