Examining Social Ecological and Network Factors to Assess Epidemiological Risk in a Large National Cohort of Cisgender Women

检查社会生态和网络因素以评估全国大型顺性别女性群体的流行病学风险

• 批准号: 10686266
• 负责人: Amy Kristen Johnson
• 金额: $ 305.04万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-18 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10686266
• 关键词: AIDS prevention; Advocate; Alcohol consumption; Algorithms; Anxiety; Behavior; Behavioral; Big Data; Biological Markers; Black race; Centers for Disease Control and Prevention (U.S.); Characteristics; Cohort Analysis; Communities; Contraceptive Agents; Crime; Data; Data Sources; Databases; Development; Diagnosis; Discrimination; Disease Surveillance; Domestic Violence; Electronics; Eligibility Determination; Epidemiology; Ethnic Origin; Exposure to; Focus Groups; Frequencies; Funding; Gender; Geographic Locations; Geography; HIV; HIV Infections; HIV Seronegativity; HIV Seropositivity; HIV diagnosis; HIV risk; Heterosexuals; Hispanic; Homelessness; Incidence; Income; Individual; Individual Differences; Inequality; Intervention; Interview; Knowledge; Latinx; Literature; Longitudinal cohort study; Measures; Mediating; Mental Depression; Methods; Motivation; Neighborhoods; Participant; Pathway Analysis; Policies; Population; Poverty; Predictive Value; Prevalence; Prevention; Prevention approach; Prevention strategy; Principal Investigator; Public Health; Public Policy; Race; Research; Research Design; Risk; Risk Factors; Sampling; Science; Self Efficacy; Sexual Partners; Sexually Transmitted Diseases; Social Network; Social support; Technology; United States; United States National Institutes of Health; Woman; abortion; cis-female; cohort; data integration; digital; epidemiologic data; epidemiology study; ethnic diversity; experience; flexibility; health care availability; health care service; high risk; improved; infection rate; injection drug use; innovation; intimate partner violence; knowledgebase; male; men who have sex with men; multilevel analysis; open source; payment; peer; pre-exposure prophylaxis; racial diversity; recruit; response; seroconversion; sexual violence; social; social health determinants; social media; social stigma; substance use; surveillance data; transmission process; uptake; women of color; AIDS prevention; Advocate; Alcohol consumption; Algorithms; Anxiety; Behavior; Behavioral; Big Data; Biological Markers; Black race; Centers for Disease Control and Prevention (U.S.); Characteristics; Cohort Analysis; Communities; Contraceptive Agents; Crime; Data; Data Sources; Databases; Development; Diagnosis; Discrimination; Disease Surveillance; Domestic Violence; Electronics; Eligibility Determination; Epidemiology; Ethnic Origin; Exposure to; Focus Groups; Frequencies; Funding; Gender; Geographic Locations; Geography; HIV; HIV Infections; HIV Seronegativity; HIV Seropositivity; HIV diagnosis; HIV risk; Heterosexuals; Hispanic; Homelessness; Incidence; Income; Individual; Individual Differences; Inequality; Intervention; Interview; Knowledge; Latinx; Literature; Longitudinal cohort study; Measures; Mediating; Mental Depression; Methods; Motivation; Neighborhoods; Participant; Pathway Analysis; Policies; Population; Poverty; Predictive Value; Prevalence; Prevention; Prevention approach; Prevention strategy; Principal Investigator; Public Health; Public Policy; Race; Research; Research Design; Risk; Risk Factors; Sampling; Science; Self Efficacy; Sexual Partners; Sexually Transmitted Diseases; Social Network; Social support; Technology; United States; United States National Institutes of Health; Woman; abortion; cis-female; cohort; data integration; digital; epidemiologic data; epidemiology study; ethnic diversity; experience; flexibility; health care availability; health care service; high risk; improved; infection rate; injection drug use; innovation; intimate partner violence; knowledgebase; male; men who have sex with men; multilevel analysis; open source; payment; peer; pre-exposure prophylaxis; racial diversity; recruit; response; seroconversion; sexual violence; social; social health determinants; social media; social stigma; substance use; surveillance data; transmission process; uptake; women of color

