As part of a study published in the journal Nature, researchers analyzed the movements of 98 million Americans during the first epidemic wave. The idea:to determine the places of frequentation where there is the greatest risk of contracting Covid-19.
The new coronavirus has been spreading around the world for almost a year, while a second winter wave is already hitting several countries. The most affected country remains the United States, with more than ten million covid cases recorded and more than 240,000 deaths attributed to the disease. For its part, France today records nearly two million cases and more than 40,000 deaths.
So far, one of the biggest challenges has been determining which places qualify as "super-contaminants". In other words, these are places where the risk of catching Covid-19 (and therefore of then spreading it around you) is considerably higher than elsewhere. Understanding this information could then allow us to fight the pandemic more effectively .
With this in mind, researchers at Stanford University (USA) used the anonymized mobile data of 98 million people to analyze their movements during the first epidemic wave between March and May 2020. These data were provided by SafeGraph. This company aggregates location information from mobile apps to determine the public places visited each day and the duration of each visit.
The researchers then focused on ten of the largest metropolitan areas in the United States, including New York, San Francisco and Los Angeles, and fed the data to an epidemiological model. In this way, they were able to assess the dynamics of the epidemic within the gathering places.
The results indicate that restaurants, cafes, gyms, hotels and religious establishments are the places that contribute most strongly to the spread of the pandemic.
It is also possible that this scientific reality has recently guided the policy of the French government. If the reopening of shops could be envisaged in early December, this will not be the case for other places open to the public "where the risks of contamination are by nature higher, such as bars, restaurants and gyms "said Prime Minister Jean Castex on Thursday.
Combined with demographic information, this data also allowed to explain why people living in poor neighborhoods are more likely to contract Covid-19. Women are less likely to be able to work from home, study finds and the stores they usually visit tend to be more crowded . Finally, the data suggests that these people also tend to stay longer in these stores than shoppers in high-income areas.
Note that the researchers recognize some limitations to their study. This is because the dataset does not cover all populations or suggest all locations where the virus could be spreading.
