Big Data Digital Outreach and Epidemiology Methods for HIV Care among Communities of Color

有色人种社区艾滋病毒护理的大数据数字推广和流行病学方法

• 批准号: 10709902
• 负责人: Sean Young
• 金额: $ 52.83万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-24 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10709902
• 关键词: Address; Adherence; Adopted; Advertising; Affect; African American; Area; Big Data; Black Populations; Black race; COVID-19 pandemic; COVID-19 risk; Caring; Case Study; Clinic; Cohort Studies; Color; Communication; Communities; County; Crime; Data; Data Sources; Devices; District of Columbia; Dropout; Enrollment; Epidemic; Epidemiologic Methods; Epidemiology; Ethics; European Union; Facebook; Future; Geography; HIV; HIV/AIDS; Health; Health Insurance Portability and Accountability Act; Individual; Intervention; Interview; Knowledge; Latinx; Latinx population; Laws; Learning; Machine Learning; Maps; Marketing; Mediator; Mental Health; Methods; Modeling; Movement; Neighborhoods; Oranges; Outcome Measure; Participant; Pattern; Persons; Policy Maker; Prevention; Privacy; Process; Public Health; Research; Research Personnel; Risk; Sampling; Services; Structure; Surveys; Target Populations; Technology; Time; United States; Visualization; aged; barrier to care; care outcomes; cohort; data de-identification; data quality; data reduction; design; digital; digital communication; experience; follow-up; handheld mobile device; high risk; implementation science; improved; innovation; insight; mobility aid; novel; outreach; participant enrollment; people of color; public-private partnership; recruit; scale up; socioeconomics; stay-at-home order; success; tool

Abstract One of the most significant problems in the field of HIV deals with addressing the low rates of HIV care among individuals living with HIV/AIDS, especially among Black/African American and Latinx communities. This application seeks to study a novel way to address that problem by adopting and applying a cutting-edge “big data outreach” approach being used to increase consumer engagement by top technologies companies. This approach has recently been replacing other digital outreach methods largely for privacy reasons-- to conform to stringent European Union privacy laws-- as it involves de-identified data. The digital outreach method being proposed is already being applied in health (but not yet HIV) settings. During the COVID-19 pandemic, our team and others (including the CDC) studied and found success applying these methods for targeted digital recruitment and outreach to those at high-risk for COVID-19. As a result of the COVID-19 pandemic and its effect on use of digital/remote tools, these approaches will soon be applied to HIV to assist in targeting and engaging hard-to reach individuals in HIV research and care. Importantly, the proposed methods allow access to large-scale passively-collected, opt-in, community and mobility (GPS pings) data, which have been shown to add rich and granular data to improve health surveillance and interventions. This application seeks to use these novel digital outreach methods to identify and enroll individuals living with HIV/AIDS from communities of color who are at high-risk for being out of care, and analyze their mobility and community data to identify the key geographic contexts that impact HIV care engagement. We are conducting this effort for, and in partnership with, 2 Ending the HIV Epidemic (EHE) jurisdictions (Washington D.C. and Orange County health departments) and key participant stakeholders to gain their insights on needs, implementation (including ethical concerns), and potential future scale-up of this approach to improve surveillance and intervention efforts. Specifically, we seek to 1) Identify individuals of color living with HIV/AIDS within EHE regions who are at high-risk for being out of care, 2) Using GPS mobility, community (e.g., local crime), and HIV care data, identify the key geographic contexts that impact HIV care engagement, and 3) In partnership with the Washington D.C. and Orange County health departments, explore a case study of the ongoing barriers and facilitators of this approach at the individual, interpersonal, and structural levels. This 1-year cohort study will be focused on identifying people living within an EHE region who have been hard-to-reach for HIV care in order to converge with EHE outcome measures. To our knowledge, this is the first study to apply these novel “big data outreach” methods to HIV, will enroll the largest cohort to date with GPS mobility, community, and other HIV care contextual data, and the first HIV study to passively collect mobility data, which helps to increase data quality and reduce dropout rates compared to previous studies.

摘要