Drug supply indicators: Pitfalls and possibilities for improvements to assist comparative analysis.

Interventions to tackle the supply of drugs are seen as standard components of illicit drug policies. Therefore drug market-related administrative data, such as seizures, price, purity and drug-related offending, are used in most countries for policy monitoring and assessment of the drug situation. International agencies, such as the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) and the UN Office of Drugs and Crime, also monitor and report on the drug situation cross-nationally and therefore seek to collect and make available key data in a uniform manner from the countries they cover. However, these data are not primarily collected for this purpose, which makes interpretation and comparative analysis difficult. Examples of limitations of these data sources include: the extent to which they reflect operational priorities rather than market changes; question marks over the robustness of and consistency in data collection methods, and issues around the timeliness of data availability. Such problems are compounded by cultural, social and contextual differences between countries. Making sense of such data is therefore challenging and extreme care needs to be taken using it. Nevertheless, these data provide an important window on a hidden area, so improving the quality of the data collected and expanding its scope should be a priority for those seeking to understand or monitor drug markets and supply reduction. In addition to highlighting some of the potential pitfalls in using supply indicators for comparative analysis, this paper presents a selection of options for improvements based on the current EMCDDA programme of work to improve their supply-related monitoring and analysis. The conceptual framework developed to steer this work may have wider application. Adopting this approach has the potential to provide a richer picture of drug markets, at both national and international levels, and make it easier to compare data between countries.