Tracking study sees higher virus risk in restaurants, gyms
Restaurants, gyms and coffee shops rank high among places where the coronavirus is most likely to spread outside the home. That’s according to a newly published report based on data from millions of Americans, tracked by their phones as they went about daily life during the pandemic’s first wave.
The study provides statistical support for a strategy built around limiting capacity at indoor venues — such as capping crowds at 20% — while allowing those sites to remain open. The researchers contend that such a strategy can make a huge dent in the infection rate while causing a far more modest drop in the total number of visits to those venues.
Starting with a “very simple” epidemiological model, the researchers superimposed the cellphone mobility data and pressed play on simulated viral spread, said Northwestern University epidemiologist Jaline Gerardin.
The predicted infections largely matched actual coronavirus caseloads in the studied regions, as tallied by The New York Times.
“Based on the data, the main result is that mobility data can be useful for predicting the spread of covid-19. This is extremely helpful to policymakers,” said Solomon Hsiang, director of the Global Policy Laboratory at the University of California at Berkeley, who has modeled the effects of several nations’ pandemic policies and was not involved with this work.
There are a few caveats. The researchers’ model cannot say with certainty where exposure occurred. Nor was it able to capture information about nursing homes or schools, largely because that phone-based location data was unavailable. And it does not account for environmental factors such as ventilation, or the protective behaviors that have become more widespread since the outbreak began.
“It is important to emphasize that many behaviors, such as wearing masks, washing hands and providing services outdoors reduce transmission,” Hsiang said.
Tuesday’s report in the journal Nature, by Gerardin and her colleagues at Northwestern and Stanford universities, used anonymized data from 98 million Americans living in Chicago, Washington, New York City and seven other metro areas. The scientists focused on movement within 57,000 census block groups — the small geographical units that make up census tracts — from March to May 2.
In those regions, the scientists traced visits to 550,000 cafes, hotels and other venues. Geospatial data, which the company SafeGraph provided to the scientists, showed how long people remained in locations, how frequently they visited and how crowded those places were.
Certain venues — places of worship, full-service restaurants and gyms — disproportionately contributed to infections. In Chicago, for instance, 10% of sites accounted for 85% of predicted infections.
The study discerned another pattern: Lower-income people, many of them essential workers, were less able to reduce their mobility during shutdowns and more likely to be exposed to crowded venues. Within low-income neighborhoods, with higher percentages of residents who are people of color, more people would be infected, which mirrors real-life patterns of transmission.
“They have to get to work; they are in occupations that are deemed vital,” said Northwestern sociologist Beth Redbird, a study co-author. Public-facing jobs may put people at higher risk of exposure — one recent study found 20% of workers at a Boston grocery store had the coronavirus in May.
This study suggested a grocery store would be doubly as dangerous for a person in a low-income neighborhood as a high-income one. The authors hypothesized this was because those stores had nearly 60% more visitors per square foot per hour, who shopped there longer on average.
Earlier models indicated that timing of shutdown orders was vital. One estimated 36,000 lives would have been saved if mid-March’s social-distancing rules began a week sooner. This model indicates that setting caps on crowds is quite powerful, too.
John Carlo, a Dallas physician who specializes in public health, applauded the new study for highlighting the importance of the density of crowds in indoor venues like grocery stores.
“It’s not just the activity itself, it’s the density of that activity. It’s one thing to go to a supermarket, and it’s another thing to go to a crowded supermarket,” Carlo said. He said if he shops at 7 a.m., there may be no one in the store, but “if I go Sunday afternoons, just before the Cowboys game, it’s jam-packed.”
Jeffrey Shaman, a Columbia University epidemiologist who also has worked on models of how the virus spreads, praised the new paper but cautioned that it does not answer precisely where the virus is being spread.
“We can’t say, ‘This is a prescription to say you gotta shut down your pizza joints and your banks as opposed to your grocery stores,’ or whatever. This paper takes us a little closer to that, but I don’t know if we’re ever going to achieve it,” Shaman said.