US research includes crowded restaurants, gyms as COVID-19 “superspreader” places
As the festive season draws near and people throng about, it is important to be aware of – and avoid – places where you’re most at risk of being infected with the dreaded novel coronavirus. A recent computer model analysis by researchers at Stanford University, California, has singled out “superspreader” locations, such as restaurants, gyms and cafes, where the virus is most likely to linger and spread; the predictions later proved accurate based on officially reported infection numbers.
Earlier, researchers chose to study anonymised cell phone data to map the movements of 98 million people from the largest metropolitan areas in the US including New York, San Francisco, and Los Angeles; the US has been steadily breaking case number records daily while many European countries also report record figures, with some imposing new restrictions and lockdowns.
Read: New insight into secondary transmission of COVID-19 at home
Feeding this data to an epidemiological model to predict how the virus is spread in closed spaces, the researchers found that, on average, full-service restaurants, gyms, hotels, cafes, religious organisations, and limited-service restaurants produced the largest predicted increases in infections when in business. (Restaurants at a full capacity ranked first, followed by gyms, cafes, and hotels.)
The researchers additionally looked at infection rate among people from different demographic backgrounds and neighbourhoods, and noticed that people from poor neighbourhoods are most likely to contract COVID-19. The data showed that these people are less able to work from home for various reasons, while the stores they usually visit tend to be more crowded than those in more affluent areas; they also stay inside those stores longer than customers in high-income areas.
Lead researcher Jure Leskovec, Dept. of Computer Science at Stanford University, surmises, “Infections are happening very unevenly — that there are about 10% of points-of-interest that account for over 80% of all infections, and these are places that are smaller, more crowded and people dwell there longer.”
The researchers believe their computer model provides a simple solution to reduce COVID-19 transmission without shutting down the economy, especially in less-developed nations, and hope their findings will prevent further virus spread.
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