Modeling the Complex Dynamics between Behaviors and Environments Shaping HIV/STIs

描述（由申请人提供）：这个指导研究科学家发展奖（K 01）的目的是三重。这将使我能够：1）拓宽我对吸毒者和性工作者在新的文化和环境背景下的艾滋病毒社会流行病学的理解，2）学习传染病计算建模的新方法，3）促进我过渡到成为加州圣地亚哥大学的一名富有成效的NIH资助的独立研究员。培训目标将通过具体的研讨会和课程，动手研究项目，并与培训委员会组成的艾滋病毒传播网络，计算建模，地理信息系统和地理空间分析，艾滋病毒社会流行病学研究在美国/墨西哥边境地区的专家一对一辅导相结合。这项研究将通过对艾滋病毒/性传播感染传播的计算机建模进行多学科研究来完成，以构建，验证和校准反映个人行为和环境对艾滋病毒/性传播感染影响之间复杂相互依赖关系的计算机模拟模型。该项目将利用现有NIH/NIDA资助的R 01，DA 028692 -01（“墨西哥/美国边境女性性工作者（FSW）不断演变的艾滋病毒/性传播感染风险环境”，又名Proyecto Mapa de Salud，PI Kimberly Brouwer）的数据，以利用该项目所代表的基础设施和专业知识。美国/墨西哥边境正在经历一场迅速发展的艾滋病毒流行病，集中在吸毒者和FSW等高危人群中。计算建模已被常规用于疾病流行病学，医疗保健能力和紧急护理中的患者流量等领域，以捕获系统的复杂行为，但在与健康相关的行为和社会科学研究中采用的速度较慢。计算建模提供了独特的机会，通过检查个人在其环境中相互作用的循环关系，进而研究艾滋病毒/性传播感染风险的因果机制， 环境塑造风险相关行为。拟议的研究将使我能够应用新获得的计算建模技能，随着我们改变风险的背景，包括在行为，社会，物理和地理层面上测量的因素，开发一个强大的艾滋病毒/性病传播模拟。将利用从蒂华纳一个特别高风险人群中抽样的现有数据对这一模型进行验证和校准，在蒂华纳，从事性工作的妇女的艾滋病毒感染率为21%。这项研究的结果将提高对哪些环境决定因素影响艾滋病毒/性传播感染的人口水平的科学认识，并可能对用于决策和公共卫生干预措施的证据类型产生重大影响。此外，发展计算建模技能将使我成为药物滥用领域少数几个拥有此类技能的定量方法研究人员之一，也是加州大学圣地亚哥分校全球公共卫生部唯一的一个。

DESCRIPTION (provided by applicant): The purpose of this Mentored Research Scientist Development Award (K01) is threefold. This will allow me to: 1) broaden my understanding of the social epidemiology of HIV among drug users and sex workers in a new cultural and environmental context, 2) learn a new methodology in computational modeling of infectious diseases, and 3) facilitate my transition to becoming a productive NIH-funded independent Investigator at the University of California San Diego. The training aims will be accomplished through a combination of specific workshops and coursework, a hands-on research project, and one-on-one mentoring with a Training Committee comprised of experts in areas of HIV-transmission networks, computational modeling, GIS and geospatial analysis, and HIV social epidemiology research in the US/Mexico border regions. This research will be accomplished by conducting multidisciplinary studies on the computational modeling of HIV/STI transmission to construct, validate, and calibrate a computer simulation model reflecting the complex interdependences between individual behavior and environmental influence on HIV/STI. This project will leverage data from an existing NIH/NIDA-funded R01, DA028692-01 ("Evolving HIV/STI risk environments of female sex workers (FSWs) on the Mexico/US border" aka Proyecto Mapa de Salud, PI Kimberly Brouwer) in order to capitalize on the infrastructure and expertise represented by that project. The US/Mexico border is experiencing a burgeoning HIV epidemic, concentrated among high-risk groups such as drug users and FSWs. Computational modeling has been routinely used in areas such as disease epidemiology, health care capacity, and patient flows in emergency care to capture the complex behavior of system but have been slower to be adopted in health-related behavioral and social science research. Computational modeling offers the unique opportunity to address the casual mechanism of HIV/STI risk by examining cyclic relationship of individuals interacting within their environment and in turn their environment shaping risk-related behaviors. The proposed research will allow me to apply newly acquired skills in computational modeling to develop a robust simulation of HIV/STI transmission as we change the context of risks including factors measured at the behavioral, social, physical, and geographical level. This model will be validated and calibrated with extant data sampled from a particularly high-risk population in Tijuana where HIV prevalence among women participating in sex work is 21%. Findings from this research will enhance scientific understanding on which environmental determinants affect population-levels of HIV/STI transmission and could have major implications for the types of evidence that are used to make policy decision and public health interventions. Further, developing skills in computational modeling will uniquely position me as only one of a handful of quantitative methodological researchers in the field of drug abuse possessing such skills, and the only one in the Division of Global Public Health at the University of California, San Diego.