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.

项目概要 为了实现重要的健康里程碑（例如国家艾滋病毒/艾滋病战略1），公共卫生系统需要 预测一个地区内艾滋病毒流行病学的方法。佛罗里达州迈阿密新增确诊病例意外激增 如果公共卫生官员能够预测这些变化并进行干预，那么印第安纳州奥斯汀市的情况很可能会被避免。 预期。然而，建模方法并没有被充分利用作为帮助公共卫生的主流工具 决定，2 由于障碍，包括(a) 无法提供考虑到 HIV 传播动态预测因素之间的时空关系，(b) 缺乏强大的大 社交媒体数据，用于衡量人口标准以及有关艾滋病毒检测和预防的信息传播 服务，(c) 缺乏整合分散但相关的数据来源来预测艾滋病毒流行病学，(d) 缺乏 整合结果的可视化工具，以及（e）缺乏模型来衡量新的影响 干预措施（例如艾滋病毒疫苗）或当前干预措施的变化。在此应用中，我们建议 如果成功的话，公共卫生官员和科学界将能够制定此类完善的方法 预测，从而规划 PrEP（暴露前预防）等干预措施。该项目将依托 现有但分散的区域流行病学、社会结构、社交媒体和干预来源 数据来生成模型和 Cyber​​-GIS-HIV，这是公共卫生官员和研究人员可以使用的工具。 该工具将分析数据并在综合输出中产生结果，识别脆弱区域，以及 预测未来的脆弱性以及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、美国人口普查数据、 美国社区调查、美国男性互联网调查、传输网络数据集、社交媒体 数据和新干预措施的效果大小来得出预测。我们还将开发新方法 社交媒体分析和比较时空建模技术。系统将提供 针对邮政编码、县和地区的服务分配建议，准备推出服务 在各个领域之间平等地进行，或者以能够为整个州带来最大改善的领域为目标。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、 以及该项目的计算基础设施。团队（伊利诺伊州：Albarracin、Chan、Li、Sundaram 和 Wang； 奥尔巴尼：Holtgrave）开发了尖端的大数据模型来预测艾滋病毒和流感，以及原始的 时空分析和现有最先进的 Cyber​​GIS 工具。 Do 博士在埃默里大学的部门任职 在疾病预防控制中心的艾滋病毒监测流行病学工作了二十年，现在是一名教员。此外，健康 部门人员将在项目的最后一年参与 Cyber​​GIS-HIV 的设计和测试 项目，如果方法通过了一组预先设定的通过/不通过标准。