Cross-Program Secondary Analyses and Public Health Innovation: The RADx Data Hub as a Resource for Integrated COVID-19 Research

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Abstract

The COVID-19 pandemic highlighted the need for timely, standardized research data to address future health challenges. From the pandemic, there has been a plethora of diverse data, including patient demographics, clinical outcomes, biospecimen information, and technology development frameworks. Yet, much of these data have been fragmented and without clear provenance and standardization. To overcome these limitations, the National Institutes of Health (NIH) established the RADx Data Hub (Data Hub) as a centralized platform to promote Rapid Acceleration of Diagnostics (RADx) data distribution under the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles. The Data Hub aggregated diverse COVID-19 diagnostic and clinical datasets into a harmonized repository that supports data integration, quality control, and secondary research. We independently tested Data Hub biomedical data management and data analysis capabilities to investigate its utility in viral monitoring, health disparity research, biomarker identification, and precarity modeling. We found that the Data Hub’s accessibility enabled efficient secondary research, including diagnostic and clinical data reuse. This supports repository use in accelerating infectious disease research and studying disease outcomes. Further, the Data Hub’s centralized, FAIR-aligned structure exemplifies a sustainable data stewardship model, extending beyond COVID-19 to addressing future public health emergencies, while strengthening the capacity to do reproducible science within broader biomedical research.

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