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Methods for population size estimation of problem drug users using a single registration

Methods for population size estimation of problem drug users using a single registration
Methods for population size estimation of problem drug users using a single registration
Background: The 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.

Methods: Two 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.

Results: The 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.

Conclusion: The 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.
0955-3959
614-618
van der Heijden, Peter G.M.
85157917-3b33-4683-81be-713f987fd612
Cruts, Guus
09acc240-8a58-4020-81c6-c81293f82bc9
Cruyff, Maarten
68bcfa19-3d85-4b0f-a6a4-6e148b265f19
van der Heijden, Peter G.M.
85157917-3b33-4683-81be-713f987fd612
Cruts, Guus
09acc240-8a58-4020-81c6-c81293f82bc9
Cruyff, Maarten
68bcfa19-3d85-4b0f-a6a4-6e148b265f19

van der Heijden, Peter G.M., Cruts, Guus and Cruyff, Maarten (2013) Methods for population size estimation of problem drug users using a single registration. International Journal of Drug Policy, 24 (6), 614-618. (doi:10.1016/j.drugpo.2013.04.002). (PMID:23664789)

Record type: Article

Abstract

Background: The 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.

Methods: Two 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.

Results: The 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.

Conclusion: The 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.

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More information

Published date: 8 May 2013
Organisations: Social Statistics & Demography

Identifiers

Local EPrints ID: 369754
URI: http://eprints.soton.ac.uk/id/eprint/369754
ISSN: 0955-3959
PURE UUID: 723ebafc-6d54-45c1-bf0b-26f1b756a7e2
ORCID for Peter G.M. van der Heijden: ORCID iD orcid.org/0000-0002-3345-096X

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Date deposited: 06 Oct 2014 12:53
Last modified: 15 Mar 2024 03:46

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Author: Guus Cruts
Author: Maarten Cruyff

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