This modeling was based on measurements taken at Heathrow airport in London, which is the busiest in Europe and where infections such as influenza A (H1N1) and Covid-19 can easily spread. The researchers used techniques such as air filtration and specific lamps For take measurements and have also used geolocation data mobile phones to track the movements of more than 200,000 people inside the airport between February and August 2017 (source 1). This allowed them to reconstruct the contact networks between these different people and identify areas where contacts were the most intense and or the risk of transmission was the most important. The results of this study have shown that common areas such as bars and restaurants were the most conducive to disease transmission (source 2).

This is because these areas bring travelers and airport employees into contact for long periodsallowing infectious diseases to spread easily. These areas are often designed to optimize logistical efficiency rather than reducing crowds, making them particularly vulnerable to disease transmission. In addition, social distancing is not always possible there.

The authors of this study therefore recommended the implementation of specific prevention measures targeting these high-risk locations, such as the establishment of air filtering, the systematic disinfection of surfaces, the use of Far-UVC lamps to disinfect large surfaces in the presence of living beings and the incentive to wearing of anti-virus mask for travelers and employees of the airport. According to the researchers, these preventive measures could halve the risk of having a secondary case of H1N1 flu or Covid-19 following a first case imported into the airport.

Finally, this modeling method could be used in the future to study any new pathogen not yet characterized and could be generalized to other modes of transportation such as trains, subways and bus stations, as well as other crowded places such as shopping malls and convention centers.