A small minority of places where people go frequently account for a large majority of coronavirus infections in big cities, according to a new modeling study.
The study, published in the journal Nature on Tuesday, suggests that reducing the maximum occupancy in such places – including restaurants, gyms, cafes and hotels – can slow the spread of illness substantially.
“Our model predicts that capping points-of-interest at 20% of maximum occupancy can reduce the infections by more than 80%, but we only lose around 40% of the visits when compared to a fully reopening with usual maximum occupancy,” Jure Leskovec, an author of the study and associate professor of computer science at Stanford University, said during a press briefing on Tuesday.
“Our work highlights that it doesn’t have to be all or nothing,” he said.
The model also found significant racial and socioeconomic inequities in coronavirus infections.
Model spotlights potential ‘superspreader’ places
The researchers – from Stanford University and Northwestern University – used cell phone location data from SafeGraph to model the potential spread of Covid-19 within 10 of the largest metropolitan areas in the United States: Atlanta, Chicago, Dallas, Houston, Los Angeles, Miami, New York, Philadelphia, San Francisco and Washington DC.
The data, representing the hourly movements of 98 million people, included mobility patterns from March to May.
The researchers examined Covid-19 case counts for each area and took a close look at how often people traveled to certain non-residential locations or “points-of-interest.”
Those locations included grocery stores, fitness centers, cafes and snack bars, doctor’s offices, religious establishments, hotels and motels and full-service restaurants.