restaurants, hotels and sports halls are said to be the main vectors for the transmission of the virus

A new study published in Nature modeled the spread of Covid-19 using geolocation data from 98 million people.

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[EN VIDÉO] In video and UV light: this is how the corona virus spreads in a restaurant
A video jointly produced by a group of researchers and the Japanese media NHK News sheds light on the spread of the coronavirus in a restaurant. Using a UV-A lamp, they show how the virus (illustrated by fluorescent lotion) moves from a single individual to an entire group during a meal.

Answer the following question “Qhat are the places where the SARS-CoV-2 spread the most? ” is critical, both from a health point of view to strengthen precautionary measures in these places, and from an economic point of view to speed up the reopening of the various less risky businesses. A recent study published in the journal Nature indicates that high risk places are restaurants, hotels, gyms and religious institutions.

98 million geolocation data used

The researchers reconstructed the movements of a segment of the US population using 98 million anonymous geolocation data collected between March and May 2020. They linked this reconstructed network of interactions to a compartmental epidemiological model called Seir (for Susceptible-exposed-infectious-deleted or susceptible-exposed-infectious-eliminated) to the dynamics ofepidemic within assembly areas. The results suggest that restaurants, sports halls, cafes, hotels and religious institutions are the places that contribute most to the dynamics of the epidemic.

These areas should therefore be under stricter supervision when the second incarceration will end to prevent a resurgence of the epidemic. Ideally, their maximum occupancy rate should be greatly reduced.

The limits of the study

Scientists point out that their model has limitations, in particular because it does not take into account all population groups or all places believed to be at risk. Also, this type of epidemiological model does not perfectly reflect the complex reality of the transmission of the disease. Nevertheless, it is based on the reproduction rate of the virus. Therefore, he can indicate the places that contribute most to its increase.

Additional demographics also show that people with a lower socio-economic level have a higher infection rate. Their risk site frequency was higher and their movements less restricted, especially since they couldn’t to work from home. The authors call on political decision-makers to use their results as guides in managing deconfinement.

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