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Estimation of the Prevalence of Problem Drug Use in Lithuania

Learn about methods, data sources, and results for estimating problem drug use in Lithuania. Explore capture-recapture methods and prevalence estimates.

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Estimation of the Prevalence of Problem Drug Use in Lithuania

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  1. Estimation of the Prevalence of Problem Drug Use in Lithuania Dr Gordon Hay Centre for Drug Misuse Research University of Glasgow, United Kingdom

  2. Introduction • Background • Definition • Methods to Estimate Prevalence • Mortality Multiplier • Capture-recapture Methods • truncated Poisson method • Prevalence Estimates • Vilnius, Klaipeda & Lithuania • Discussion

  3. Background • UNODC project • Project “HIV/AIDS prevention and care among injecting drug users and in prison settings in Estonia, Latvia and Lithuania” • Objectives • To obtain estimates of Problem Drug Use (PDU) and Injecting Drug Use (IDU) prevalence • 5 days fieldwork (September 2007) • Workshop on prevalence estimation

  4. My experience • United Kingdom Government • Estimating the prevalence of problem drug use • Dundee (1994) • Lanarkshire (2007), Aberdeen (1998) • Scotland (2000, 2003, 2006) • England (2004, 2005, 2006) • Northern Ireland (2005) • Other studies • Cohort study of drug users in treatment • Children / young people

  5. My Experience • European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) • All member states required to provide information on the prevalence of problem drug use • Seven Cities Study (1997) • Dublin, Helsinki, Rome, Rotterdam, Setubal Toulouse & Vienna • Methodological Studies • UK Scientific Expert (problem drug use)

  6. My Experience • Synergy project • USAID / Family Health International projects • Prevalence estimation in Estonia, Latvia and Lithuania • Fieldwork in Klaipeda, Riga, Tallinn & Vilnius • Prevalence estimate for Riga • Recommendations • Involved in prevalence estimation study in Tallinn

  7. Definitions • EMCDDA defines problem drug use as: • injecting drug use or long-duration / regular use of opiates, cocaine and / or amphetamines • In this study / estimation we define problem drug use as: • Opiate use (mostly opiate injecting) • We do not include stimulant or marijuana use

  8. Methods to Estimate Prevalence • Indirect methods • Mortality Multiplier Method • Capture-recapture Method • truncated Poisson Method • Multiple Indicator Method • Estimate the size of hidden populations

  9. General Idea • There are some problem drug users that are ‘visible’ or ‘identifiable’ or ‘known’ • Treatment • Police • Mortality • A proportion of problem drug users are visible • In United Kingdom about 40 – 50% in treatment • Data on visible population can be used to estimate the size of the total population

  10. Mortality Multiplier • Uses the: • Number of drug-related deaths • Mortality rate • Both need to refer to the same population, such as opiate users

  11. Drug related death dataSource: Health Statistics Quarterly 1,506 deaths in 2005

  12. Mortality Multiplier • 1,506 drug-related deaths in 2005 • What is the mortality rate? • Anecdotal evidence = 1% per year • Therefore 150,600 problem drug users

  13. Mortality Multiplier • Average 40 drug-related deaths in Lithuania • Source: Lithuanian Focal Point Report to the EMCDDA • Mortality rate = 1.7% • Source: Most up-to-date study of drug-related mortality in European Union (data for Denmark) • 2,350 injecting drug users in Lithuania • 2,940 problem drug users in Lithuania

  14. Capture-recapture method • Simple idea: • Only a certain proportion of drug users are in contact with treatment agencies • Examine the overlap between those in treatment and a second sample (e.g. Police) • Find the proportion in treatment • Thus estimate the total number of drug users

  15. Two sample capture-recapture method

  16. Capture-recapture Methods • With two sources we need to assume that the sources are not related to each other • With three sources we can include relationships between data sources • Different statistical models are fitted to the data • We select the ‘best’ model and estimate

  17. Data sources (Vilnius) • Three distinct sources from the Vilnius Centre for Addictive Disorders • Detoxification with Subutex (n = 207) • Outpatient Treatment (n = 306) • Police sample (n = 166) • 6 month period within 2006 • Opiate users (mostly injectors) • Does not include methadone substitution

  18. Three-source overlap (Vilnius) In total there were 588 ‘visible’ individuals 457 were in Detox or Outpatient Treatment

  19. Results (Vilnius) • 2,167 problem drug users • 95% Confidence Interval = 1,663 – 2,934 • Assumes that detox and outpatient sources are related (but Police data independent) • ‘best’ model and estimate

  20. truncated Poisson method • Uses a single data source • Number of visits at a syringe exchange • Number attended once • Number attended twice • Total number who had attended • Estimates number who have attended zero times • Assumptions • Attendances are not related to each other • You can identify people who attend more than once

  21. truncated Poisson Analysis

  22. truncated Poisson analysis (Vilnius)Data for 2006 complete year • Vilnius Centre for Addictive Disorders • Computerised data • 1,444 people who had used the syringe exchange provision at any time during 2006 • Estimated 1,622 drug injectors in 2006

  23. truncated Poisson analysis (Vilnius)Data for individual months • Between 250 and 550 individuals attended in any one month period • More in summer • Average number of ‘active’ drug injectors each month = 600

  24. truncated Poisson analysis (Klaipeda) • Data from hand written log book (registers) • Good data • My understanding of Lithuanian alphabet is bad! • Could only do a monthly analysis • Between 100 and 185 individual attended in any one month period • Average number of ‘active’ drug injectors each month = 280 • Total number of injectors in Klaipeda = 750

  25. truncated Poisson analysis(Summary) • Vilnius • 600 ‘active’ injectors per month • 1,663 injectors in 2006 • Klaipeda • 280 ‘active’ injectors per month • 750 injectors in 2006 • Both estimates should be treated with caution • Useful for comparing Vilnius and Klaipeda • Does not contradict capture-recapture analysis

  26. National Estimates • Use published statistics to extrapolate • Ministry of Interior • Drug offences • Lithuanian Focal Point to the EMCDDA • Number of new demands for treatment • Vilnius Municipality has 50% of national total in both datasets • Half of Lithuania’s problem drug users live in Vilnius Municipality

  27. National Estimates • 4,300 problem drug users in Lithuania • 2006 estimate • Problem opiate use • 3,200 drug injectors • truncated Poisson analysis • 75% injecting

  28. Summary • These are provisional estimates • The capture-recapture analysis for Vilnius is as good (if not better) than studies elsewhere in Europe • The truncated Poisson estimates (for Vilnius and Klaipeda) should be used with caution • But should be reliable for comparing prevalence rates between the two cities

  29. Discussion • National Treatment Register • Over 5,000 for Lithuania • 2,600 for Vilnius • WHO estimates • 7,000 – 11,000 problem drug users (Lithuania) • Case definition • Opiate use, problem opiate use

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