Department of Medicine, University of California San Diego, San Diego, CA, USA.
Houston Health Department, Houston, TX, USA.
Sci Rep. 2022 Nov 10;12(1):19230. doi: 10.1038/s41598-022-21924-8.
Detection of viral transmission clusters using molecular epidemiology is critical to the response pillar of the Ending the HIV Epidemic initiative. Here, we studied whether inference with an incomplete dataset would influence the accuracy of the reconstructed molecular transmission network. We analyzed viral sequence data available from ~ 13,000 individuals with diagnosed HIV (2012-2019) from Houston Health Department surveillance data with 53% completeness (n = 6852 individuals with sequences). We extracted random subsamples and compared the resulting reconstructed networks versus the full-size network. Increasing simulated completeness was associated with an increase in the number of detected clusters. We also subsampled based on the network node influence in the transmission of the virus where we measured Expected Force (ExF) for each node in the network. We simulated the removal of nodes with the highest and then lowest ExF from the full dataset and discovered that 4.7% and 60% of priority clusters were detected respectively. These results highlight the non-uniform impact of capturing high influence nodes in identifying transmission clusters. Although increasing sequence reporting completeness is the way to fully detect HIV transmission patterns, reaching high completeness has remained challenging in the real world. Hence, we suggest taking a network science approach to enhance performance of molecular cluster detection, augmented by node influence information.
利用分子流行病学检测病毒传播簇对于终结艾滋病流行倡议的应对支柱至关重要。在这里，我们研究了在数据集不完整的情况下进行推断是否会影响重建分子传播网络的准确性。我们分析了休斯顿卫生部监测数据中约 13000 名诊断为 HIV 的个体的病毒序列数据，数据完整性为 53%（n=6852 名有序列的个体）。我们提取了随机样本，并将得到的重建网络与全尺寸网络进行了比较。模拟完整性的增加与检测到的簇数量的增加有关。我们还根据病毒传播过程中网络节点的影响进行了抽样，其中我们测量了网络中每个节点的预期力（ExF）。我们从全数据集模拟了删除具有最高和最低 ExF 的节点，并发现分别检测到了 4.7%和 60%的优先级簇。这些结果突出表明，在识别传播簇时，捕获高影响节点对识别传播簇的影响是非均匀的。虽然增加序列报告的完整性是全面检测 HIV 传播模式的方法，但在现实世界中达到高完整性一直具有挑战性。因此，我们建议采取网络科学方法来增强分子簇检测的性能，并辅以节点影响信息。
