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: 10447508
• 负责人: DOLORES ALBARRACIN
• 金额: $ 58.72万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 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/10447508
• 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 预测一个地区内艾滋病流行病学的方法。佛罗里达州迈阿密新确诊病例意外激增， 如果公共卫生官员能够预测这些变化并进行干预， 期待然而，建模方法作为主流工具，以帮助公共卫生利用不足 由于各种障碍，包括（a）没有方便用户的方法， 艾滋病毒传播动力学预测因素之间的时空关系，（B）缺乏强有力的大规模 社交媒体数据，以衡量人口规范和传播有关艾滋病毒检测和预防的信息 （c）没有整合分散但相关的数据来源，以预测艾滋病毒流行病学，（d）缺乏 （e）缺乏模型来衡量新技术的影响， 干预（例如，艾滋病毒疫苗），或改变目前的干预措施。在本申请中，我们提出 这些方法如果成功，将使公共卫生官员和科学界能够改进这种方法， 预测，从而计划干预措施，如PrEP（暴露前预防）。该项目将依靠 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 数据生成模型和Cyber-GIS-HIV，这是一个可供公共卫生官员和研究人员使用的工具。 该工具将分析数据，并在确定脆弱地区的综合产出中产生结果， 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，以得出预测。我们还将开发新的方法， 社交媒体分析和比较时空建模技术。该系统将提供 关于邮政编码、县和地区的服务分配的建议，设置为引入服务 平等地在各个领域，或针对那些将为整个国家带来最大改善的领域。的 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、 和计算基础设施。球队（伊利诺斯州：阿尔瓦拉辛，陈，李，孙达拉姆，王; 奥尔巴尼：霍尔特格雷夫）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CyberGIS工具。埃默里大学的杜博士曾在 艾滋病毒监测流行病学在疾病预防控制中心二十年，现在是一名教员。此外，健康 国防部人员将参与设计和测试网络地理信息系统-艾滋病毒在去年的 项目，如果方法通过了预先建立的Go/No Go标准。