Addressing COVID-19 Testing Disparities in Vulnerable Populations Using a Community JITAI (Just in Time Adaptive Intervention) Approach: RADxUP Phase III

弱势群体，包括患有医疗合并症的人、生活在农村的人 不同背景和少数群体之间存在着显著的新冠肺炎差异。此外，拉美裔和 与白人相比，黑人感染和住院的可能性明显更大， 非西班牙裔美国人。建议的研究是建立在RADX-UP第一阶段和第二阶段工作的基础上 这些人口分布在三个种族不同的地区：休斯顿/哈里斯县、南得克萨斯州和 德克萨斯州东北部将增加SARS-CoV-2检测、疫苗接种和风险缓解行为，以 减少德克萨斯州服务不足人口中的新冠肺炎发病率、死亡率和不平等现象。 这项拟议的研究利用了临床和医疗中心的伙伴关系和资源 翻译科学(CCTS)，包括长期的社区伙伴关系。第三阶段将 包括混合方法和社区参与的方法，以告知我们的适应 现有(和开发新的)多层次干预信息、材料和 战略，重点是增加SARS-CoV-2的快速检测。它还将包括更广泛的 重点解决健康的社会决定因素(SDOH)，并强调抗击 错误的信息。拟议研究的创新要素包括测试一种新的方法 优化社区参与度，使用实时数据为干预适应和 实施，利用社会计算和机器学习的进步来更好地理解 社交媒体中的错误信息模式，并使用多层次社交网络分析 提高干预的灵活性、强度和可达性的技术。这个项目有三个目标： 目标1)扩大现有基于人口的新冠肺炎监测数据来源，以量化 德克萨斯州三个地区的感染、检测和疫苗接种趋势，并使用创新方法 通报和评估拟议的干预措施；目标2)调整、执行和评估 多层次社区即时适应性干预(MC-JITAI)在第二阶段至 增加SARS-CoV-2检测、缓解行为和新冠肺炎疫苗接种，其中 得克萨斯州三个地区的服务不足和弱势人口；以及Aim 3)决定 利用多层次社会网络改善SARS-CoV-2的可行性和有效性 在德克萨斯州的三个地区进行了测试和新冠肺炎接种。

Vulnerable populations including those with medical comorbidities, people living in rural settings and minorities experience significant COVID-19 disparities. Additionally, Hispanics and Blacks are significantly more likely to be infected and hospitalized when compared to White, Non-Hispanics. The proposed study builds on RADx-UP Phases I & Phase II work reaching these populations in three racially diverse regions: Houston/Harris County, South Texas, and Northeast Texas to increase SARS-CoV-2 testing, vaccination, and risk mitigation behaviors to reduce COVID-19 morbidity, mortality, and inequities among underserved populations in Texas. The proposed study leverages the partnerships and resources of the Center for Clinical and Translational Science (CCTS) including long-standing community partnerships. Phase III will include mixed methods and community-engaged approaches to inform adaptation of our existing (and the development of new) multilevel intervention messages, materials and strategies with a focus on increasing rapid SARS-CoV-2 testing. It will also include a broader focus on addressing the social determinants of health (SDOH) and an emphasis on combating misinformation. Innovative elements of the proposed study include testing a novel approach to optimize community engagement that uses real-time data to inform intervention adaptation and implementation, using advances in social computing and machine learning to better understand patterns of misinformation in social media, and using multilevel social network analysis techniques to increase intervention agility, intensity, and reach. This project has three aims: Aim 1) Expand existing sources of population-based COVID-19 surveillance data to quantify infection, testing and vaccination trends in three Texas regions, and use innovative methods to inform and evaluate the proposed interventions; Aim 2) Adapt, implement and evaluate the multilevel community just-in-time adaptive intervention (MC-JITAI) developed in Phase II to increase SARS-CoV-2 testing, mitigation behaviors, and COVID-19 vaccination, among underserved and vulnerable populations in three regions of Texas; and Aim 3) Determine the feasibility and effectiveness of leveraging multilevel social networks to improve SARS-CoV-2 testing and COVID-19 vaccination, in three regions of Texas.