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Restaurants, Gyms, Religious Sites: New Study Finds Locations You're Most Likely to Catch Covid-19

People eat at a mostly empty restaurant with tables on the street, in the financial district during the coronavirus disease (COVID-19) pandemic in the Manhattan borough of New York City, Credits: Reuters

People eat at a mostly empty restaurant with tables on the street, in the financial district during the coronavirus disease (COVID-19) pandemic in the Manhattan borough of New York City, Credits: Reuters

The model also predicted that people living in neighborhoods with the lowest income, based on Census data, were more likely to have been infected -- driven in part by how places in those areas tended to be smaller in size, leading to crowding and increasing the risk of spread.

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Buzz Staff

Ten months into a global pandemic, we've become more or less used to the new normal - face masks, hand sanitizers, social-distancing.

We've started going out, eating at small businesses, enjoying open air entertainment, and limiting visiting crowded places: But cases are still rising, with more and more people being infected every single day.

This is also because interactions have increased a lot more than before: More people are going out than in lockdowns or initial days when they only stepped out for essentials.

A new scientific study, published in Nature, found the places you're most likely to catch Covid-19.

The study found that a small minority of places where people go frequently account for a large majority of coronavirus infections in big cities.

According to it's modelling study, 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, told CNN.

The researchers used cell phone location data from Safe Graph to model the potential spread of Covid-19 within 10 of the largest metropolitan areas in the United States.

The researchers tracked people’s movements to locations such as restaurants, cafes, grocery stores, gyms and hotels, as well as doctor’s offices and places of worship, while looking at the coronavirus counts in their areas.

“On average across metro areas, full-service restaurants, gyms, hotels, cafes, religious organizations, and limited-service restaurants produced the largest predicted increases in infections when reopened,” said the study.

The model also predicted that people living in neighborhoods with the lowest income, based on Census data, were more likely to have been infected -- driven in part by how places in those areas tended to be smaller in size, leading to crowding and increasing the risk of spread.

"Our model predicts that one visit to a grocery store is twice more dangerous for a lower-income individual compared to a higher-income individual," added Leskovec, the author.

However, the study also has drawbacks - it isn't an all-encompassed study. The model is a simulation and the data is based on just 10 metropolitan areas in one country, and doesn't captured other places like prisons, residencies, nursing homes, schools, offices where outbreaks are also common.


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