AIMS: (i) To compare indirect estimation methods to obtain mean injecting drug use (IDU) prevalence for a confined geographic location; and (ii) to use these estimates to calculate IDU and injection coverage of a medically supervised injecting facility. DESIGN: Multiple indirect prevalence estimation methods. SETTING: Kings Cross, Sydney, Australia. PARTICIPANTS: IDUs residing in Kings Cross area postcodes recorded in surveillance data of the Sydney Medically Supervised Injecting Centre (MSIC) between November 2001 and October 2002. MEASUREMENTS: Two closed and one open capture-recapture (CRC) models (Poisson regression, truncated Poisson and Jolly-Seber, respectively) were fitted to the observed data. Multiplier estimates were derived from opioid overdose mortality data and a cross-sectional survey of needle and syringe programme attendees. MSIC client injection frequency and the number of needles and syringes distributed in the study area were used to estimate injection prevalence and injection coverage. FINDINGS: From three convergent estimates, the mean estimated size of the IDU population aged 15-54 years was 1103 (range 877-1288), yielding a population prevalence of 3.6% (2.9-4.3%). Mean IDU coverage was 70.7% (range 59.1-86.7%) and the mean adjusted injection coverage was 8.8% (range 7.3-10.8%). Approximately 11.3% of the total IDU population were estimated to be new entrants to the population per month. CONCLUSIONS: Credible local area IDU prevalence estimates using MSIC surveillance data were obtained. MSIC appears to achieve high coverage of the local IDU population, although only an estimated one in 10 injections occurs at MSIC. Future prevalence estimation efforts should incorporate open models to capture the dynamic nature of IDU populations.
AIMS: (i) To compare indirect estimation methods to obtain mean injecting drug use (IDU) prevalence for a confined geographic location; and (ii) to use these estimates to calculate IDU and injection coverage of a medically supervised injecting facility. DESIGN: Multiple indirect prevalence estimation methods. SETTING: Kings Cross, Sydney, Australia. PARTICIPANTS: IDUs residing in Kings Cross area postcodes recorded in surveillance data of the Sydney Medically Supervised Injecting Centre (MSIC) between November 2001 and October 2002. MEASUREMENTS: Two closed and one open capture-recapture (CRC) models (Poisson regression, truncated Poisson and Jolly-Seber, respectively) were fitted to the observed data. Multiplier estimates were derived from opioid overdose mortality data and a cross-sectional survey of needle and syringe programme attendees. MSIC client injection frequency and the number of needles and syringes distributed in the study area were used to estimate injection prevalence and injection coverage. FINDINGS: From three convergent estimates, the mean estimated size of the IDU population aged 15-54 years was 1103 (range 877-1288), yielding a population prevalence of 3.6% (2.9-4.3%). Mean IDU coverage was 70.7% (range 59.1-86.7%) and the mean adjusted injection coverage was 8.8% (range 7.3-10.8%). Approximately 11.3% of the total IDU population were estimated to be new entrants to the population per month. CONCLUSIONS: Credible local area IDU prevalence estimates using MSIC surveillance data were obtained. MSIC appears to achieve high coverage of the local IDU population, although only an estimated one in 10 injections occurs at MSIC. Future prevalence estimation efforts should incorporate open models to capture the dynamic nature of IDU populations.
Authors: Heather Bradley; Elizabeth M Rosenthal; Meredith A Barranco; Tomoko Udo; Patrick S Sullivan; Eli S Rosenberg Journal: J Infect Dis Date: 2020-09-02 Impact factor: 5.226
Authors: Hayley E Jones; Matthew Hickman; Barbara Kasprzyk-Hordern; Nicky J Welton; David R Baker; A E Ades Journal: Sci Total Environ Date: 2014-03-15 Impact factor: 7.963
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