Statistical Issues in AIDS Research

在发现艾滋病毒30年后，艾滋病仍在流行，估计有3700万人 目前全球感染人数和每年新增感染人数为180万人。研究以预防 治疗艾滋病毒感染变得越来越复杂，分析挑战已经成为 相应地也很复杂。此应用程序旨在解决及时而重要的统计问题 在艾滋病毒/艾滋病研究方面。特别是，将开发新的统计方法，用于(I)数据分析 来自艾滋病毒临床试验，包括实施试验的方法、暴露前预防试验 (PREP)和疫苗研究(2)必要的监测研究的最佳设计和分析 确定艾滋病毒流行的特征，以及(Iii)分析艾滋病毒治疗中使用的关键实验室化验数据 和疫苗研究。 首先，提出了应对当前艾滋病毒预防的关键挑战的统计方法， 治疗和实施试验。这些方法包括因果建模和无模型/模型-模型方法。 不可知的方法，消除了复杂的建模假设的需要。建议的方法 对艾滋病毒/艾滋病的临床和实施研究以及其他领域具有广泛的适用性。 第二，提出了统计方法，以帮助描述艾滋病毒的关键特征 流行病。其中包括能够提供精细尺度的时空建模的新方法 艾滋病毒流行率、发病率、抑制率等地图(带有不确定性信息) 措施，以及结合(随机)计数过程方法的新方法 用(确定性)微分方程分析交互和动态系统的生存分析， 比如社交性网络。这些方法有可能为 优化防治资源配置。最后，拟议的研究将 研究用于治疗和疫苗的关键实验室化验分析的统计方法 研究，包括用于量化潜伏的艾滋病毒大小的病毒载量增长定量分析 以及疫苗研究中使用的基于细胞内染色的流式细胞仪分析 量化细胞刺激后细胞因子的产生和积累。 拟议的研究反映了调查人员广泛和持续地参与 艾滋病毒/艾滋病研究领域。所解决的统计问题是由KEY中的应用程序驱动的 艾滋病毒研究领域。概述的解决方案具有很高的创新性，直接适用于当前 疫苗开发、艾滋病毒预防试验、实施研究等方面的科学研究 艾滋病毒/艾滋病相关研究。

Thirty years after identification of HIV, the AIDS epidemic continues with an estimated 37 million individuals currently infected worldwide and 1.8 million new infections each year. Research to prevent and treat HIV infection has grown increasingly sophisticated and the analytic challenges have become correspondingly complex. This application is intended to address timely and important statistical issues in HIV/AIDS research. In particular, novel statistical methods will be developed for (i) analysis of data from HIV clinical trials, including methods for implementation trials, trials of pre-exposure prophylaxis (PrEP), and vaccine studies (ii) optimal design and analysis of surveillance studies that are necessary to characterize the HIV epidemic, and (iii) analysis of data from key laboratory assays used in HIV cure and vaccine research. First, statistical methods are proposed that address key challenges in current HIV prevention, treatment and implementation trials. The approaches include causal modeling and model-free/model- agnostic methods that remove the need for complex modeling assumptions. The proposed methods have broad applicability to clinical and implementation studies of HIV/AIDS as well as other fields. Second, statistical methods are proposed to help characterize and describe key features of the HIV epidemic. These include new approaches to spatial-temporal modeling that can provide fine-scale maps (with uncertainty information) of HIV prevalence, incidence, percent suppressed, and other measures, as well as a novel approach to combining the (stochastic) counting process approach to survival analysis with (deterministic) differential equations to analyze interactive and dynamic systems, such as socio-sexual networks. These methods have the potential to provide critical guidance for optimizing the distribution of treatment and prevention resources. Finally, the proposed research will investigate statistical methods for the analysis of key laboratory assays used in cure and vaccine studies, including the quantitative viral load outgrowth assay used to quantify the size of the latent HIV reservoir, and the intra-cellular staining flow-cytometry-based assay used in vaccine research to quantify cytokine production and accumulation after cell stimulation. The proposed research reflects the extensive and ongoing involvement of the investigators in the field of HIV/AIDS research. The statistical problems addressed are motivated by applications in key areas of HIV research. The solutions outlined are highly innovative and directly applicable to current scientific research in vaccine development, HIV prevention trials, implementation research, and other HIV/AIDS related studies.