About RADx Data Hub
The NIH Rapid Acceleration of Diagnostics Data Hub (RADx Data Hub) supports researchers in accessing curated and de-identified COVID-19 data, allowing them to find, aggregate, and perform data analyses in a cloud-enabled platform.
The RADx Data Hub supports efforts to understand COVID-19 and factors associated with disparities in COVID-19 morbidity and mortality in underserved and vulnerable populations. To do this, the RADx Data Hub seeks to accelerate scientific solutions and innovations in the development, commercialization, and implementation of technologies for COVID-19 testing by providing de-identified COVID-19-related data, algorithms, and other capabilities generated by various digital health solutions and technologies.
The RADx Data Hub allows researchers to share the results of their analyses and relevant data, collaborate with other members of the research community, and make use of AI machine learning algorithm research that supports their individual contributions.
RADx Coordinating and Data Collection Centers
Sharing RADx data and results as rapidly as possible will allow researchers to conduct secondary analyses and address issues related to the difficulties with the detection and prevention of community spread for COVID-19, ultimately leading to rapid development of new technologies needed to move the nation beyond the pandemic. As such, the RADx Data Hub supports the following RADx Coordinating and Data Collection Centers (C)DCCs, which collect and share a wide variety of COVID-related research data and technologies:
RADx Tech
The RADx Tech initiative aims to speed the development, validation, and commercialization of innovative point-of-care and home-based tests and improve clinical laboratory tests that can directly detect the COVID-19 virus. RADx Tech has expanded the NIH’s National Institute of Biomedical Imaging and Bioengineering (NIIBIB) Point-of-Care Technologies Research Network (POCTRN) that is using a flexible, rapid process to fund and enhance technology designs at key stages of development with expertise from technology innovators, clinical testing, regulatory affairs, entrepreneurs, and business leaders. Learn more at https://www.covid19testus.org
RADx Underserved Populations (RADx-UP)
The overarching goal of the RADx-UP initiative is to understand the factors associated with disparities in COVID-19 morbidity and mortality in order to reduce health disparities for underserved and vulnerable populations, who are disproportionately affected by the highest infection rates of COVID-19 and are most at risk for complications or poor outcomes from the pandemic. Learn more at https://radx-up.org/
RADx Radical (RADx-rad)
The RADx-rad effort is aimed to address usability, accessibility, and accuracy gaps in COVID-19 testing by supporting existing and new, non-traditional approaches, including rapid detection devices and home-based testing technologies. This work may also lead to new ways of identifying SARS-CoV-2 virus and its variants. Learn more at https://www.radxrad.org/
RADx Digital Health Technologies (RADx DHT)
The RADx DHT goal is to develop digital health solutions, including user-friendly tools such as smartphone apps, wearable devices, and software, to identify and trace contacts of infected individuals, track verified COVID-19 test results, and monitor health status of infected and potentially infected individuals. Learn more at https://rapids.ll.mit.edu/
A partnership of Stanford University (Stanford), Booz Allen Hamilton, and the Renaissance Computing Institute (RENCI) assists the NIH with three key aspects of the RADx Data Hub:
- Data Hub Development: Develop and enhance the Data Hub functions that store, share, and provide data analysis and utilization capabilities (Booz Allen Hamilton )
- Data Management: Translate proposed standards for data and metadata into computational form, validate data quality, and enable greater use of common data elements, standardization, and harmonization (Stanford )
- Program Management: Establish and maintain effective cross-disciplinary program management, including technical development, data coordinating center connectivity, researcher engagement, and training (RENCI )
