With South Carolina?s population already being vulnerable to poor health as evidenced by poor national health rankings, challenging rural geography and health professional shortages, the impact of the novel Coronavirus Disease 2019 (COVID-19) will be long lasting in the state. Patient morbidity and mortality rates already continue to increase, with ongoing economic damage to health systems and businesses. The speed of transmission and geographical spread of COVID-19 across South Carolina and the United States is alarming, which combined with the novel nature of the disease justifies the need for accelerated research to combat this pandemic. As clinicians and frontline health workers battle to save lives, creating a data environment that accelerates research is key, and necessary to battle the disease. Access to such information will equip frontline health workers to continue the fight against the disease. This proposal will build the capacity for accelerated research and intelligence gathering by coalescing multiple state partners and leveraging relevant data for discoveries around COVID-19. To accomplish this, this proposal aims to (1) create a de-identified linked database system via REDCap and a mobile application (app) to collate surveillance, clinical, multi-omics and geospatial data on both COVID-19 patients and health workers treating COVID-19 patients in South Carolina; (2) examine the natural history of COVID-19 including transmission dynamics, disease progression, and geospatial visualization; and (3) identify important predictors of short- and long-term clinical outcomes of COVID-19 patients in South Carolina using machine learning algorithms.
These aims will be accomplished through collaborations with multiple state agencies and stakeholders relevant to COVID-19 and the creation of a REDCap database and mobile app that allow for coalescing relevant data in a timely fashion, combined with leveraging of statewide integrated data warehouse capabilities.

Public Health Relevance

COVID-19 represents an opportunity to create and deploy a research system that allows accelerated research on any pandemic. While South Carolina is rural in nature, and has low health rankings, it has a powerful integrated health data infrastructure that allows for tracking short-and long-term clinical and health system impacts of pandemics like the novel coronavirus (COVID-19). The creation of multiple data sources at the individual level, coupled with innovative big data science techniques will advance important discoveries in disease surveillance, transmission, natural history and progression important for treatment and necessary for targeted intervention purposes in South Carolina.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Mckaig, Rosemary G
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University of South Carolina at Columbia
Public Health & Prev Medicine
Schools of Public Health
United States
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Zhang, Qingpeng; Zhong, Lu; Gao, Siyang et al. (2018) Optimizing HIV Interventions for Multiplex Social Networks via Partition-Based Random Search. IEEE Trans Cybern 48:3411-3419