Dasgupta Sharoda, France Anne Marie, Brandt Mary-Grace, Reuer Jennifer, Zhang Tianchi, Panneer Nivedha, Hernandez Angela L, Oster Alexandra M
1 Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention , Atlanta, Georgia .
2 Michigan Department of Health and Human Services, Southfield, Michigan.
AIDS Res Hum Retroviruses. 2019 Apr;35(4):368-375. doi: 10.1089/AID.2018.0181. Epub 2018 Dec 20.
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.
HIV核苷酸序列数据能够识别出感染基因相似毒株的人群集群，这表明存在病毒传播。我们模拟了数据完整性降低（由报告了序列的HIV确诊患者百分比定义）对传播模式以及对不断扩大的HIV传播集群检测的影响。我们分析了2008年至2014年期间居住在密歇根州或华盛顿州的HIV确诊患者的HIV监测数据。我们计算了基因距离，构建了每个辖区的推断传播网络，并将完整数据集中的传播网络特征以及对不断扩大的传播集群的检测与人为减少的数据集进行了比较。模拟较低的完整性水平导致与集群相关联的人群百分比从高完整性（完整数据集）到低完整性（5%）有所下降（密歇根州：54% - 18%；华盛顿州：46% - 16%）。随着数据完整性水平降低，某些人群之间的传播模式仍然很明显。随着数据完整性被人为降低，两个州集群检测的敏感性都大幅下降。在密歇根州，敏感性从完整数据集时的100%降至完整性为50%时的62%以及完整性为25%时的21%。在华盛顿州，敏感性从完整数据集时的100%降至完整性为50%时的71%以及完整性为25%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，即使数据完整性较低，在数量充足时也可以对传播模式进行推断。数据完整性应被优先考虑，因为未能检测到或延迟检测传播集群可能导致更多感染。
