ModelsResearchers Devise New Model to Track COVID-19’s Spread

Published 29 April 2020

Yale University researchers and colleagues in Hong Kong and China have developed an approach for rapidly tracking population flows that could help policymakers worldwide more effectively assess risk of disease spread and allocate limited resources as they combat the COVID-19 pandemic. Mike Cummings writers for Yale News that the approach, described in a study published early online on April 29 in the journal Nature, differs from existing epidemiological models by exploiting real-time data about population flows, such as phone use data and other “big data” sources that can accurately quantify the movement of people.