Estimating the size and dynamics of an injecting drug user population and implications for health service coverage: comparison of indirect prevalence estimation methods.

AIMS: (i) To compare indirect estimation methods to obtain mean injecting drug use (IDU) prevalence for a confined geographic location; and (ii) to use these estimates to calculate IDU and injection coverage of a medically supervised injecting facility. DESIGN: Multiple indirect prevalence estimatio...

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Publicado en:Addiction Vol. 103; no. 10; pp. 1604 - 1614
Autores principales: Kimber J, Hickman M, Degenhardt L, Coulson T, van Beek I
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell Oct2008
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2008
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      pub: Wiley-Blackwell
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        10.1111/j.1360-0443.2008.02276.x
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        atl: Estimating the size and dynamics of an injecting drug user population and implications for health service coverage: comparison of indirect prevalence estimation methods.
      aug:
        au:
          Kimber J
          Hickman M
          Degenhardt L
          Coulson T
          van Beek I
        affil: Centre for Research on Drugs and Health Behaviour, London School of Hygiene and Tropical Medicine, London, UK
      sug:
        subj:
          Disease Surveillance Australia
          Substance Abuse, Intravenous Epidemiology
          Adolescence
          Adult
          Australia
          Cross Sectional Studies
          Data Analysis Software
          Descriptive Statistics
          Epidemiological Research
          Female
          Health Resource Utilization
          Male
          Middle Age
          Needle Exchange Programs
          Regression
          Substance Abuse, Intravenous Mortality
          Substance Use Rehabilitation Programs
          Human
          Adolescent: 13-18 years
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Female
          Male
      ab: AIMS: (i) To compare indirect estimation methods to obtain mean injecting drug use (IDU) prevalence for a confined geographic location; and (ii) to use these estimates to calculate IDU and injection coverage of a medically supervised injecting facility. DESIGN: Multiple indirect prevalence estimation methods. SETTING: Kings Cross, Sydney, Australia. PARTICIPANTS: IDUs residing in Kings Cross area postcodes recorded in surveillance data of the Sydney Medically Supervised Injecting Centre (MSIC) between November 2001 and October 2002. MEASUREMENTS: Two closed and one open capture-recapture (CRC) models (Poisson regression, truncated Poisson and Jolly-Seber, respectively) were fitted to the observed data. Multiplier estimates were derived from opioid overdose mortality data and a cross-sectional survey of needle and syringe programme attendees. MSIC client injection frequency and the number of needles and syringes distributed in the study area were used to estimate injection prevalence and injection coverage. FINDINGS: From three convergent estimates, the mean estimated size of the IDU population aged 15-54 years was 1103 (range 877-1288), yielding a population prevalence of 3.6% (2.9-4.3%). Mean IDU coverage was 70.7% (range 59.1-86.7%) and the mean adjusted injection coverage was 8.8% (range 7.3-10.8%). Approximately 11.3% of the total IDU population were estimated to be new entrants to the population per month. CONCLUSIONS: Credible local area IDU prevalence estimates using MSIC surveillance data were obtained. MSIC appears to achieve high coverage of the local IDU population, although only an estimated one in 10 injections occurs at MSIC. Future prevalence estimation efforts should incorporate open models to capture the dynamic nature of IDU populations.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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