A new model developed by Princeton and Carnegie Mellon researchers improves tracking of epidemics by accounting for mutations in diseases. Now, the researchers are working to apply their model to allow leaders to evaluate the effects of countermeasures to epidemics before they deploy them.
New mathematical model can more effectively track epidemics
John Sullivan, Office of Engineering Communications March 25, 2020
As COVID-19 spreads worldwide, leaders are relying on mathematical models to make public health and economic decisions.
A new model developed by Princeton and Carnegie Mellon researchers improves tracking of epidemics by accounting for mutations in diseases. Now, the researchers are working to apply their model to allow leaders to evaluate the effects of countermeasures to epidemics before they deploy them.
“We want to be able to consider interventions like quarantines, isolating people, etc., and then see how they affect an epidemic’s spread when the pathogen is mutating as it spreads,” said H. Vincent Poor, one of the researchers on this study and Princeton’s interim dean of engineering.
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