A new study published in Nature modeled the spread of COVID-19 using geolocation data for 98 million people.
The answer to the question “Where does SARS-Cov-2 spread the most?” is crucial both from a health point of view to reinforce precautions at these sites and from an economic point of view to allow the various less vulnerable companies to reopen more quickly. A recent study published in Nature magazine highlights that restaurants, hotels, fitness clubs, and religious institutions are the biggest culprits.
Geolocation data used
The researchers reconstructed the movements of part of the US population using 98 million anonymous tracking data that was collected between March and May 2020. They combined this reconstructed network of interactions with a comparative epidemiological model called SEIR (for Susceptible Exposed Infective Recovered) to assess the dynamics of the epidemic within the collection sites. The results suggest that restaurants, sports halls, cafes, hotels, and religious institutions are the places that most contribute to the epidemic dynamics.
Therefore, these sites should be subject to increased surveillance, in order to prevent the epidemic from starting again or getting worst. Ideally, their maximum capacity of use should be greatly reduced.
Scientists point out that their model has limitations, particularly because it does not take into account all types of populations or all places that could be considered vulnerable. Nor does this type of epidemiological model perfectly reflect the complex reality of disease transmission. However, it is based on the rate of reproduction of the virus. It is therefore able to identify the places that contribute most to its increase.
Additional demographic data also show that people with a lower socio-economic level have a higher rate of infection. They used riskier places and their freedom of movement was less restricted, certainly because they could not work from home. The authors urge policymakers to use their findings as a guide when planning for ways to slow down the pandemic.