HCV prevalence can predict HIV epidemic potential among people who inject drugs: mathematical modeling analysis.
HCV prevalence can predict HIV epidemic potential among people who inject drugs: mathematical modeling analysis.
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DOI：
10.1186/s12889-016-3887-y
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发表时间：
2016-12-03
影响因子：
4.5
通讯作者：
Abu-Raddad LJ
中科院分区：
文献类型：
--
作者：
Akbarzadeh V;Mumtaz GR;Awad SF;Weiss HA;Abu-Raddad LJ
丙型肝炎病毒（HCV）和艾滋病毒都是通过注射毒品（PWID）人群中的经皮接触传播的。对全球流行病学数据的生态分析发现，在PWID中HCV和HIV流行率之间存在正相关。我们的目的是证明如何HCV的流行率可以用来预测艾滋病毒的流行潜力PWID。建立了两个群体水平的模型来模拟PWID中HCV和HIV流行的演变。该模型描述了HCV和HIV的肠道外传播，并解决了确定性和随机。建模结果提供了一个很好的适合描述生态HCV和HIV的PWID之间的关联的流行病学数据。据估计，HCV的传染性是HIV的8倍。确定了可持续HIV流行（HIV流行率>1%）和集中HIV流行（HIV流行率>5%）的阈值HCV流行率分别为29.0%（95%不确定性区间（UI）：20.7-39.8）和46.5%（95% UI：37.6-56.6）。HCV和HIV之间的关联进一步描述了6个动态机制，描述了两种感染的重叠流行病学，并使用定义和估计的关联措施进行量化。在广泛的丙型肝炎病毒流行率的建模预测表明，在地方病平衡预测艾滋病毒流行率的整体可接受的精度。建模预测被认为是强大的随机性和行为和生物参数的不确定性。在一个说明性的应用的方法，在伊朗流行的艾滋病毒流行的建模预测同意在这个国家的艾滋病毒流行的规模和时间过程。我们的研究结果表明，丙型肝炎病毒的流行率可以作为一个代理生物标志物的艾滋病毒流行病的潜力之间PWID，和艾滋病毒流行病的扩展的规模和演变可以预测有足够的精度，告知艾滋病毒的政策，规划和资源分配。本文的在线版本（doi：10.1186/s12889-016-3887-y）包含补充材料，可供授权用户使用。
Hepatitis C virus (HCV) and HIV are both transmitted through percutaneous exposures among people who inject drugs (PWID). Ecological analyses on global epidemiological data have identified a positive association between HCV and HIV prevalence among PWID. Our objective was to demonstrate how HCV prevalence can be used to predict HIV epidemic potential among PWID. Two population-level models were constructed to simulate the evolution of HCV and HIV epidemics among PWID. The models described HCV and HIV parenteral transmission, and were solved both deterministically and stochastically. The modeling results provided a good fit to the epidemiological data describing the ecological HCV and HIV association among PWID. HCV was estimated to be eight times more transmissible per shared injection than HIV. A threshold HCV prevalence of 29.0% (95% uncertainty interval (UI): 20.7-39.8) and 46.5% (95% UI: 37.6-56.6) were identified for a sustainable HIV epidemic (HIV prevalence >1%) and concentrated HIV epidemic (HIV prevalence >5%), respectively. The association between HCV and HIV was further described with six dynamical regimes depicting the overlapping epidemiology of the two infections, and was quantified using defined and estimated measures of association. Modeling predictions across a wide range of HCV prevalence indicated overall acceptable precision in predicting HIV prevalence at endemic equilibrium. Modeling predictions were found to be robust with respect to stochasticity and behavioral and biological parameter uncertainty. In an illustrative application of the methodology, the modeling predictions of endemic HIV prevalence in Iran agreed with the scale and time course of the HIV epidemic in this country. Our results show that HCV prevalence can be used as a proxy biomarker of HIV epidemic potential among PWID, and that the scale and evolution of HIV epidemic expansion can be predicted with sufficient precision to inform HIV policy, programming, and resource allocation. The online version of this article (doi:10.1186/s12889-016-3887-y) contains supplementary material, which is available to authorized users.
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