Kiwuwa-Muyingo Sylvia, Nazziwa Jamirah, Ssemwanga Deogratius, Ilmonen Pauliina, Njai Harr, Ndembi Nicaise, Parry Chris, Kitandwe Paul Kato, Gershim Asiki, Mpendo Juliet, Neilsen Leslie, Seeley Janet, Seppälä Heikki, Lyagoba Fred, Kamali Anatoli, Kaleebu Pontiano
Medical Research Council/Uganda Virus Research Institute, Research Unit on AIDS, Entebbe, Uganda.
Aalto University, School of Science, Department of Mathematics and Systems Analysis, Espoo, Finland.
PLoS One. 2017 Oct 12;12(10):e0185818. doi: 10.1371/journal.pone.0185818. eCollection 2017.
Fishing communities around Lake Victoria in sub-Saharan Africa have been characterised as a population at high risk of HIV-infection.
Using data from a cohort of HIV-positive individuals aged 13-49 years, enrolled from 5 fishing communities on Lake Victoria between 2009-2011, we sought to identify factors contributing to the epidemic and to understand the underlying structure of HIV transmission networks. Clinical and socio-demographic data were combined with HIV-1 phylogenetic analyses. HIV-1 gag-p24 and env-gp-41 sub-genomic fragments were amplified and sequenced from 283 HIV-1-infected participants. Phylogenetic clusters with ≥2 highly related sequences were defined as transmission clusters. Logistic regression models were used to determine factors associated with clustering.
Altogether, 24% (n = 67/283) of HIV positive individuals with sequences fell within 34 phylogenetically distinct clusters in at least one gene region (either gag or env). Of these, 83% occurred either within households or within community; 8/34 (24%) occurred within household partnerships, and 20/34 (59%) within community. 7/12 couples (58%) within households clustered together. Individuals in clusters with potential recent transmission (11/34) were more likely to be younger 71% (15/21) versus 46% (21/46) in un-clustered individuals and had recently become resident in the community 67% (14/21) vs 48% (22/46). Four of 11 (36%) potential transmission clusters included incident-incident transmissions. Independently, clustering was less likely in HIV subtype D (adjusted Odds Ratio, aOR = 0.51 [95% CI 0.26-1.00]) than A and more likely in those living with an HIV-infected individual in the household (aOR = 6.30 [95% CI 3.40-11.68]).
A large proportion of HIV sexual transmissions occur within house-holds and within communities even in this key mobile population. The findings suggest localized HIV transmissions and hence a potential benefit for the test and treat approach even at a community level, coupled with intensified HIV counselling to identify early infections.
撒哈拉以南非洲维多利亚湖周边的渔业社区被视为艾滋病毒感染的高危人群。
利用2009年至2011年间从维多利亚湖5个渔业社区招募的13至49岁艾滋病毒阳性个体队列的数据，我们试图确定导致该流行病的因素，并了解艾滋病毒传播网络的潜在结构。临床和社会人口统计学数据与艾滋病毒-1系统发育分析相结合。从283名感染艾滋病毒-1的参与者中扩增并测序了艾滋病毒-1 gag-p24和env-gp-41亚基因组片段。具有≥2个高度相关序列的系统发育簇被定义为传播簇。使用逻辑回归模型确定与聚类相关的因素。
总共有24%（n = 67/283）的艾滋病毒阳性个体的序列在至少一个基因区域（gag或env）内属于34个系统发育上不同的簇。其中，83%发生在家庭或社区内；8/34（24%）发生在家庭伴侣关系内，20/34（59%）发生在社区内。家庭中的7/12对夫妇（58%）聚集在一起。有近期潜在传播的簇中的个体（11/34）更有可能较年轻，71%（15/21），而非聚集个体中的比例为46%（21/46），并且最近才在社区定居，比例分别为67%（14/21）和48%（22/46）。11个潜在传播簇中有4个（36%）包括新发-新发传播。单独来看，艾滋病毒D亚型个体聚类的可能性较小（调整后的优势比，aOR = 0.51 [95%置信区间0.26 - 1.00]），低于A亚型，而与家庭中感染艾滋病毒的个体共同生活的个体聚类可能性更大（aOR = 6.30 [95%置信区间3.40 - 11.68]）。
即使在这个关键的流动人群中，很大一部分艾滋病毒性传播也发生在家庭和社区内。研究结果表明存在局部艾滋病毒传播，因此即使在社区层面，检测和治疗方法也可能有益，同时加强艾滋病毒咨询以识别早期感染。
