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Estimating prevalence of injecting drug users and associated heroin-related death rates in England by using regional data and incorporating prior information

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  • Ruth King
  • Sheila M. Bird
  • Antony M. Overstall
  • Gordon Hay
  • Sharon J. Hutchinson

Abstract

type="main" xml:id="rssa12011-abs-0001"> Injecting drug users (IDUs) have a direct social and economic effect yet can typically be regarded as a hidden population within a community. We estimate the size of the IDU population across the nine different Government Office regions of England in 2005–2006 by using capture–recapture methods with age (ranging from 15 to 64 years) and gender as covariate information. We consider a Bayesian model averaging approach using log-linear models, where we can include explicit prior information within the analysis in relation to the total IDU population (elicited from the number of drug-related deaths and injectors’ drug-related death rates). Estimation at the regional level allows for regional heterogeneity with these regional estimates aggregated to obtain a posterior mean estimate for the number of England's IDUs of 195840 with 95% credible interval (181700, 210480). There is significant variation in the estimated regional prevalence of current IDUs per million of population aged 15–64 years, and in injecting drug-related death rates across the gender × age cross-classifications. The propensity of an IDU to be seen by at least one source also exhibits strong regional variability with London having the lowest propensity of being observed (posterior mean probability 0.21) and the South West the highest propensity (posterior mean 0.46).

Suggested Citation

  • Ruth King & Sheila M. Bird & Antony M. Overstall & Gordon Hay & Sharon J. Hutchinson, 2014. "Estimating prevalence of injecting drug users and associated heroin-related death rates in England by using regional data and incorporating prior information," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(1), pages 209-236, January.
  • Handle: RePEc:bla:jorssa:v:177:y:2014:i:1:p:209-236
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    File URL: http://hdl.handle.net/10.1111/rssa.2013.177.issue-1
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    Cited by:

    1. Marco Alfò & Dankmar Böhning & Irene Rocchetti, 2021. "Upper bound estimators of the population size based on ordinal models for capture‐recapture experiments," Biometrics, The International Biometric Society, vol. 77(1), pages 237-248, March.
    2. Matthew R. Schofield & Richard J. Barker & William A. Link & Heloise Pavanato, 2023. "Estimating population size: The importance of model and estimator choice," Biometrics, The International Biometric Society, vol. 79(4), pages 3803-3817, December.

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