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Mobility models of COVID-19 inform reopening

Restaurants, gyms, cafes and other crowded indoor venues accounted for some 8 in 10 new coronavirus infections in the early months of the U.S. epidemic, according to a new analysis that could help officials around the world now considering curfews, partial lockdowns and other measures in response to renewed outbreaks.

The New York Times recently wrote about a new study from Stanford Data Science co-director, Dr. Jure Lesckovec et al., on a model which predicts that a small minority of “superspreader” points of interest (POI) account for a large majority of  COVID-19 infections and that restricting maximum occupancy at each POI is more effective than uniformly reducing mobility. 

New York Times: Research using spring cellphone data in 10 U.S. cities could help influence officials

This research was part of the Stanford Data Science Collabratory.

Mobility network models of COVID-19 explain inequities and inform reopening

Read paper here:

Read pre-print here: