AIM: This study sought to estimate the prevalence of injecting drug users (IDU) in Togliatti city and to examine the implications of these estimates for HIV prevalence and harm reduction. DESIGN: Routine data sources of IDUs were identified. Covariate capture-recapture techniques were used on the individuals identified on the three data sources and used to estimate the number of IDU 'not observed' by the data sources, and thereby estimate the prevalence of IDU. SETTING: Togliatti City, Samara Oblast, Russian Federation. PARTICIPANTS: IDUs recorded on three data sources (narcology records, HIV positive test results and police arrest data) during 2001. MEASUREMENTS: Poisson regression models were fitted to the observed data, with interactions between data sources fitted to replicate 'dependencies' between those data sources. To select the best model the goodness of fit was approximated by chi2 distribution and the best-fitting model was selected on the basis of standard information criteria and log likelihood ratio tests. FINDINGS: The total estimated population of IDUs is 20 226 [95% confidence interval (CI): 16 971-24 749] giving a population prevalence of 5.4% (95% CI: 4.5-6.6%) of the registered population and 2.7% (95% CI: 2.4-3.5%) of the population (including migrants) aged 15-44 years. For every one IDU in contact with a service there were three out of contact. CONCLUSIONS: There is a high prevalence of IDU which, in the context of a fast-emerging IDU-associated HIV epidemic, will have serious public health implications.
AIM: This study sought to estimate the prevalence of injecting drug users (IDU) in Togliatti city and to examine the implications of these estimates for HIV prevalence and harm reduction. DESIGN: Routine data sources of IDUs were identified. Covariate capture-recapture techniques were used on the individuals identified on the three data sources and used to estimate the number of IDU 'not observed' by the data sources, and thereby estimate the prevalence of IDU. SETTING: Togliatti City, Samara Oblast, Russian Federation. PARTICIPANTS: IDUs recorded on three data sources (narcology records, HIV positive test results and police arrest data) during 2001. MEASUREMENTS: Poisson regression models were fitted to the observed data, with interactions between data sources fitted to replicate 'dependencies' between those data sources. To select the best model the goodness of fit was approximated by chi2 distribution and the best-fitting model was selected on the basis of standard information criteria and log likelihood ratio tests. FINDINGS: The total estimated population of IDUs is 20 226 [95% confidence interval (CI): 16 971-24 749] giving a population prevalence of 5.4% (95% CI: 4.5-6.6%) of the registered population and 2.7% (95% CI: 2.4-3.5%) of the population (including migrants) aged 15-44 years. For every one IDU in contact with a service there were three out of contact. CONCLUSIONS: There is a high prevalence of IDU which, in the context of a fast-emerging IDU-associated HIV epidemic, will have serious public health implications.
Authors: Catherine S Todd; Abdullah M S Abed; Paul T Scott; Naqibullah Safi; Kenneth C Earhart; Steffanie A Strathdee Journal: Subst Use Misuse Date: 2009 Impact factor: 2.164
Authors: Hayley E Jones; Matthew Hickman; Nicky J Welton; Daniela De Angelis; Ross J Harris; A E Ades Journal: Am J Epidemiol Date: 2014-04-11 Impact factor: 4.897