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Methods for population size estimation of problem drug users using a single registration
Authors:Peter GM van der Heijden  Guus Cruts  Maarten Cruyff
Institution:1. Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, PO Box 80140, NL-3508 TC Utrecht, The Netherlands;2. Trimbos Institute, Netherlands Institute of Mental Health and Addiction, PO Box 725, NL-3500 AS Utrecht, The Netherlands;1. Medical Students Research Center of International Campus, Tehran University of Medical Sciences, Tehran, Iran;2. University of Social Welfare and Rehabilitation Sciences, Tehran, Iran;1. Ukrainian Institute on Public Health Policy, 4 Malopidvalna Str., Office 6, Kyiv 01001, Ukraine;2. Yale University School of Medicine, New Haven, CT, USA;3. Yale University School of Public Health, 135 College Street, Suite 323, New Haven, CT 06510-2283, USA;1. Centre for Population Health, Burnet Institute, 85 Commercial Road, Melbourne, Victoria 3004, Australia;2. School of Public Health and Preventive Medicine, Monash University, Victoria 3800, Australia;1. Centre for Applied Research in Mental Health and Addiction, Faculty of Health Sciences, Simon Fraser University, Vancouver, Canada;2. Social and Epidemiological Research, Centre for Addiction and Mental Health, Toronto, Canada;3. Department of Psychiatry, University of Toronto, Toronto, Canada;4. Institute of Psychiatry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;5. Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, Brazil;6. Infectious Diseases Division, University of Ottawa, Ottawa, Canada
Abstract:BackgroundThe number of problem drug users is used as a key indicator to monitor the drug situation in the European Union. An alternative approach to estimate the number of problem drug users is given by ‘the one-source capture–recapture analysis’ that uses a single registration.MethodsTwo variants of the one-source capture–recapture analysis were applied to a single registration: the truncated Poisson regression model (TPR) and the Zelterman regression model. These models were applied to data about clinical drug-related hospital admissions derived from the Dutch Hospital Registration (LMR). The TPR accounts for heterogeneity in capture probabilities by allowing for covariates and the Zelterman regression model relies on the problem drug users that were seen only once or twice in the hospital; the latter model is known to be robust against unobserved heterogeneity.ResultsThe TPR model was found to have a bad fit due to unobserved heterogeneity. The Zelterman regression model estimated the population size at 10,415 problem drug users (95% CI is 8400–12,429). This figure is an estimate of the number of problem drug users who are at risk of a clinical hospital admission due to the medical consequences of their drug use. The model can also provide estimates of different subgroups of problematic drug users.ConclusionThe method presented here offers a promising alternative for estimating the number of problem drug users, including different subgroups of drug users. In addition, observed and unobserved heterogeneity can be accounted for in these estimates.
Keywords:Estimation  Single registration capture recapture  Problem drug users
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