Literature DB >> 11282789

Estimating the relative incidence of heroin use: application of a method for adjusting observed reports of first visits to specialized drug treatment agencies.

M Hickman1, S Seaman, D de Angelis.   

Abstract

In this paper, the authors propose a method for estimating the incidence of heroin use by adjusting reported numbers of heroin users visiting drug treatment agencies for the time lag between onset of heroin use and first treatment request (lag distribution). The adjusted incidence is relative, since it represents the number of individuals beginning heroin use in each year whose cases will be reported within 8 years of starting use. Users with longer lag times or whose cases are never reported are excluded. Utilizing data from southeastern England (1991--1998), the authors analyzed the effects of covariates (sex, age group, ethnic group, route of consumption, and year of onset of drug use) on the lag distribution. Trends in the adjusted incidence of heroin use were very different for injectors and noninjectors: Incidence among injectors seemed to be stable, while in noninjectors it increased twofold between 1991 and 1996--1997. These results must be interpreted cautiously, especially in relation to the wider context of underlying trends in the population. Potential biases derive from underreporting and from changes in the proportion of heroin users in treatment. The lag correction method adds substantially to the value of routine treatment data, at least for heroin use, and is potentially the best method for obtaining estimates of incidence.

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Year:  2001        PMID: 11282789     DOI: 10.1093/aje/153.7.632

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  7 in total

1.  The dynamics of heroin use; implications for intervention.

Authors:  T Millar; N Craine; T Carnwath; M Donmall
Journal:  J Epidemiol Community Health       Date:  2001-12       Impact factor: 3.710

2.  Estimating the prevalence of injection drug users in the U.S. and in large U.S. metropolitan areas from 1992 to 2002.

Authors:  Joanne E Brady; Samuel R Friedman; Hannah L F Cooper; Peter L Flom; Barbara Tempalski; Karla Gostnell
Journal:  J Urban Health       Date:  2008-03-15       Impact factor: 3.671

3.  A decline in the prevalence of injecting drug users in Estonia, 2005-2009.

Authors:  Anneli Uusküla; Kristiina Rajaleid; Ave Talu; Katri Abel-Ollo; Don C Des Jarlais
Journal:  Int J Drug Policy       Date:  2013-01-03

4.  Modelling the force of infection for hepatitis B and hepatitis C in injecting drug users in England and Wales.

Authors:  A J Sutton; N J Gay; W J Edmunds; V D Hope; O N Gill; M Hickman
Journal:  BMC Infect Dis       Date:  2006-06-08       Impact factor: 3.090

5.  Modeling the initiation of others into injection drug use, using data from 2,500 injectors surveyed in Scotland during 2008-2009.

Authors:  Simon R White; Sharon J Hutchinson; Avril Taylor; Sheila M Bird
Journal:  Am J Epidemiol       Date:  2015-03-18       Impact factor: 4.897

6.  Estimating incidence trends in regular heroin use in 26 regions of Switzerland using methadone treatment data.

Authors:  Carlos Nordt; Karin Landolt; Rudolf Stohler
Journal:  Subst Abuse Treat Prev Policy       Date:  2009-06-12

7.  A multi-state model to estimate incidence of heroin use.

Authors:  Albert Sánchez-Niubò; Odd O Aalen; Antònia Domingo-Salvany; Ellen J Amundsen; Josep Fortiana; Kjetil Røysland
Journal:  BMC Med Res Methodol       Date:  2013-01-14       Impact factor: 4.615

  7 in total

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