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首页> 外文期刊>Journal of the International Aids Society >Eliminating hepatitis C virus as a public health threat among HIV‐positive men who have sex with men: a multi‐modelling approach to understand differences in sexual risk behaviour
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Eliminating hepatitis C virus as a public health threat among HIV‐positive men who have sex with men: a multi‐modelling approach to understand differences in sexual risk behaviour

机译:在与男性发生性关系的艾滋病毒阳性男性中消除丙型肝炎病毒对公共健康的威胁:一种多模型的方法来了解性风险行为的差异

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IntroductionOutbreaks of hepatitis C virus (HCV) infections among HIV-positive men who have sex with men (MSM) have been observed globally. Using a multi-modelling approach we estimate the time and number of direct-acting antiviral treatment courses required to achieve an 80% reduction in HCV prevalence among HIV-positive MSM in the state of Victoria, Australia. MethodsThree models of HCV transmission, testing and treatment among MSM were compared: a dynamic compartmental model; an agent-based model (ABM) parametrized to local surveillance and behavioural data (“ABM1”); and an ABM with a more heterogeneous population (“ABM2”) to determine the influence of extreme variations in sexual risk behaviour. ResultsAmong approximately 5000 diagnosed HIV-positive MSM in Victoria, 10% are co-infected with HCV. ABM1 estimated that an 80% reduction in HCV prevalence could be achieved in 122 (inter-quartile range (IQR) 112 to 133) weeks with 523 (IQR 479 to 553) treatments if the average time from HCV diagnosis to treatment was six months. This was reduced to 77 (IQR 69 to 81) weeks if the average time between HCV diagnosis and treatment commencement was decreased to 16?weeks. Estimates were consistent across modelling approaches; however ABM2 produced fewer incident HCV cases, suggesting that treatment-as-prevention may be more effective in behaviourally heterogeneous populations. ConclusionsMajor reductions in HCV prevalence can be achieved among HIV-positive MSM within two years through routine HCV monitoring and prompt treatment as a part of HIV care. Compartmental models constructed with limited behavioural data are likely to produce conservative estimates compared to models of the same setting with more complex parametrizations.
机译:简介在全球范围内已观察到与男性发生性关系的HIV阳性男性中爆发丙型肝炎病毒(HCV)感染。使用多模型方法,我们估算了在澳大利亚维多利亚州实现HIV阳性MSM中HCV感染率降低80%所需的直接作用抗病毒治疗疗程的时间和数量。方法比较了MSM之间HCV传播,检测和治疗的三种模型:动态区室模型;动态区隔模型;动态区隔模型。基于本地监视和行为数据(“ ABM1”)的基于代理的模型(ABM);以及具有更多异类人群的“ ABM”(“ ABM2”)来确定性风险行为极端变化的影响。结果在维多利亚州约5000个被诊断为HIV阳性的MSM中,有10%与HCV共同感染。 ABM1估计,如果从HCV诊断到治疗的平均时间为六个月,则在523(IQR 479至553)治疗后的122周(四分位间距(IQR)112至133)周内,HCV患病率可降低80%。如果HCV诊断和开始治疗之间的平均时间减少到16周,则可以减少到77周(IQR 69到81)。各种建模方法的估算值是一致的;然而,ABM2产生的HCV感染病例较少,这表明预防性治疗可能在行为异质人群中更有效。结论通过常规的HCV监测和作为HIV护理的一部分的迅速治疗,可以在两年内使HIV阳性MSM的HCV感染率大大降低。与具有更复杂参数设置的相同环境的模型相比,使用有限的行为数据构建的隔间模型可能会产生保守的估计。

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