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评估从系统进化树推断出的 HIV 传播中年龄混合模式的不确定性。

Assessing the uncertainty around age-mixing patterns in HIV transmission inferred from phylogenetic trees.

机构信息

Division of Epidemiology & Biostatistics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.

The South African Department of Science and Technology-National Research Foundation (DST-NRF) Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Cape Town, South Africa.

出版信息

PLoS One. 2021 Mar 25;16(3):e0249013. doi: 10.1371/journal.pone.0249013. eCollection 2021.

Abstract

Understanding age-mixing patterns in Human Immunodeficiency Virus (HIV) transmission networks can enhance the design and implementation of HIV prevention strategies in sub-Saharan Africa. Due to ethical consideration, it is less likely possible to conduct a benchmark study to assess which sampling strategy, and sub-optimal sampling coverage which can yield best estimates for these patterns. We conducted a simulation study, using phylogenetic trees to infer estimates of age-mixing patterns in HIV transmission, through the computation of proportions of pairings between men and women, who were phylogenetically linked across different age groups (15-24 years, 25-39 years, and 40-49 years); and the means, and standard deviations of their age difference. We investigated also the uncertainty around these estimates as a function of the sampling coverage in four sampling strategies: when missing sequence data were missing completely at random (MCAR), and missing at random (MAR) with at most 30%-50%-70% of women in different age groups being in the sample. The results suggested that age-mixing patterns in HIV transmission can be unveiled from proportions of phylogenetic pairings between men and women across age groups; and the mean, and standard deviation of their age difference. A 55% sampling coverage was sufficient to provide the best values of estimates of age-mixing patterns in HIV transmission with MCAR scenario. But we should be cautious in interpreting proportions of men phylogenetically linked to women because they may be overestimated or underestimated, even at higher sampling coverage. The findings showed that, MCAR was the best sampling strategy. This means, it is advisable not to use sequence data collected in settings where we can find a systematic imbalance of age and gender to investigate age-mixing in HIV transmission. If not possible, ensure to take into consideration the imbalance in interpreting the results.

摘要

了解人类免疫缺陷病毒(HIV)传播网络中的年龄混合模式可以增强撒哈拉以南非洲地区 HIV 预防策略的设计和实施。由于伦理考虑,不太可能进行基准研究来评估哪种采样策略和次优采样覆盖率可以为这些模式提供最佳估计。我们进行了一项模拟研究,使用系统发育树来推断 HIV 传播中年龄混合模式的估计,通过计算在不同年龄组(15-24 岁、25-39 岁和 40-49 岁)之间具有系统发育联系的男性和女性之间配对的比例;以及它们年龄差异的平均值和标准差。我们还研究了这些估计值的不确定性,作为四个采样策略中采样覆盖率的函数:当缺失序列数据完全随机缺失(MCAR)时,以及缺失数据最多为 30%-50%-70%的女性处于不同年龄组的随机缺失(MAR)。结果表明,从男性和女性在不同年龄组之间的系统发育配对比例;以及它们年龄差异的平均值和标准差,可以揭示 HIV 传播中的年龄混合模式。MCAR 情景下,55%的采样覆盖率足以提供 HIV 传播中年龄混合模式估计的最佳值。但我们应该谨慎解释与女性具有系统发育联系的男性的比例,因为即使在更高的采样覆盖率下,它们也可能被高估或低估。研究结果表明,MCAR 是最佳采样策略。这意味着,在研究 HIV 传播中的年龄混合时,建议不要使用可能存在年龄和性别系统不平衡的环境中收集的序列数据。如果不可能,在解释结果时应注意考虑不平衡性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06ea/7993798/9db0a2c52ec0/pone.0249013.g001.jpg

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