NIH Provides Funding for COVID-19-Related Big Data Projects

The National Institutes of Health (NIH) is offering contracts to seven companies and academic organizations to develop COVID-19-related digital technologies using big data.

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The projects could lead to tools like smartphone apps, wearable devices, and software that can monitor the spread of COVID-19, track the verified COVID-19 results, and assess the health status of infected individuals.

The National Cancer Institute (NCI) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) chose the seven projects from nearly 200 different ideas. The projects represent a broad range of solutions for immediate public health needs related to the pandemic, and several focus on solutions for medically underserved communities and people with limited access to healthcare.

“The tools these organizations plan to develop could allow us to use containment efforts, like COVID-19 testing, social distancing, and quarantine, precisely when and where they’re needed. That might let more people return to less restricted living and reduce the risk of devastating local outbreaks,” said NCI Director Norman E. Sharpless, MD. “We are working as quickly as possible to help businesses and universities develop innovative tools to achieve this goal.”

The effort is a key part of NCI’s and NBIB’s responses to the COVID-19 pandemic. NCI has previously provided $306 million to support serological science research, expand testing capacity, and develop other technologies for COVID-19, while NBIB has provided supplemental funding to help address COVID-19.

NCI and NBIB will award the contracts in two phases. Researchers and developers will use the initial awards in phase one to demonstrate feasibility of the project. After assessing phase one results, a contractual option for phase two would provide additional funding for further development of the awardee’s program and demonstration of utility in response to the pandemic.

If all seven projects were to move into the second phase, the total value of the contracts in this network would be $22.8 million. Awardees have one year to complete both phases.

The seven digital health solutions include a project from IBM that aims to develop sophisticated contact tracing and verifiable health status reporting. This will lead to a wide array of research data that simultaneously empowers users and facilitates research.

NCI and NIBIB will also provide funding to the University of California, San Francisco (UCSF), where researchers are working to create a GPS-based retroactive contact tracing tool for alerting users about contact with COVID-19-infected individuals. The tool would also identify businesses that were visited by someone who later tested positive for COVID-19, and would help businesses and public health departments develop strategies to reduce the spread of the virus.

In Fairfax, Virginia, Vibrent Health will use the funding to develop mobile applications, data integrations, and validated machine learning algorithms to identify COVID-19 and differentiate it from the flu. iCrypto in Santa Clara, California is leveraging the NIH contract to build a smartphone-based platform to provide irrefutable proof of testing, serologic, and vaccination status for individuals.

The proposed digital health tools will leverage multiple data sources, such as wearable devices and COVID-19 diagnostic and serology test results. Each organization will share data and other assets in an NIH-supported central data hub in ways that protect individuals’ privacy. To facilitate further research, researchers will also have access to data stored in the hub.

With all projects, there is an emphasis on providing adequate privacy protections that allow researchers and developers to collect personal health data without compromising civil liberties.

“Digital health technologies built around smartphones and wearable devices will play an essential role in guiding us through the COVID-19 pandemic,” said NIBIB Director Bruce J. Tromberg, PhD.

“These platforms can acquire large amounts of data from many different sources spanning from testing technologies to sensors. When this information is analyzed using cutting-edge computational and machine learning methods, everyone will have access to powerful new tools for reducing the risk of infection and returning to normal activities.”