Improved benchmark-multiplier method to estimate the prevalence of ever-injecting drug use in Belgium, 2000–10

Kaatje Bollaerts,Marc Aerts,Andre Sasse

doi:10.1186/0778-7367-71-10

Abstract

BackgroundAccurate estimates of the size of the drug-using populations are essential for evidence-based policy making. However, drug users form a ‘hidden’ population, necessitating the use of indirect methods to estimate population sizes.MethodsThe benchmark-multiplier method was applied to estimate the population size of ever injecting drug users (ever-IDUs), aged 18–64 years, in Belgium using data from the national HIV/AIDS register and from a sero-behavioral study among injecting drug users. However, missing risk factor information and absence of follow-up of the HIV+/AIDS– cases, limits the usefulness of the Belgian HIV/AIDS register as benchmark. To overcome these limitations, statistical corrections were required. In particular, Imputation by Chained Equations was used to correct for the missing risk factor information whereas stochastic mortality modelling was applied to account for the mortality among the HIV+/AIDS– cases. Monte Carlo simulation was used to obtain confidence intervals, properly reflecting the uncertainty due to random error as well as the uncertainty associated with the two statistical corrections mentioned above.ResultsIn 2010, the prevalence (/1000) of ever-IDUs was estimated to be 3.5 with 95% confidence interval [2.5;4.8]. No significant time trends were observed for the period 2000–2010.ConclusionsTo be able to estimate the ever-IDU population size using the Belgian HIV/AIDS register as benchmark, statistical corrections were required without which seriously biased estimates would result. By developing the improved methodology, Belgium is again able to provide ever-IDU population estimates, which are essential to assess the coverage of treatment and to forecast health care needs and costs.

Highlights

Accurate estimates of the size of the drug-using populations are essential for evidence-based policy making
The key assumptions underlying the BM method are that the benchmark should be exhaustive, the sample used to estimate the multiplier should be representative of the target population and the case definition used for the benchmark should exactly match the one used for the multiplier, including the time window [12]
The benchmark-multiplier (BM) method was applied to estimate the prevalence of ever injecting drug users within the population aged 15–64 years in Belgium, 2000–10, using the HIV/AIDS register as benchmark

Summary

Introduction

Accurate estimates of the size of the drug-using populations are essential for evidence-based policy making. Drug users form a ‘hidden’ population, necessitating the use of indirect methods to estimate population sizes. Accurate estimates of the size of the drug-using population are indispensable to govern and evaluate drug policy. They are important to forecast health care needs and costs and to assess the coverage of treatment and harm reduction measures e.g. The BM method combines (an estimate of ) the size of the known part of the target population, the benchmark, with an estimate of the proportion of individuals from the target population belonging to the benchmark. The size of the target population is estimated as the product of the benchmark and the multiplier. The key assumptions underlying the BM method are that the benchmark should be exhaustive, the sample used to estimate the multiplier should be representative of the target population and the case definition used for the benchmark should exactly match the one used for the multiplier, including the time window [12]

Methods

Results

Discussion

Conclusion