Juga Adelino J C, Hens Niel, Osman Nafissa, Aerts Marc
Department of Mathematics and Informatics, Faculty of Sciences, Eduardo Mondlane University, Maputo, Mozambique.
I-BioStat, Hasselt University, Diepenbeek, Belgium.
PLoS One. 2017 Mar 2;12(3):e0172959. doi: 10.1371/journal.pone.0172959. eCollection 2017.
Whereas the number of people newly infected by HIV is continuing to decline globally, the epidemic continues to expand in many parts of the world. As the HIV/AIDS epidemic has matured in many countries, it is believed that the proportion of new infections occurring within couples has risen. Across countries, including Mozambique, a sizeable proportion of couples with HIV infection are discordant. A serodiscordant couple is a couple in which one partner has tested positive for HIV and the other has not. To describe the HIV serodiscordance among couples, a variety of association measures can be used. In this paper, we propose the serodiscordance measure (SDM) as a new alternative measure. Focus is on the specification of flexible marginal and random effects models for multivariate correlated binary data together with a full-likelihood estimation method, to adequately and directly describe the measure of interest. Fitting joint models allows examining the effects of different risk factors and other covariates on the probability to be HIV positive for each member within a couple, and estimating common effects for both probabilities more efficiently, while accounting for the association between their infection status. Moreover, the interpretation of the proposed association parameter SDM is more direct and relevant and effects of covariates can be studied as well. Results show that the HIV prevalence for the province where a couple was located as well as the union number for the woman within a couple are factors associated with HIV serodiscordance. These findings are important for the Mozambican public health policy makers to design national prevention plans, which include policies to stimulate regular HIV testing for couples as well as adolescents and young adults, prior to getting married or living together as a couple.
尽管全球新感染艾滋病毒的人数持续下降，但这一流行病在世界许多地区仍在蔓延。随着艾滋病毒/艾滋病疫情在许多国家逐渐成熟，据信夫妻间新感染的比例有所上升。在包括莫桑比克在内的各个国家，相当一部分感染艾滋病毒的夫妻一方呈阳性，另一方呈阴性。血清学不一致的夫妻是指一方艾滋病毒检测呈阳性而另一方检测呈阴性的夫妻。为了描述夫妻间的艾滋病毒血清学不一致情况，可以使用多种关联度量方法。在本文中，我们提出血清学不一致度量（SDM）作为一种新的替代度量方法。重点在于为多变量相关二元数据指定灵活的边际和随机效应模型以及全似然估计方法，以充分且直接地描述感兴趣的度量。拟合联合模型能够检验不同风险因素和其他协变量对夫妻中每个成员艾滋病毒呈阳性概率的影响，并更有效地估计两个概率的共同效应，同时考虑到他们感染状况之间的关联。此外，所提出的关联参数SDM的解释更直接且相关，并且也可以研究协变量的影响。结果表明，夫妻所在省份的艾滋病毒流行率以及夫妻中女性的结婚次数是与艾滋病毒血清学不一致相关的因素。这些发现对于莫桑比克公共卫生政策制定者设计国家预防计划很重要，这些计划包括鼓励夫妻以及青少年和年轻人在结婚或同居前定期进行艾滋病毒检测的政策。
