Development and validation of regional models of HIV vulnerabilities and solutions

艾滋病毒脆弱性和解决方案的区域模型的开发和验证

• 批准号: 9982770
• 负责人: DOLORES ALBARRACIN
• 金额: $ 60.13万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-24 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9982770
• 关键词: AIDS prevention; AIDS/HIV problem; American; Area; Big Data; Censuses; Centers for Disease Control and Prevention (U.S.); Code; Color; Communities; Community Surveys; Computer software; County; Data; Data Set; Data Sources; Development; Diagnosis; Diffusion; Disease Outbreaks; Encapsulated; Epidemiologic Monitoring; Epidemiology; Faculty; Future; Gays; Goals; HIV; HIV Infections; HIV diagnosis; HIV risk; HIV vaccine; HIV/STD; Health; Health Personnel; Health system; Human Resources; Human immunodeficiency virus test; Illinois; Incidence; Indiana; Infection; Infrastructure; Injections; Internet; Intervention; Letters; Mainstreaming; Maps; Media Intervention; Methamphetamine; Methods; Modeling; Opioid; Output; Pattern; Policies; Population; Prevalence; Prevention Research; Prophylactic treatment; Public Health; Recommendation; Reporting; Research Personnel; Risk Behaviors; Scientist; Services; Social Sciences; Source; Surveys; System; Techniques; Testing; Time; Training; United States; United States Public Health Service; Universities; Update; Validation; Viral; Visualization software; West Virginia; austin; computer network; data modeling; design; digital; evidence based guidelines; experience; flu; health record; innovation; member; men; models and simulation; pre-exposure prophylaxis; prevention service; response; rural counties; service utilization; social; social media; social norm; social structure; spatiotemporal; testing services; tool; transmission process; user-friendly

PROJECT SUMMARY To achieve critical health milestones (e.g., National HIV/AIDS Strategy1), the public health system needs methods to predict HIV epidemiology within a region. An unexpected surge of new diagnoses in Miami, FL or Austin, IN, may well be avoided if public health officials are able to forecast these changes and to intervene in anticipation. However, modeling approaches are underutilized as mainstream tools to aid public health decisions,2 owing to barriers including (a) unavailability of user-friendly methods that consider the spatiotemporal relations among predictors of HIV transmission dynamics, (b) lack of inclusion of powerful big social media data to gauge population norms and diffusion of information about HIV testing and prevention services, (c) lack of integration of disperse yet relevant sources of data to predict HIV epidemiology, (d) lack of visualization tools for the results of that integration, and (e) lack of models to gauge impact of new interventions (e.g., an HIV vaccine), or changes in current interventions. In this application, we propose methods that, if successful, will allow public health officials and the scientific community to make such refined predictions and thereby to plan for interventions such as PrEP (PreExposure Prophylaxis). The project will rely on existing but disperse sources of regional epidemiological, socio-structural, social media, and intervention data to produce models and Cyber-GIS-HIV, a tool that can be used by public health officials and researchers. The tool will analyze data and produce results in an integrated output identifying vulnerable regions, and predicting future pockets of vulnerability and the effects of changes in intervention policy. We will integrate epidemiological and biomedical service data recorded by health departments, data from the US Census, the American Community Survey, the American Men Internet Survey, transmission network datasets, social media data, and effect sizes from new interventions to derive predictions. We will also develop new methods for social media analyses and compare spatio-temporal modeling techniques. The system will offer recommendations about service allocation for a zip code, a county, and a region, set to introduce services equally across areas, or to target the areas that would give the most improvement for the state as a whole. The University of Illinois, Emory University, and the University at Albany offer the ideal social science, public health, and computing infrastructure for this project. The team (Illinois: Albarracin, Chan, Li, Sundaram, and Wang; Albany: Holtgrave) has developed cutting-edge big-data models to predict HIV and flu, as well as original spatiotemporal analysis and existing state-of-the-art CyberGIS tools. Dr. Do at Emory served in the division of HIV surveillance epidemiology at CDC for two decades and is now a faculty member. In addition, health department personnel will be involved in designing and in testing CyberGIS-HIV during the last year of the project, if the methods pass a preestablished set of Go/No Go criteria.

项目摘要 为了实现关键的健康里程碑（例如，国家艾滋病毒/艾滋病战略1），公共卫生系统需要 预测区域内HIV流行病学的方法。迈阿密，佛罗里达州或 如果公共卫生官员能够预测这些变化并干预 预期。但是，建模方法被用作主流工具，以帮助公共卫生 决定，2由于障碍，包括（a）不可用的用户友好方法考虑 艾滋病毒传播动态预测指标之间的时空关系，（b）缺乏强大的大型 社交媒体数据衡量人口规范以及有关HIV测试和预防的信息的扩散 服务，（c）缺乏分散但相关数据来源的整合以预测艾滋病毒流行病学，（d）缺乏 可视化工具为该集成的结果，以及（e）缺乏模型来衡量新的影响 干预措施（例如，HIV疫苗）或当前干预措施的变化。在此应用程序中，我们建议 如果成功的话，将允许公共卫生官员和科学界做出如此精致的方法 预测，从而计划干预措施（例如预防预防）。该项目将依靠 关于区域流行病学，社会结构，社交媒体和干预的现有但分散的来源 数据生产模型和网络GIS-HIV，这是一种可以由公共卫生官员和研究人员使用的工具。 该工具将分析数据并在识别易受伤害区域的集成输出中产生结果，并且 预测未来的脆弱性和干预政策变化的影响。我们将整合 卫生部门记录的流行病学和生物医学服务数据，美国人口普查的数据， 美国社区调查，美国男子互联网调查，传输网络数据集，社交媒体 数据和效果大小从新的干预措施到得出预测。我们还将为 社交媒体分析和比较时空建模技术。该系统将提供 有关邮政编码，县和一个地区的服务分配的建议，旨在引入服务 同样，跨越地区，或针对将为整个国家提供最大进步的领域。这 伊利诺伊大学，埃默里大学和奥尔巴尼大学提供理想的社会科学，公共卫生， 和该项目的计算基础架构。团队（伊利诺伊州：Albarracin，Chan，Li，Sundaram和Wang； 奥尔巴尼：霍尔特格雷夫（Holtgrave））已经开发了尖端的大数据模型来预测艾滋病毒和流感以及原始 时空分析和现有的最新网络行为工具。 Do博士在埃默里（Emory）任职 CDC的HIV监测流行病学已有二十年了，现在是教职员工。此外，健康 部门人员将参与设计和测试网络HIV 项目，如果这些方法通过了一套已预先建立的GO/NO GO标准。