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 longterm 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.