USF Electrical Engineering Associate Professor Sylvia Thomas (PI) and Computer Science, Engineering Assistant Professor Tempestt Neal (Co-PI), with Alessandro Negro (Co-PI) from GraphAware, Inc. were awarded a one-year $200,000 NSF grant for the project titled RAPID: Early Detection of Disease Outbreaks using Self-Organizing Patterns – COVID-19.
With globalization and increased international travel of goods, products, and people, disease transmission across national borders is inevitable once person-to-person transmission has begun, making early detection critical to containing the spread of infectious diseases. Thomas, Neal, and GraphAware, Inc. will investigate new models based on the theory of self-organizing systems for early detection of disease outbreaks. This research will leverage GraphAware’s Hume network-science oriented software to create accessible and usable knowledge graphs capable of representing and integrating heterogeneous data sources that can be analyzed from many different perspectives at scale and in real time.