The rapid global spread of COVID-19 is changing the way we handle pandemics and has prompted academia, private industry, and government to leverage new technologies and approaches to minimize the impact on human lives. While much attention is on outbreaks in urban areas, the efforts to assist rural populations has lagged. The rural communities encompass roughly 19.3% of the US population and 95% of the US land area. They are especially vulnerable to disease outbreaks due to lower levels of necessary resources, such as access to hospitals, internet, 911, as well as overall lower socioeconomic status. The impacts of COVID-19 in rural areas are expected to be devastating. This project delivers research, scientific, and COVID-19 planning to three rural communities. The deliverable to the research community is access to hundreds of layers of integrated geospatial data that are available for advanced queries and visualization of results to support their own COVID-19 research. In addition, research results will enhance the understanding of disease transmission behavior and enable preparation for resilience in rural populations. The scientific community will receive new computational methods inspired by the rural disease analysis and associated resource management need assessment and tracking. The implementation of this mathematical and computational work will be made available to the COVID-19 planning community, including rural stakeholders, by creation of an interactive dashboard where maps and summaries will provide the frontline clinicians and/or public health responders up-to-date reports and context for specific rural areas. The project focuses on Missouri?s rural areas with a plan to extend the framework to the bordering states.
This project addresses whether the recent advancements in geospatial and network analyses can be leveraged to provide a scalable connected health ecosystem for rural America in response to the COVID-19 outbreak. It also address the new innovations necessary to bring explainable intelligence the future waves of COVID-19 outbreak. To answer these issues, the research team, consisting of experts in computing, geoinformatics, influenza, virology, pathology, acute care, and telemedicine, plans the following: (1) the team will first rapidly extend their previous work with the unique GeoSPatial Analytical Research Knowledgebase (GeoSPARK) big data framework with relevant data from the Census, healthcare systems, as well as the evolving information surrounding COVID-19 disease dynamics. GeoSPARK will provide real-time analysis using advanced complex queries across multi-resolution locational information to address the lack of an integrated data framework dedicated to COVID-19 risk assessment, capacity investigation, and geo-enabled decision support. (2) The team will develop and implement a suite of geospatial analytic methods which are inspired by the dynamics of disease outbreaks, such as network analysis (e.g., scenario analyses ? analyze the sensitivity and impact of disruptions in resource distribution, containment, etc.), hot spot analysis, contextual analysis, clustering analysis, etc., to quantitatively weigh risk and assess the multi-faceted problem of rural disparity. The analytical tools and dashboards inspired by the field?s needs and disease dynamics in rural areas are transformative and will enable better understanding of scenarios other than COVID-19, such as zoonotic disease outbreaks, flooding, and earthquakes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