PROJECT SUMMARY While HIV prevention strategies have improved and HIV incidence rates continue to decrease in the United States (US), a critical need remains to strengthen and advance prevention science where declines appear to have stalled, particularly among cisgender women of color. The most recent surveillance data from the Centers for Disease Control and Prevention demonstrate that as of 2019, about 7,000 of all new HIV diagnoses were identified among cisgender women (hereafter simply referred to as “women”). Traditional demographic and behavioral risk factors are insufficient to identify women who are vulnerable to HIV infection. Recent research on the use of risk algorithms to determine pre-exposure prophylaxis (PrEP) eligibility demonstrated poor predictive power for women in contrast to good predictive value among men who have sex with men. Identifying women who are vulnerable to HIV infection is crucial for the development and deployment of tailored prevention approaches. While the mode of HIV acquisition for women is well known, with heterosexual contact (85%) identified as the most frequent mode of HIV transmission among women, followed by 15% due to injection drug use, less is known about the social-ecological factors (e.g., community, network, geospatial, and policy factors) associated with HIV seroconversion. Broadly, several factors beyond individual behavior have been associated with increased risk for HIV acquisition among women in the US such as gender inequality, income, exposure to domestic and sexual violence, homelessness, and sex partner’s characteristics. Nonetheless, identifying the combination of characteristics that predict seroconversion among women and establish them as candidates for PrEP has been challenging. To overcome this gap and in response to RFA-AI-21-058, we propose to harness innovative digital methods to establish a knowledgebase for women living in the US who are behaviorally vulnerable to HIV. The knowledgebase will consist of a national cohort of 1,800 women from whom we will collect HIV and sexually transmitted infections (STIs) incidence data and social and sexual network data, paired with open-source big data to contextualize HIV risk among women vulnerable to HIV infection. Our study team has extensive experience in using digital approaches to recruit study participants (through electronic methods and geospatial analytics). Capitalizing on our expertise, we will use the developed knowledgebase to identify theoretically-driven correlates of HIV seroconversion, STI incidence, and predictors of PrEP uptake. Findings will increase our understanding of women’s vulnerabilities to HIV infection, enhance identification of PrEP eligibility, and inform interventions to decrease the incidence of HIV and STIs among women living in the US.

项目摘要 虽然艾滋病毒预防策略有所改善，而联合的艾滋病毒事件率继续下降 国家（美国），仍然需要加强和提高预防科学的关键需求 已经停滞不前，尤其是在有色女性中。中心的最新监视数据 对于疾病控制和预防的证明，截至2019年，所有新的HIV诊断中约有7,000个是 在cisgender妇女中被确定（以下简称为“妇女”）。传统的人群和 行为风险因素不足以识别容易受到艾滋病毒感染的女性。最近的研究 关于使用风险算法来确定暴露前预防（PREP）资格证明很差 与男性发生性关系的良好预测价值相比，女性的预测能力。 确定容易感染艾滋病毒的妇女对于发展和部署至关重要 量身定制的预防方法。虽然众所周知，女性艾滋病毒获取模式是异性恋的 接触（85％）被确定为女性最常见的艾滋病毒传播模式，其次是15％ 注射药物的使用，对社会生态因素的了解少（例如，社区，网络，地理空间， 和政策因素）与HIV血清转化相关。广泛地，超出个人行为的几个因素 与性别等美国妇女中艾滋病毒收购风险的增加有关 不平等，收入，对家庭和性暴力的接触，无家可归以及性伴侣的 特征。但是，确定了预测血清转化的特征的组合 妇女并将其确立为PREP候选人的挑战。克服这个差距和 对RFA-AI-21-058的响应，我们建议利用创新的数字方法建立知识库 对于生活在行为上容易受到艾滋病毒的妇女。知识库将包括 我们将从中心收集艾滋病毒和性传播感染（ETI）的1,800名妇女的国家队列 发病率数据以及社交和性网络数据，并与开源大数据配对，以将HIV风险与之相关 在容易感染艾滋病毒的妇女中。我们的学习团队在使用数字方面拥有丰富的经验 招募研究参与者的方法（通过电子方法和地理空间分析）。大写 我们的专业知识，我们将使用开发的知识库来识别艾滋病毒的理论驱动相关性 血清转化，STI事件和预摄取的预测指标。调查结果将增加我们对 妇女患艾滋病毒感染的脆弱性，增强对准备资格的识别，并为干预措施提供干预措施 减少居住在美国的妇女中的艾滋病毒和性传播感染事件。