BACKGROUND: A recent systematic review observed that HIV prevalence amongst injectors is negligible (<1%) below a threshold HCV prevalence of 30%, but thereafter increases with HCV prevalence. We explore whether a model can reproduce these trends, what determines different epidemiological profiles and how this affects intervention impact. METHODS: An HIV/HCV transmission model was developed. Univariate sensitivity analyses determined whether the model projected a HCV prevalence threshold below which HIV is negligible, and how different behavioural and epidemiological factors affect the threshold. Multivariate uncertainty analyses considered whether the model could reproduce the observed breadth of HIV/HCV epidemics, how specific behavioural patterns produce different epidemic profiles, and how this affects an intervention's impact (reduces injecting risk by 30%). RESULTS: The model projected a HCV prevalence threshold, which varied depending on the heterogeneity in risk, mixing, and injecting duration in a setting. Multivariate uncertainty analyses showed the model could produce the same range of observed HIV/HCV epidemics. Variability in injecting transmission risk, degree of heterogeneity and injecting duration mainly determined different epidemic profiles. The intervention resulted in 50%/28% reduction in HIV incidence/prevalence and 37%/10% reduction in HCV incidence/prevalence over five years. For either infection, greater impact occurred in settings with lower prevalence of that infection and higher prevalence of the other infection. DISCUSSION: There are threshold levels of HCV prevalence below which HIV risk is negligible but these thresholds are likely to vary by setting. A setting's HIV and HCV prevalence may give insights into IDU risk behaviour and intervention impact.
BACKGROUND: A recent systematic review observed that HIV prevalence amongst injectors is negligible (<1%) below a threshold HCV prevalence of 30%, but thereafter increases with HCV prevalence. We explore whether a model can reproduce these trends, what determines different epidemiological profiles and how this affects intervention impact. METHODS: An HIV/HCV transmission model was developed. Univariate sensitivity analyses determined whether the model projected a HCV prevalence threshold below which HIV is negligible, and how different behavioural and epidemiological factors affect the threshold. Multivariate uncertainty analyses considered whether the model could reproduce the observed breadth of HIV/HCV epidemics, how specific behavioural patterns produce different epidemic profiles, and how this affects an intervention's impact (reduces injecting risk by 30%). RESULTS: The model projected a HCV prevalence threshold, which varied depending on the heterogeneity in risk, mixing, and injecting duration in a setting. Multivariate uncertainty analyses showed the model could produce the same range of observed HIV/HCV epidemics. Variability in injecting transmission risk, degree of heterogeneity and injecting duration mainly determined different epidemic profiles. The intervention resulted in 50%/28% reduction in HIV incidence/prevalence and 37%/10% reduction in HCV incidence/prevalence over five years. For either infection, greater impact occurred in settings with lower prevalence of that infection and higher prevalence of the other infection. DISCUSSION: There are threshold levels of HCV prevalence below which HIV risk is negligible but these thresholds are likely to vary by setting. A setting's HIV and HCV prevalence may give insights into IDU risk behaviour and intervention impact.
Authors: Carolyn F Wong; Karol Silva; Aleksandar Kecojevic; Sheree M Schrager; Jennifer Jackson Bloom; Ellen Iverson; Stephen E Lankenau Journal: Drug Alcohol Depend Date: 2013-02-28 Impact factor: 4.492
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Authors: Jeffrey W Eaton; Nicolas A Menzies; John Stover; Valentina Cambiano; Leonid Chindelevitch; Anne Cori; Jan A C Hontelez; Salal Humair; Cliff C Kerr; Daniel J Klein; Sharmistha Mishra; Kate M Mitchell; Brooke E Nichols; Peter Vickerman; Roel Bakker; Till Bärnighausen; Anna Bershteyn; David E Bloom; Marie-Claude Boily; Stewart T Chang; Ted Cohen; Peter J Dodd; Christophe Fraser; Chaitra Gopalappa; Jens Lundgren; Natasha K Martin; Evelinn Mikkelsen; Elisa Mountain; Quang D Pham; Michael Pickles; Andrew Phillips; Lucy Platt; Carel Pretorius; Holly J Prudden; Joshua A Salomon; David A M C van de Vijver; Sake J de Vlas; Bradley G Wagner; Richard G White; David P Wilson; Lei Zhang; John Blandford; Gesine Meyer-Rath; Michelle Remme; Paul Revill; Nalinee Sangrujee; Fern Terris-Prestholt; Meg Doherty; Nathan Shaffer; Philippa J Easterbrook; Gottfried Hirnschall; Timothy B Hallett Journal: Lancet Glob Health Date: 2013-12-10 Impact factor: 26.763