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.
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.
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.
“This work shows that it is possible to very accurately forecast the timing, intensity, and geographic distribution of the COVID-19 outbreak based on population movement alone,” said Yale’s Nicholas A. Christakis, Sterling Professor of Social and Natural Science and a co-author of the study. “Moreover, by tracking population flows in real time, our model can provide policymakers and epidemiologists a powerful tool to limit an epidemic’s impact and save lives.”
Read more at Yale University
Image by Arek Socha from Pixabay
