HIV - Emergence of Drug Resistance

描述(由申请人提供)：该申请是更新一个项目，重点是使用数学模型来了解和预测人类免疫缺陷病毒(HIV)治疗中抗逆转录病毒(ARV)耐药性的出现。随着资源匮乏地区抗逆转录病毒药物使用率的增加，可能会出现高水平的抗药性，并对全球公共卫生产生破坏性影响，破坏向数百万艾滋病毒感染者提供这种治疗的全球计划。我们提议的项目将扩展当前奖项的工作，该奖项显示了使用数学模型来了解美国艾滋病毒耐药毒株的时间动态以及在这种情况下预测耐药性大小的价值。在更新中，我们的工作将通过将数学建模与统计分析结合起来，对美国、欧洲和非洲的合作小组收集的数据集进行统计分析。我们将获得在这三大洲进行的大规模流行病学和治疗研究中有关耐药性和重要相关变量的数据。在资源匮乏的地区，如非洲，药物将受到限制，因此往往会供不应求。我们将利用运筹学(OR)技术研究在非洲分配抗逆转录病毒药物的问题。我们有三个具体目标。目的1：了解美国和欧洲艾滋病毒耐药毒株的出现，解释目前的情况并预测其演变。目的2：预测由于一线方案和预防性使用抗逆转录病毒药物而导致的耐药菌株在非洲的流行演变。目标3：评估在非洲分配稀缺的艾滋病毒卫生保健资源的后果。为了实现这一目标，我们将使用模型来评估获得治疗方面性别不平等的流行病学和伦理后果，评估治疗优先标准的流行病学和伦理影响，并确定确保可持续性的医疗资源分配战略。我们在更新中的研究将把传播建模、OR技术和统计分析联系起来；我们的分析将利用我们在美国、欧洲和非洲的合作者提供的非凡数据集。 与公共卫生相关：艾滋病毒耐药株的出现和控制现在是一个全球性问题。这一问题的流行病学很复杂，艾滋病毒疫情的未来也是未知的。我们的项目重点是使用数学模型来理解、解释和预测由美国、欧洲和非洲的艾滋病毒耐药毒株组成的复杂流行病的演变。抗逆转录病毒药物在非洲的推出才刚刚开始；然而，药物的需求远远超过了供应。我们将利用数学模型评估分配非洲稀缺的抗逆转录病毒药物的流行病学和伦理后果。我们的研究基于数学建模和数据分析。我们的分析将利用我们在美国、欧洲和非洲的合作者提供的非凡数据集。我们的结果将与卫生政策制定者直接相关。

DESCRIPTION (provided by applicant): This application is to renew a project focused on using mathematical models to understand and predict the emergence of drug resistance to antiretrovirals (ARVs) for the treatment of Human Immunodeficiency Virus (HIV). As the usage rate of ARVs in resource-poor regions is increasing, high levels of drug resistance potentially could emerge and have a devastating impact on public health worldwide, derailing global plans to provide this treatment to many millions of HIV-infected individuals. Our proposed projects will extend the work of the current award, which showed the value of using mathematical models to understand the temporal dynamics of drug-resistant strains of HIV in the United States (US), and for predicting the magnitude of resistance in this setting. In the renewal our work will be extended by combining mathematical modeling with statistical analysis of datasets collected by collaborating groups in the US, Europe and Africa. We will have access to data on drug resistance and important related variables from large scale epidemiological and treatment studies conducted in these three continents. In resource-poor settings, such as Africa, drugs will be limited and thus demand will often greatly exceed supply. We will investigate the problems of allocating ARVs in Africa by using operation research (OR) techniques. We have three Specific Aims. Aim 1: to understand the emergence, explain the present, and predict the evolution of, complex epidemics of drug-resistant strains of HIV in the US and Europe. Aim 2: to predict the evolution of epidemics of drug-resistant strains, as a result of first- line regimens and prophylactic use of ARVs, in Africa. Aim 3: to evaluate the consequences of allocation of scarce HIV healthcare resources in Africa. To achieve this aim we will use models to evaluate the epidemiological and ethical consequences of gender-inequities in access to treatment, assess the epidemiological and ethical impact of treatment priority criteria, and determine healthcare resource allocation strategies that ensure sustainability. Our studies in the renewal will link transmission modeling, OR techniques and statistical analyses; our analyses will take advantage of the extraordinary data sets provided by our collaborators in the US, Europe and Africa. PUBLIC HEALTH RELEVANCE: The emergence and control of drug-resistant strains of HIV is now a global problem. The epidemiology of this problem is complex, and the future of the HIV epidemic is unknown. Our projects focus on using mathematical models to understand, explain, and predict, the evolution of complex epidemics composed of drug-resistant strains of HIV in the US, Europe and Africa. The rollout of antiretrovirals in Africa is just beginning; however demand for drugs greatly exceeds supply. We will, by using mathematical models, evaluate the epidemiological and ethical consequences of allocation of the scarce supply of antiretrovirals in Africa. Our studies are based upon both mathematical modeling and data analyses. Our analyses will take advantage of the extraordinary data sets provided by our collaborators in the US, Europe and Africa. Our results will have direct relevance for health policy makers.