Characterization of Molecular Cluster Detection and Evaluation of Cluster Investigation Criteria Using Machine Learning Methods and Statewide Surveillance Data in Washington State
Characterization of Molecular Cluster Detection and Evaluation of Cluster Investigation Criteria Using Machine Learning Methods and Statewide Surveillance Data in Washington State
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DOI：
10.3390/v12020142
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发表时间：
2020-02-01
期刊：
影响因子：
4.7
通讯作者：
Reuer, Jennifer R.
中科院分区：
文献类型：
--
作者：
Erly, Steven J.;Herbeck, Joshua T.;Reuer, Jennifer R.
分子簇检测可用于阻断艾滋病毒传播，但依赖于识别可能传播的簇。我们描述了华盛顿州的分子聚类检测，评估了当前的聚类调查标准，并使用机器学习开发了一个标准。从2015年到2018年，对华盛顿州的艾滋病毒感染者（PLWH）、具有可分析基因型序列的人群和聚集性人群进行了人口统计学特征描述。描述了3个月和12个月集群生长与人口统计学、临床和时间预测因子之间的关系，并使用2016年至2017年的数据拟合随机森林模型。该模型识别未来传播集群的能力与2018年美国疾病控制与预防中心（CDC）和华盛顿州的标准进行了比较。具有基因型的人群与所有PLWH相似，但一个集群中的人群不成比例地是白人、男性和男男性行为者。随机森林模型选取的调查聚类在3个月内平均增长2.3例（95% CI 1.1 ~ 1.4），与CDC标准（2.0例，95% CI 0.5 ~ 3.4）相比，增幅不显著。分析的病例差异表明，分子聚类检测可能不会使所有人群受益。司法管辖区应使用辅助数据源进行预测或继续使用既定的调查标准。
Molecular cluster detection can be used to interrupt HIV transmission but is dependent on identifying clusters where transmission is likely. We characterized molecular cluster detection in Washington State, evaluated the current cluster investigation criteria, and developed a criterion using machine learning. The population living with HIV (PLWH) in Washington State, those with an analyzable genotype sequences, and those in clusters were described across demographic characteristics from 2015 to2018. The relationship between 3- and 12-month cluster growth and demographic, clinical, and temporal predictors were described, and a random forest model was fit using data from 2016 to 2017. The ability of this model to identify clusters with future transmission was compared to Centers for Disease Control and Prevention (CDC) and the Washington state criteria in 2018. The population with a genotype was similar to all PLWH, but people in a cluster were disproportionately white, male, and men who have sex with men. The clusters selected for investigation by the random forest model grew on average 2.3 cases (95% CI 1.1-1.4) in 3 months, which was not significantly larger than the CDC criteria (2.0 cases, 95% CI 0.5-3.4). Disparities in the cases analyzed suggest that molecular cluster detection may not benefit all populations. Jurisdictions should use auxiliary data sources for prediction or continue using established investigation criteria.