Wilkinson Eduan, Engelbrecht Susan, de Oliveira Tulio
Division of Medical Virology, Department of Pathology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, Western Cape Province, South Africa; Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Somkhele, KwaZulu-Natal, South Africa.
Division of Medical Virology, Department of Pathology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, Western Cape Province, South Africa; National Health Laboratory Services, Tygerberg Hospital, Cape Town, Western Cape Province, South Africa.
PLoS One. 2014 Oct 30;9(10):e109296. doi: 10.1371/journal.pone.0109296. eCollection 2014.
Despite recent breakthroughs in the fight against the HIV/AIDS epidemic within South Africa, the transmission of the virus continues at alarmingly high rates. It is possible, with the use of phylogenetic methods, to uncover transmission events of HIV amongst local communities in order to identify factors that may contribute to the sustained transmission of the virus. The aim of this study was to uncover transmission events of HIV amongst the infected population of Cape Town.
We analysed gag p24 and RT-pol sequences which were generated from samples spanning over 21-years with advanced phylogenetic techniques. We identified two transmission clusters over a 21-year period amongst randomly sampled patients from Cape Town and the surrounding areas. We also estimated the origin of each of the identified transmission clusters with the oldest cluster dating back, on average, 30 years and the youngest dating back roughly 20 years.
These transmission clusters represent the first identified transmission events among the heterosexual population in Cape Town. By increasing the number of randomly sampled specimens within a dataset over time, it is possible to start to uncover transmission events of HIV amongst local communities in generalized epidemics. This information can be used to produce targeted interventions to decrease transmission of HIV in Africa.
尽管南非在抗击艾滋病毒/艾滋病疫情方面最近取得了突破,但病毒传播仍以惊人的高速度持续。利用系统发育方法有可能揭示艾滋病毒在当地社区中的传播事件,以便确定可能导致病毒持续传播的因素。本研究的目的是揭示开普敦感染人群中的艾滋病毒传播事件。
我们使用先进的系统发育技术分析了从跨越21年的样本中生成的gag p24和RT-pol序列。我们在来自开普敦及其周边地区的随机抽样患者中,在21年期间识别出两个传播集群。我们还估计了每个已识别传播集群的起源,最古老的集群平均可追溯到30年前,最年轻的集群大约可追溯到20年前。
这些传播集群代表了开普敦异性恋人群中首次识别出的传播事件。随着时间的推移,通过增加数据集中随机抽样标本的数量,有可能开始揭示一般流行疫情中当地社区的艾滋病毒传播事件。这些信息可用于制定有针对性的干预措施,以减少非洲的艾滋病毒传播。