Estimating Effects of HIV Sequencing Data Completeness on Transmission Network Patterns and Detection of Growing HIV Transmission Clusters
Estimating Effects of HIV Sequencing Data Completeness on Transmission Network Patterns and Detection of Growing HIV Transmission Clusters
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DOI：
10.1089/aid.2018.0181
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发表时间：
2019-04-01
影响因子：
1.5
通讯作者：
Oster, Alexandra M.
中科院分区：
文献类型：
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作者：
Dasgupta, Sharoda;France, Anne Marie;Oster, Alexandra M.
艾滋病毒核苷酸序列数据可以确定具有遗传相似菌株的人群，表明传播。我们模拟了降低数据完整性的影响，定义为具有报告序列的确诊HIV患者的百分比，对传播模式和不断增长的HIV传播集群的检测。我们分析了2008年至2014年期间居住在密歇根州或华盛顿的艾滋病病毒感染者的艾滋病病毒监测数据。我们计算了遗传距离，为每个管辖区构建了推断的传输网络，并将传输网络特征和完整数据集中不断增长的传输集群的检测与人工减少的数据集进行了比较。模拟较低水平的完整性导致与高完整性（完整数据集）到低完整性（5%）的聚类相关的人员百分比下降（密歇根州：54%-18%;华盛顿，46%-16%）。随着数据完整性水平的降低，某些人群之间的传播模式仍然很强。由于数据的完整性被人为地降低了，聚类检测的灵敏度在这两个国家大大降低。在密歇根州，敏感性从完整数据集的100%下降到50%完整性的62%和25%完整性的21%。在华盛顿，敏感性从完整数据集的100%下降到50%完整性时的71%和25%完整性时的29%。较低的序列数据完整性限制了检测可能受益于调查的集群的能力;然而，即使数据完整性低，只要有足够的数量，也可以对传输模式进行推断。应优先考虑数据的完整性，因为缺乏或延迟发现传播集群可能导致更多的感染。
HIV nucleotide sequence data can identify clusters of persons with genetically similar strains suggesting transmission. We simulated the effect of lowered data completeness, defined by the percent of persons with diagnosed HIV with a reported sequence, on transmission patterns and detection of growing HIV transmission clusters. We analyzed HIV surveillance data for persons with HIV diagnosed during 2008-2014 who resided in Michigan or Washington. We calculated genetic distances, constructed the inferred transmission network for each jurisdiction, and compared transmission network characteristics and detection of growing transmission clusters in the full dataset with artificially reduced datasets. Simulating lower levels of completeness resulted in decreased percentages of persons linked to a cluster from high completeness (full dataset) to low completeness (5%) (Michigan: 54%-18%; Washington, 46%-16%). Patterns of transmission between certain populations remained robust as data completeness level was reduced. As data completeness was artificially decreased, sensitivity of cluster detection substantially diminished in both states. In Michigan, sensitivity decreased from 100% with the full dataset, to 62% at 50% completeness and 21% at 25% completeness. In Washington, sensitivity decreased from 100% with the full dataset, to 71% at 50% completeness and 29% at 25% completeness. Lower sequence data completeness limits the ability to detect clusters that may benefit from investigation; however, inferences can be made about transmission patterns even with low data completeness, given sufficient numbers. Data completeness should be prioritized, as lack of or delays in detection of transmission clusters could result in additional infections.