The Impacts of Mitigation Strategies to Prevent COVID-19 Transmission in American Indian Communities

美洲印第安人社区预防 COVID-19 传播的缓解策略的影响

• 批准号: 10410532
• 负责人: Randall K. Q. Akee
• 金额: $ 54.02万
• 依托单位: NATIONAL BUREAU OF ECONOMIC RESEARCH
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-25 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10410532
• 关键词: Address; Advocate; Affect; American Indians; Area; Behavior; Big Data; Businesses; COVID-19; COVID-19 impact; COVID-19 pandemic; COVID-19 prevention; California; Cellular Phone; Cessation of life; Chronic; Clinic; Communities; Commuting; County; Data; Data Analyses; Data Collection; Data Set; Data Sources; Death Rate; Destinations; Diabetes Mellitus; Dimensions; Economic Conditions; Economic Policy; Economics; Elderly; Employment; End stage renal failure; Epidemic; Evaluation; Funding; Future; Geography; Goals; Government; Health; Health Policy; Health care facility; Healthcare; Home; Incidence; Indian reservation; Indigenous; Intervention; Interview; Link; Measures; Medical; Methods; Minority Groups; Movement; Natural experiment; Nature; Outcome; Pattern; Personal Satisfaction; Persons; Play; Policies; Population; Public Health; Public Policy; Recommendation; Research; Research Design; Reservations; Role; Rural; SARS-CoV-2 infection; SARS-CoV-2 transmission; Services; Social Behavior; Social Conditions; Social Distance; Social Impacts; Source; Surveys; Techniques; Time; Transportation; Travel; Tribes; United States National Institutes of Health; Vaccines; Virus; Visit; Vital Statistics; Vulnerable Populations; Work; analytical tool; authority; behavioral economics; behavioral outcome; care outcomes; computer science; consumer behavior; cost; data hub; data resource; data warehouse; deep learning; design; economic behavior; economic impact; effectiveness evaluation; effectiveness measure; health care service; health care service utilization; health economics; implementation intervention; improved; infection rate; innovation; intervention effect; member; minority communities; non-Native; novel; operation; pandemic disease; prevent; public health emergency; public health research; response; rural Americans; rural area; secondary analysis; social vulnerability; tribal community; tribal lands; underserved minority

OTHER PROJECT INFORMATION – Project Summary/Abstract The Impacts of Mitigation Strategies to Prevent COVID-19 Transmission in American Indian Communities Very little is known about the impact of locally-mandated COVID-19 mitigation policies such as Non- Pharmaceutical Interventions (NPI) on the health and wellbeing of medically and economically vulnerable populations such as American Indians (AI) living in rural tribal lands. There is an urgent need to evaluate the effect of already implemented measures on the spread of COVID-19, the social and economic impact of those measures in these communities, and the potential spillover effects on non-AIAN communities. The staggered nature of the NPI implementation in tribal lands and the independence of sovereign nations’ policy decisions from local (e.g. county-level) policies present a unique quasi-natural experiment in policy timing, allowing us to study spillover effects from tribal NPIs to connected non-tribal areas. Our research efforts seek to improve American Indian health by understanding and evaluating these NPI measures on an NIH-designated disparity community. This R01 proposal has four specific aims: (1) Identify whether COVID-19 cases and deaths are related to the early closure of American Indian reservations and/or tribal casinos among Native and non-Native populations living on and off of adjacent reservation lands. (2) Identify the change in commuter patterns and movement behaviors as a result of NPIs. (3) Use in-time claims data to analyze how the implementation of NPIs and the progression of the epidemic affected utilization of different non-COVID-19 health care services and facilities. (4) Conduct a survey of American Indians living in rural areas to create a new primary data resource and cross-validate the results we obtain through analysis of secondary data of cell phone traffic flows. The long- term goal of this proposal is to develop and validate analytical tools that could be applied with large secondary datasets to aid the evaluation and design of public policies to address public health emergencies in AI populations. Our central hypothesis is that the timely implementation of tribal NPIs reduced the incidence of COVID-19 cases and deaths in AI communities and in traffic-connected areas. However, we also expect that the secondary effects of NPIs, such as economic hardship and under-utilization of non-COVID-related health care, would be stronger on tribal lands. We will use an innovative two-pronged approach to combine empirical analysis of secondary big data sources with primary data collection to provide robust evidence on the current and future effects of these policies. This proposal is significant because the impact of COVID-19 and related policies on tribal communities is under-researched, under-funded, and not well understood, and yet relevant not only for AI tribal policies and populations but for regional health and economic policies. Our research is guided by the C.A.R.E. Principles of Indigenous Data Governance developed by our team members. It is innovative because it applies techniques from economics, computer science and public health to deliver actionable results and recommendations for future policy implementation.

其他项目信息 - 项目摘要/摘要 美洲印第安人社区预防 COVID-19 传播的缓解策略的影响 人们对当地强制实施的 COVID-19 缓解政策（例如非限制性政策）的影响知之甚少。 针对医疗和经济弱势群体的健康和福祉的药物干预措施 (NPI) 迫切需要对居住在农村部落土地上的美洲印第安人 (AI) 人口进行评估。 已实施的措施对 COVID-19 传播的影响，以及这些措施的社会和经济影响 这些社区采取的措施，以及对非 AIAN 社区的潜在溢出效应。 实施部落土地中的NPI的性质和主权国家政策决定的独立性 来自地方（例如县级）政策的政策在政策时机上提出了一种独特的准自然实验，使我们能够 研究部落非营利机构对相关非部落地区的溢出效应我们的研究工作旨在改进。 通过根据 NIH 指定的差异了解和评估这些 NPI 措施来了解美洲印第安人的健康 该 R01 提案有四个具体目标：(1) 确定 COVID-19 病例和死亡是否属于 与提前关闭美洲印第安人保留地和/或原住民和非原住民部落赌场有关 (2) 识别通勤模式的变化 NPI 导致的移动行为 (3) 使用及时索赔数据来分析 NPI 的实施情况。 疫情的发展影响了不同非 COVID-19 医疗保健服务的利用 (4) 对生活在农村地区的美国印第安人进行调查，以创建新的主要数据资源。 并交叉验证我们通过分析手机流量的二手数据获得的结果。 该提案的长期目标是开发和验证可应用于大型二次开发的分析工具 帮助评估和设计公共政策以应对人工智能中的突发公共卫生事件的数据集 我们的中心假设是，部落 NPI 的及时实施减少了疾病的发生率。 AI 社区和交通连接区域的 COVID-19 病例和死亡情况 然而，我们也预计。 NPI 的次要影响，例如经济困难和非新冠相关医疗保健利用不足， 我们将采用创新的双管齐下的方法来结合实证分析。 二级大数据源与主要数据收集相结合，为当前和未来提供强有力的证据 这些政策的影响非常重要，因为 COVID-19 和相关政策对 部落社区的研究不足、资金不足、理解不够，但不仅与人工智能相关 部落政策和人口，但区域健康和经济政策是我们的研究的指导。 我们的团队成员制定的 C.A.R.E. 本土数据治理原则之所以具有创新性，是因为。 它应用经济学、计算机科学和公共卫生领域的技术来提供可行的结果， 对未来政策实施的建议。