Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Rakai Health Sciences Program, Baltimore, USA.
Curr Opin HIV AIDS. 2019 May;14(3):173-180. doi: 10.1097/COH.0000000000000542.
The HIV epidemic in sub-Saharan Africa is far from being under control and the ambitious UNAIDS targets are unlikely to be met by 2020 as declines in per-capita incidence being largely offset by demographic trends. There is an increasing number of proven and specific HIV prevention tools, but little consensus on how best to deploy them.
Traditionally, phylogenetics has been used in HIV research to reconstruct the history of the epidemic and date zoonotic infections, whereas more recent publications focus on HIV diversity and drug resistance. However, it is also the most powerful method of source attribution available for the study of HIV transmission. The PANGEA (Phylogenetics And Networks for Generalized Epidemics in Africa) consortium has generated over 18 000 NGS HIV sequences from five countries in sub-Saharan Africa. Using phylogenetic methods, we will identify characteristics of individuals or groups, which are most likely to be at risk of infection or at risk of infecting others.
Combining phylogenetics, phylodynamics and epidemiology will allow PANGEA to highlight where prevention efforts should be focussed to reduce the HIV epidemic most effectively. To maximise the public health benefit of the data, PANGEA offers accreditation to external researchers, allowing them to access the data and join the consortium. We also welcome submissions of other HIV sequences from sub-Saharan Africa to the database.
目的综述： 撒哈拉以南非洲地区的 HIV 疫情仍远未得到控制，而且到 2020 年，艾滋病规划署的宏伟目标也不太可能实现，因为人均发病率的下降在很大程度上被人口趋势所抵消。虽然已经有越来越多经过验证的、特定的 HIV 预防工具，但对于如何最好地部署这些工具，几乎没有达成共识。
最新发现： 传统上，系统发生学在 HIV 研究中用于重建疫情的历史和确定人畜共患病感染的时间，而最近的出版物则侧重于 HIV 的多样性和耐药性。然而，它也是研究 HIV 传播时可用于源归因的最强大的方法。泛非基因进化和一般传染病网络（PANGEA）联盟已经从撒哈拉以南非洲的五个国家生成了超过 18000 个 NGS HIV 序列。通过使用系统发生学方法，我们将确定个人或群体的特征，这些特征最有可能面临感染风险或有感染他人的风险。
总结： 将系统发生学、系统进化动力学和流行病学相结合，将使 PANGEA 能够突出指出应将预防工作重点放在哪些地方，以最有效地减少 HIV 疫情。为了使数据对公众健康的最大益处，PANGEA 向外部研究人员提供认证，允许他们访问数据并加入该联盟。我们也欢迎撒哈拉以南非洲地区的其他 HIV 序列提交到数据库中。
