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Crowded restaurants, gyms, cafes and other indoor venues accounted for around 8 in 10 new infections in the first months of the coronavirus outbreak in the United States, according to new analysis that could help officials around the world consider now curfews, partial lockdowns and other measures in response to new outbreaks.
The study, which used cell phone mobility data from 10 U.S. cities from March through May, also explains why many low-income neighborhoods were hit the hardest. Public spaces in these communities were more crowded than in the wealthier ones and residents were more mobile on average, likely due to work demands, the authors said in a study published Tuesday in the journal Nature.
The data came from the metropolitan areas of Atlanta, Chicago, Dallas, Houston, Los Angeles, Miami, New York, Philadelphia, San Francisco and Washington DC
Infectious disease models had provided similar estimates of the risk posed by crowded indoor spaces, dating back to February; all of these models are subject to uncertainties, due in large part to unforeseen changes in community behavior. The new analysis provides more precise estimates of the contribution of each type of location to urban epidemics, by tracking hourly movements and accounting for mobility reductions due to lockdown restrictions or other changes that occurred during these early days. crucial months. He was not modeling the infection in schools or offices.
“Restaurants were by far the riskiest places, about four times riskier than gyms and cafes, followed by hotels” in terms of new infections, said Jure Leskovec, a computer scientist at Stanford University and lead author of the new report, at a conference. call with reporters. The study was a collaboration between scientists from Stanford, Northwestern University, Microsoft Research and the Chan Zuckerberg Biohub.
Public officials across Europe and parts of the United States, including Governor Phil Murphy of New Jersey, have begun instituting partial restaurant and bar closures, or limited hours of operation to the indoors, as new infections have increased in recent weeks. In New York City, a spike in virus cases threatens the city’s recovery and could mean “a lot more restrictions,” Mayor Bill de Blasio said on Monday.
These measures are especially important in low-income areas, suggests the new study. Infections exploded in many such communities last spring, and the new model provides a likely explanation: local places tend to be more crowded than elsewhere.
Researchers took a close look at grocery stores to understand the differences between high and low income communities. In eight of the ten cities, transmission rates were twice as high in low-income areas as in high-income areas. The mobility data pointed to a reason: grocers in low-income neighborhoods had nearly 60 percent more people per square foot; buyers tended to stay there longer as well.
And residents are apparently less able to shelter in their homes.
“We think a big reason for this is that essential workers had to be at work, they weren’t working from home,” said Serina Chang, also co-author at Stanford.
In the analysis, the research team mapped the hourly mobility of some 98 million people to and from indoor public spaces, such as grocery stores, churches, hotels and bars. He calculated the traffic to each location over the course of a day, how long people stayed on average, and the square footage of the location. Given the background infection rate, the researchers then evolved the model – “hit play,” said Dr Chang, and observed how infections spread and where, using standard infectious disease assumptions. .
The estimates dovetailed well with what actually happened in those towns – a crucial reality check, as from March 1 to May 2, the behavior of communities changed dramatically due to stay-at-home orders.
In Chicago, for example, new infections occurring at just 10% of indoor sites accounted for 85% of expected infections. According to the analysis, the reopening of full-service restaurants alone would have resulted in an additional 600,000 new infections by the end of May.
By focusing on indoor public places, researchers could also model the impact of partial restrictions. Limiting restaurant occupancy to one-fifth of capacity, for example, would reduce new infections there by 80%, while preserving around 60% of customers.
“These are important compromises,” said Dr Leskovec. “Our work shows that it doesn’t have to be all or nothing” when implementing restrictions.
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