Amundsen, E.J., Bretteville-Jensen, A.L., Kraus, L.

Estimating incidence of problem drug use using the Horwitz-Thompson estimator – A new approach applied to people who inject drugs in Oslo 1985–2008


International Journal of Drug Policy, 27 (1), 36–42

Open Access

The trend in the number of new problem drug users per year (incidence) is the most important measure for studying the diffusion of problem drug use. Due to sparse data sources and complicated statistical models, estimation of incidence of problem drug use is challenging. The aim of this study is to widen the palette of available methods and data types for estimating incidence of problem drug use over time, and for identifying the trends.

This study presents a new method of incidence estimation, applied to people who inject drugs (PWID) in Oslo. The method took into account the transition between different phases of drug use progression - active use, temporary cessation, and permanent cessation. The Horwitz-Thompson estimator was applied. Data included 16 cross-sectional samples of problem drug users who reported their onset of injecting drug use. We explored variation in results for selected probable scenarios of parameter variation for disease progression, as well as the stability of the results based on fewer years of cross-sectional samples.

The method yielded incidence estimates of problem drug use, over time. When applied to people in Oslo who inject drugs, we found a significant reduction of incidence of 63% from 1985 to 2008. This downward trend was also present when the estimates were based on fewer surveys (five) and in the results of sensitivity analysis for likely scenarios of disease progression.

This new method, which incorporates temporarily inactive problem drug users, may become a useful tool for estimating the incidence of problem drug use over time. The method may be less data intensive than other methods based on first entry to treatment and may be generalized to other groups of substance users. Further studies on drug use progression would improve the validity of the results.


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