BEIJING, 12 November (BelTA - Xinhua) - Most COVID-19 cases in large U.S. cities stem from visits to just a few types of places, a new study finds.
Metros, restaurants, gyms, hotels, cafes and religious organizations produce the largest predicted increases in infections when reopened, according to a research published in the journal Nature on Tuesday.
The model predicted that "infections are happening very unevenly -- that there are about 10 pct of points-of-interest that account for over 80 pct of all infections, and these are places that are smaller, more crowded and people dwell there longer," Jure Leskovec, an author of the study and associate professor of computer science at Stanford University, said during a press briefing on Tuesday.
The study suggested that by capping a 20 pct of maximum occupancy of those places, the infections could be reduced by more than 80 pct.
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 model also predicted that people living in lower-income neighbourhoods were more likely to have been infected.
One of the possible cause of this observed disparities is that lower-income neighbourhoods tend to have higher numbers of front-line workers, who had less overall reduction in mobility during lockdowns.
The second possible contributor is that, across many types of setting, the venues visited by people from lower-income neighbourhoods tend to be more crowded than are the venues visited by those from higher-income areas, according to the study.
The study comes with limitations, including that the model is a simulation -- not a real-life experiment -- and the data are based on 10 metropolitan areas and do not capture all places someone could frequent, such as schools, nursing homes and prisons, which also have been associated with COVID-19 outbreaks. More research is needed to determine whether similar findings would emerge among other populations and places.
