HIV Care Prioritization Using Phylogenetic Branch Length.
HIV Care Prioritization Using Phylogenetic Branch Length.
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DOI：
10.1097/qai.0000000000002612
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发表时间：
2021-04-15
期刊：
影响因子：
--
通讯作者：
Mirarab S
中科院分区：
文献类型：
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作者：
Moshiri N;Smith DM;Mirarab S
艾滋病毒传播网络的结构可以由少数人决定。公共卫生干预措施，例如确保艾滋病毒感染者坚持抗逆转录病毒治疗并继续抑制病毒，可以帮助控制病毒的传播。然而，这种干预需要利用有限的公共卫生资源拨款。确定哪些人最有可能传播艾滋病毒，可以使公共卫生官员将有限的资源集中在这些人身上。分子流行病学可以根据从病毒序列中推断出的传播模式，帮助确定艾滋病毒感染者的优先顺序。这种优先级划分以前已被建议并通过监测集群增长来执行。在本文中，我们介绍了ProACT（使用祖先边缘长度优先排序），这是一种用于优先排序艾滋病毒感染者的系统发育方法。ProACT从序列数据推断的系统发育开始，根据末端分支长度对个体进行排序，使用祖先分支长度打破联系。我们对2005年至2014年在圣地亚哥获得的926个HIV-1亚型B pol数据的真实数据集和模拟相同流行病的模拟数据集进行了ProACT评估。优先排序方法通过预测优先排序后传输最多的个体的能力进行比较。在所有模拟条件和大多数真实数据采样条件下，ProACT在优先级效率的多个指标上优于监控集群增长。与依靠监测基于遗传距离定义的传播集群增长的最先进方法相比，ProACT使用的简单策略提高了优先排序的有效性。
The structure of the HIV transmission networks can be dictated by just a few individuals. Public health intervention, such as ensuring people living with HIV adhere to antiretroviral therapy and remain virally-suppressed, can help control the spread of the virus. However, such intervention requires utilizing limited public health resource allocations. Determining which individuals are most at risk of transmitting HIV could allow public health officials to focus their limited resources on these individuals. Molecular epidemiology can help prioritize people living with HIV by patterns of transmission inferred from their sampled viral sequences. Such prioritization has been previously suggested and performed by monitoring cluster growth. In this paper, we introduce ProACT (Prioritization using AnCesTral edge lengths), a phylogenetic approach for prioritizing individuals living with HIV. ProACT starts from a phylogeny inferred from sequence data and orders individuals according to their terminal branch length, breaking ties using ancestral branch lengths. We evaluated ProACT on a real dataset of 926 HIV-1 subtype B pol data obtained in San Diego between 2005 and 2014, and a simulation datasets modelling the same epidemic. Prioritization methods are compared by their ability to predict individuals who transmit most after the prioritization. Across all simulation conditions and most real data sampling conditions, ProACT outperformed monitoring cluster growth for multiple metrics of prioritization efficacy. The simple strategy used by ProACT improves the effectiveness of prioritization compared to state-of-the-art methods that rely on monitoring the growth of transmission clusters defined based on genetic distance.