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A multidisciplinary team of researchers from UCLA and UC Irvine have received an 18-month, $996,000 grant from the National Science Foundation to develop a comprehensive, early-warning system to predict the emergence and spread of the next pandemic.

The diagram shows the components of an AI-based pandemic warning system.
AsterixDB, Texera and Clouberry are software systems to support data collection, storage, analytics and visualization. Courtesy of Wei Wang/UCLA Samueli

The 10-member team includes experts in biology, social sciences, epidemiology and computer science. The principal investigator of the grant is Wei Wang, the Leonard Kleinrock Professor of Computer Science at the UCLA Samueli School of Engineering and a professor of computational medicine, a department affiliated with both UCLA Samueli and the David Geffen School of Medicine at UCLA. At UC Irvine, Chen Li, a professor of computer science in the Donald Bren School of Information and Computer Sciences, will lead research efforts.

The team’s goal is to develop a predictive system powered by artificial intelligence, machine learning, data science and other open-source technologies that can spot signs of new and evolving infectious diseases in real time, predict their potential spread and continuously monitor their risk factors around the globe.

“The ongoing global COVID-19 pandemic, along with other recent disease outbreaks, have made it clear that our interconnected world needs to better prepare for pandemics as the next one is more a matter of ‘when’ and not ‘if’,” Wang said. “This grant from the National Science Foundation will support our multidisciplinary team’s efforts in developing an open-source, intelligence-gathering-and-analysis system that sifts through a broad range of data — biological, environmental, socio-economic and behavioral — across a diverse range of sources, including the media, looking for early signals of pathogens with the potential for major outbreaks.”

The NSF funding will support the development and demonstration of the technology, and place it in contention for additional funding through a full-fledged research center in the project’s next phases.

“Ultimately, a pandemic early-warning system could be comparable to weather forecasting, where advances in big data technologies and information analysis have resulted in better forecasts that are further out,” Li added. “Such a system for forecasting potential pandemics could allow for better and faster responses in public health, medicine and government sectors.”

Other UCLA faculty members on the research team are Kai-Wei Chang, associate professor of computer science; Eleazar Eskin, professor and chair of the Computational Medicine Department, and a professor of computer science and human genetics; Quanquan Gu, associate professor of computer science; and Violet Peng, assistant professor of computer science and computational medicine.

Additional UC Irvine researchers on the team are Carter Butts, Chancellor’s Professor of Sociology; Andrew Noymer, associate professor of public health; Kristin Turney, professor of sociology; and Dominik Wodarz, professor of public health.

The grant was made possible by the NSF’s Predictive Intelligence for Pandemic Prevention Phase I program, which is jointly funded by the foundation’s directorates for Biological Sciences; Engineering; Computer Information Science and Engineering; as well as Social, Behavioral and Economic Sciences.

Originally posted on the UCLA Samueli Newsroom