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评估完整的HIV-1基因组序列以估计南非农村社区的发病率和人口迁移情况。

Evaluating whole HIV-1 genome sequence for estimation of incidence and migration in a rural South African community.

作者信息

Nascimento Fabrícia F, Ragonnet-Cronin Manon, Golubchik Tanya, Danaviah Siva, Derache Anne, Fraser Christophe, Volz Erik

机构信息

Department of Infectious Disease Epidemiology, Imperial College London, London, UK.

Big Data Institute, University of Oxford, Oxford, UK.

出版信息

Wellcome Open Res. 2022 Jun 21;7:174. doi: 10.12688/wellcomeopenres.17891.1. eCollection 2022.

Abstract

South Africa has the largest number of people living with HIV (PLWHIV) in the world, with HIV prevalence and transmission patterns varying greatly between provinces. Transmission between regions is still poorly understood, but phylodynamics of HIV-1 evolution can reveal how many infections are attributable to contacts outside a given community. We analysed whole genome HIV-1 genetic sequences to estimate incidence and the proportion of transmissions between communities in Hlabisa, a rural South African community. We separately analysed HIV-1 for , , and genes sampled from 2,503 PLWHIV. We estimated time-scaled phylogenies by maximum likelihood under a molecular clock model. Phylodynamic models were fitted to time-scaled trees to estimate transmission rates, effective number of infections, incidence through time, and the proportion of infections imported to Hlabisa. We also partitioned time-scaled phylogenies with significantly different distributions of coalescent times. Phylodynamic analyses showed similar trends in epidemic growth rates between 1980 and 1990. Model-based estimates of incidence and effective number of infections were consistent across genes. Parameter estimates with were generally smaller than those estimated with and . When estimating the proportions of new infections in Hlabisa from immigration or transmission from external sources, our posterior median estimates were 85% (95% credible interval (CI) = 78%-92%) for , 62% (CI = 40%-78%) for , and 77% (CI = 58%-90%) for in 2015. Analysis of phylogenetic partitions by gene showed that most close global reference sequences clustered within a single partition. This suggests local evolving epidemics or potential unmeasured heterogeneity in the population. We estimated consistent epidemic dynamic trends for , and genes using phylodynamic models. There was a high probability that new infections were not attributable to endogenous transmission within Hlabisa, suggesting high inter-connectedness between communities in rural South Africa.

摘要

南非是世界上感染人类免疫缺陷病毒(HIV)人数最多的国家,各省之间的HIV流行率和传播模式差异很大。不同地区之间的传播情况仍知之甚少,但HIV-1进化的系统动力学可以揭示有多少感染可归因于特定社区之外的接触。我们分析了全基因组HIV-1基因序列,以估计南非农村社区赫拉比萨的发病率以及社区间传播的比例。我们分别分析了从2503名HIV感染者中采样的HIV-1的gag、pol和env基因。我们在分子钟模型下通过最大似然法估计了时间尺度系统发育树。将系统动力学模型应用于时间尺度树,以估计传播率、有效感染数、随时间变化的发病率以及输入到赫拉比萨的感染比例。我们还对合并时间分布有显著差异的时间尺度系统发育树进行了划分。系统动力学分析显示,1980年至1990年期间流行增长率呈现相似趋势。基于模型的发病率和有效感染数估计在各基因间是一致的。使用gag估计的参数通常小于使用pol和env估计的参数。在估计2015年赫拉比萨新感染中来自移民或外部来源传播的比例时,我们的后验中位数估计对于gag为85%(95%可信区间(CI)=78%-92%),对于pol为62%(CI = 40%-78%),对于env为77%(CI = 58%-90%)。按基因对系统发育划分进行的分析表明,大多数密切的全球参考序列聚集在单个划分内。这表明存在局部不断演变的疫情或人群中潜在的未测量的异质性。我们使用系统动力学模型估计了gag、pol和env基因一致的流行动态趋势。新感染很可能不归因于赫拉比萨内部的内源性传播,这表明南非农村社区之间的联系紧密。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68f4/10276198/e0fb1fea75bb/wellcomeopenres-7-19822-g0000.jpg

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