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丙型肝炎病毒(HCV)预防的数学建模:文献综述及消除策略的见解。

Mathematical modeling of hepatitis c virus (HCV) prevention among people who inject drugs: A review of the literature and insights for elimination strategies.

机构信息

IQVIA, Copenhagen, Denmark.

Division of Infectious Diseases and Global Public Health, University of California San Diego, CA, USA.

出版信息

J Theor Biol. 2019 Nov 21;481:194-201. doi: 10.1016/j.jtbi.2018.11.013. Epub 2018 Nov 16.

DOI:10.1016/j.jtbi.2018.11.013
PMID:30452959
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6522340/
Abstract

In 2016, the World Health Organization issued global elimination targets for hepatitis C virus (HCV), including an 80% reduction in HCV incidence by 2030. The vast majority of new HCV infections occur among people who inject drugs (PWID), and as such elimination strategies require particular focus on this population. As governments urgently require guidance on how to achieve elimination among PWID, mathematical modeling can provide critical information on the level and targeting of intervention are required. In this paper we review the epidemic modeling literature on HCV transmission and prevention among PWID, highlight main differences in mathematical formulation, and discuss key insights provided by these models in terms of achieving WHO elimination targets among PWID. Overall, the vast majority of modeling studies utilized a deterministic compartmental susceptible-infected-susceptible structure, with select studies utilizing individual-based network transmission models. In general, these studies found that harm reduction alone is unlikely to achieve elimination targets among PWID. However, modeling indicates elimination is achievable in a wide variety of epidemic settings with harm reduction scale-up combined with modest levels of HCV treatment for PWID. Unfortunately, current levels of testing and treatment are generally insufficient to achieve elimination in most settings, and require further scale-up. Additionally, network-based treatment strategies as well as prison-based treatment and harm reduction provision could provide important additional population benefits. Overall, epidemic modeling has and continues to play a critical role in informing HCV elimination strategies worldwide.

摘要

2016 年,世界卫生组织发布了丙型肝炎病毒(HCV)全球消除目标,包括到 2030 年将 HCV 发病率降低 80%。绝大多数新的 HCV 感染发生在注射毒品者(PWID)中,因此消除策略需要特别关注这一人群。由于各国政府迫切需要关于如何在 PWID 中实现消除的指导,数学建模可以提供有关干预水平和目标的关键信息。在本文中,我们回顾了 HCV 在 PWID 中传播和预防的流行建模文献,强调了数学公式中的主要差异,并讨论了这些模型在 PWID 中实现世卫组织消除目标方面提供的关键见解。总体而言,绝大多数建模研究都采用了确定性的房室易感感染易感性结构,而一些研究则采用了基于个体的网络传播模型。一般来说,这些研究发现,仅减少伤害不太可能在 PWID 中实现消除目标。然而,建模表明,在广泛的流行环境中,通过扩大减少伤害措施并对 PWID 进行适度的 HCV 治疗,可以实现消除。不幸的是,目前的检测和治疗水平在大多数情况下通常不足以实现消除,需要进一步扩大规模。此外,基于网络的治疗策略以及监狱内的治疗和减少伤害措施可以为人群提供重要的额外效益。总体而言,流行建模已经并将继续在为全球 HCV 消除策略提供信息方面发挥关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/6522340/deadaaa9f123/nihms-1007905-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/6522340/fa5768fc0e9a/nihms-1007905-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/6522340/deadaaa9f123/nihms-1007905-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/6522340/fa5768fc0e9a/nihms-1007905-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/6522340/deadaaa9f123/nihms-1007905-f0002.jpg

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