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: 10249585
• 负责人: Randall K. Q. Akee
• 金额: $ 51.36万
• 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/10249585
• 关键词: Address; Advocate; Affect; American Indians; Area; Behavior; Big Data; Businesses; COVID-19; 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; 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 缓解策略的影响，以防止19日在美洲印第安人社区传播 关于本地授权的1900减轻政策的影响，诸如非 - 关于医学和经济脆弱的健康和福祉的药物干预措施（NPI） 居住在粗糙的部落土地上的美国印第安人（AI）等人口。迫切需要评估 已经实施的措施对Covid-19的传播的影响，即那些人的社会和经济影响 这些社区的措施以及潜在的Spilover对非AIAN社区的影响。交错 NPI在部落土地上实施的性质和主权国家政策决定的独立性 从当地（例如县级）政策中，在政策时机中提出了一个独特的准自然实验，使我们能够 研究从部落NPI到连接的非部落区域的Spilover效应。我们的研究工作旨在改善 通过理解和评估NIH指定差异的这些NPI措施，美国印第安人的健康 社区。该R01提案具有四个具体目的：（1）确定COVID-19案件和死亡是否是 与本地和非本地人之间的美洲印第安人保留和/或部落赌场的早期关闭有关 居住在相邻预订土地上的人群。 （2）确定通勤模式的变化和 NPI导致运动行为。 （3）使用及时索赔数据分析NPI的实施方式 流行病的进展影响了不同非旋转199的医疗保健服务的利用 设施。 （4）对居住在农村地区的美洲印第安人进行调查，以创建新的主要数据资源 并通过分析手机流量流的辅助数据来跨验证我们获得的结果。长期 该提案的一项目标是开发和验证可以与大型次要一起应用的分析工具 数据集以帮助评估和设计公共政策，以解决AI中的公共卫生紧急情况 人群。我们的中心假设是，及时实施部落NPI减少了事件 AI社区和交通连接的地区的COVID-19案件和死亡。但是，我们也期望 NPI的次要影响，例如经济困难和非杂化医疗保健的利用不足， 在部落土地上会很强大。我们将使用一种创新的两管齐的方法来结合经验分析 带有主要数据收集的次要大数据源，以提供有关当前和未来的可靠证据 这些政策的影响。该提案很重要，因为Covid-19和相关政策对 部落社区的研究不足，资金不足且不太了解，但不仅与人工智能有关 部落政策和人口，但针对区域卫生和经济政策。我们的研究以 关心。我们的团队成员制定的土著数据治理原则。这是创新的，因为 它采用经济学，计算机科学和公共卫生的技术来提供可行的结果， 未来政策实施的建议。