The impacts of HIV-related service interruptions during COVID-19 pandemic in South Carolina

南卡罗来纳州 COVID-19 大流行期间与 HIV 相关的服务中断的影响

• 批准号: 10700518
• 负责人: Shan Qiao
• 金额: $ 69.9万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-04 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10700518
• 关键词: AIDS prevention; Acquired Immunodeficiency Syndrome; Address; Adherence; Affect; Buffers; CD4 Lymphocyte Count; COVID-19; COVID-19 outbreak; COVID-19 pandemic; COVID-19 pandemic effects; Caring; Cellular Phone; Censuses; Clinic; Clinical; Collaborations; Communities; Data; Data Reporting; Data Science; Data Set; Deep South; Diagnostic Reagent Kits; Disasters; Disease Progression; Electronic Health Record; Epidemic; Equipment; Focus Groups; Funding; Future; HIV; HIV diagnosis; HIV/AIDS; HIV/STD; Health; Health Personnel; Health Policy; Health Services Accessibility; Health care facility; Health system; Hospitals; Human immunodeficiency virus test; Infrastructure; Institution; Interruption; Intervention; Interview; Investigation; Knowledge; Literature; Measures; Medical; Medicine; Modeling; Monitor; Monkeypox; Nature; Outcome; Outcome Measure; Patients; Persons; Pharmaceutical Preparations; Policy Making; Prevention; Provider; Public Health; Readiness; Recommendation; Research; Resource Allocation; Resources; Risk; Series; Services; Social Sciences; Solid; Source; South Carolina; State Government; Strategic Planning; Surveys; Time; Travel; United States National Institutes of Health; Viral; Viral Load result; antiretroviral therapy; care systems; climate change; cohort; coronavirus disease; data infrastructure; experience; health care availability; mortality; multiple data types; pandemic disease; pre-exposure prophylaxis; pressure; promote resilience; public health emergency; resilience; resilience factor; response; service organization; service utilization; social capital; social culture; stay-at-home order; supply chain; surveillance data; telehealth; transmission process; uptake

Abstract The global COVID-19 pandemic has imposed unprecedented pressure on health systems and has interrupted public health efforts for other major health conditions, including HIV. HIV service interruptions in the forms of redeployment of staff, reallocation of resources, lack of equipment and medicine (e.g., shortages of HIV/STI testing kits, strained drug supply chain), and reduced access to care (e.g., travel restrictions, lock downs) may have a profound and long-term impact on HIV treatment cascade outcomes, especially given the evolving nature of the pandemic. There are several gaps in the existing literature in addressing HIV service interruptions and their consequences. These gaps include a lack of using large-scale, real-world, multi-type data with theoretical guidance; the focus on single or limited HIV treatment cascade outcomes; and limited efforts to identify factors that can mitigate the negative impacts of such interruptions to inform potential interventions and capacity building at state or local levels. In response to NOT-AI-21-057, we propose to comprehensively investigate HIV service interruptions during the COVID-19 pandemic following a socioecological model, assess their impacts on various outcomes of the HIV prevention and treatment cascade, and identify resilience resources for buffering impacts of interruptions on HIV treatment cascade outcomes. Specifically, we will assess HIV service interruptions in South Carolina (SC) since 2020 using operational report data of Ryan White HIV clinics, in-depth interview data with clinic leaders and providers, and HIV service utilization data based on both electronic health records (EHR) and publicly available cellphone-based HIV clinics visitation data. We will further explore how HIV service interruptions affects HIV prevention and treatment cascade outcomes at appropriate geospatial units based on the integration of multi-type datasets (e.g., EHR, geospatial data) from multiple sources. Finally, we will identify institutional-, community-, and structural-level factors (e.g., resilience resources) that may mitigate the adverse impacts of HIV service interruptions based on the triangulation of quantitative (EHR data, online survey data) and qualitative (in- depth interviews, focus group discussion) data regarding health infrastructure, social capital, and organizational preparedness. Our proposed research can lead to a better understanding of complicated HIV service interruptions in SC and resilience factors that can mitigate the negative effects of such interruptions on various HIV treatment cascade outcomes. The multi-level resilience resources identified through data triangulation will assist SC health departments and communities in developing strategic plans in response to this evolving pandemic and other future public health emergencies (e.g., monkeypox, disasters caused by climate change). The research findings can also inform public health policymaking and the practices of other Deep South states with similar sociocultural contexts and experiences of HIV service interruptions during the pandemic.

摘要 全球COVID-19大流行给卫生系统带来了前所未有的压力， 公共卫生工作，包括艾滋病毒在内的其他主要健康状况。艾滋病毒服务中断的形式 重新部署工作人员、重新分配资源、缺乏设备和药品（例如，艾滋病毒/性传播感染短缺 检测试剂盒，紧张的药物供应链），以及获得护理的机会减少（例如，旅行限制、唐斯）可能 对艾滋病毒治疗级联结果产生深远和长期的影响，特别是考虑到不断变化的 大流行病的性质。现有文献在论述艾滋病毒服务方面存在若干空白 中断及其后果。这些差距包括缺乏使用大规模、真实世界、多类型的 具有理论指导的数据;关注单一或有限的艾滋病毒治疗级联结果;以及有限的 努力确定可以减轻这种中断的负面影响的因素， 国家或地方一级的干预措施和能力建设。针对NOT-AI-21-057，我们建议： 全面调查2019冠状病毒病大流行期间的艾滋病毒服务中断情况， 社会生态模型，评估其对艾滋病毒预防和治疗级联的各种结果的影响， 并确定弹性资源，以缓冲中断对艾滋病毒治疗级联结果的影响。 具体而言，我们将使用运营数据评估自2020年以来南卡罗来纳州的艾滋病毒服务中断情况。 Ryan白色艾滋病诊所的报告数据，与诊所领导和提供者的深入访谈数据，以及艾滋病 基于电子健康记录（EHR）和基于手机的公共服务使用数据 艾滋病毒诊所访问数据。我们将进一步探索艾滋病毒服务中断如何影响艾滋病毒预防， 基于多种类型数据集整合的适当地理空间单位的治疗级联结果 (e.g., EHR，地理空间数据）。最后，我们将确定机构、社区和 结构级因素（例如，可减轻艾滋病毒服务的不利影响 基于定量（电子健康记录数据，在线调查数据）和定性（在 深度访谈、焦点小组讨论）有关卫生基础设施、社会资本和 组织准备。我们提出的研究可以更好地了解复杂的艾滋病毒 供应链中的服务中断和弹性因素，可以减轻这种中断对 各种艾滋病毒治疗级联结果。通过数据识别的多层次韧性资源 三角测量将协助SC卫生部门和社区制定战略计划， 这种不断发展的流行病和其他未来的公共卫生紧急情况（例如，猴痘， 气候变化）。研究结果还可以为公共卫生政策制定和其他国家的做法提供信息。 在2010年期间，具有类似社会文化背景和艾滋病毒服务中断经历的深南方各州 流行病