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建模异烟肼预防治疗在 HIV 流行地区降低结核病的效果:网络结构的影响。

Modelling the performance of isoniazid preventive therapy for reducing tuberculosis in HIV endemic settings: the effects of network structure.

机构信息

Bristol Centre for Complexity Sciences, University of Bristol, Bristol, UK.

出版信息

J R Soc Interface. 2011 Oct 7;8(63):1510-20. doi: 10.1098/rsif.2011.0160. Epub 2011 Apr 20.

Abstract

Individuals living with HIV experience a much higher risk of progression from latent M. tuberculosis infection to active tuberculosis (TB) disease relative to individuals with intact immune systems. A several-month daily course of a single drug during latent infection (i.e. isoniazid preventive therapy (IPT)) has proved in clinical trials to substantially reduce an HIV-infected individual's risk of TB disease. As a result of these findings and ongoing studies, the World Health Organization has produced strong guidelines for implementing IPT on a community-wide scale for individuals with HIV at risk of TB disease. To date, there has been limited use of IPT at a community-wide level. In this paper, we present a new co-network model for HIV and TB co-epidemics to address questions about how the population-level impact of community-wide IPT may differ from the individual-level impact of IPT offered to selected individuals. In particular, we examine how the effect of clustering of contacts within high-TB incidence communities may affect the rates of re-infection with TB and how this clustering modifies the expected population-level effects of IPT. We find that populations with clustering of respiratory contacts experience aggregation of TB cases and high numbers of re-infection events. While, encouragingly, the overall population-level effects of community-wide IPT appear to be sustained regardless of network structure, we find that in populations where these contacts are highly clustered, there is dramatic heterogeneity in the impact of IPT: in some sub-regions of these populations, TB is nearly eliminated, while in others, repeated re-infection almost completely undermines the effect of IPT. Our findings imply that as IPT programmes are brought to scale, we should expect local heterogeneity of effectiveness as a result of the complex patterns of disease transmission within communities.

摘要

个体在感染 HIV 后,潜伏性结核分枝杆菌感染向活动性结核病(TB)发展的风险比免疫系统健全的个体要高得多。在潜伏感染期间(即异烟肼预防治疗(IPT))每日使用单一药物持续数月,临床试验已证明可显著降低 HIV 感染者患 TB 病的风险。基于这些发现和正在进行的研究,世界卫生组织制定了关于在广泛的社区范围内为有 TB 病风险的 HIV 感染者实施 IPT 的强有力指南。迄今为止,IPT 在社区范围内的应用有限。在本文中,我们提出了一种新的 HIV 和 TB 共流行的联合网络模型,以解决关于社区范围内广泛开展 IPT 的人群水平影响与为选定个体提供的 IPT 的个体水平影响可能存在差异的问题。特别是,我们研究了高 TB 发病率社区内接触者的聚集如何影响 TB 再感染率,以及这种聚集如何改变 IPT 的预期人群水平效应。我们发现,呼吸接触者聚集的人群中,TB 病例会聚集,再感染事件也会很多。虽然令人鼓舞的是,无论网络结构如何,IPT 的总体人群水平效果似乎都得到了维持,但我们发现,在这些接触者高度聚集的人群中,IPT 的影响存在显著的异质性:在这些人群的一些子区域,TB 几乎被消除,而在其他子区域,反复再感染几乎完全削弱了 IPT 的效果。我们的研究结果表明,随着 IPT 项目的推广,我们应该预期由于社区内疾病传播的复杂模式,IPT 的有效性会存在局部异质性。

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