The C3.ai Digital Transformation Institute, an AI research consortium founded in March by the AI software firm C3.ai, Microsoft and several US academic institutions, is developing modeling and AI-based tools to mitigate pandemics. Its first research awards are focused on a broad swathe of topics that intersect with COVID-19, including social issues, such as housing precariousness and the social determinants of health, as well as technical problems, such as mathematical modeling and computational biology.
For example, Vince Poor, professor of electrical engineering at Princeton University, and collaborators in Princeton, Carnegie Mellon University and the University of Pennsylvania are applying network engineering concepts to model the epidemiology of COVID-19. A key element of their approach is to incorporate a more nuanced description of R0, which is the average number of new infections expected to arise in a naïve population from one infected individual. By modifying the ‘susceptible, infected and recovered’ (SIR) model, they aim to develop a more accurate picture of the spread of the virus. “Instead of applying a uniform R0 across the entire population, the idea is to apply a probability distribution to the transmissibility of each individual in the population,” he says.
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