The World Health Organization’s recent statement that Covid-19 may soon be behind us (“I think we’re getting to the point where we can look at Covid-19 the same way we look at seasonal flu” , said Friday, March 17, the head of WHO’s emergency programs, Michael Ryan) should not make us forget that, at any time, another zoonosis can arise, allowing the irruption in the human population of a animal virus to which our immune systems are not accustomed, and likely to kill en masse – let us recall that, according to a last count, the SARS-CoV-2 had killed at the beginning of the year more than 6.6 million people in the world.
High density spaces
It is in this perspective that we must resituate the work recently published by a Franco-Spanish team in “Nature Communications” . These researchers from the Pierre Louis Institute of Epidemiology and Public Health and the Spanish institute CSIC-IFISC have developed a mathematical model allowing them to identify, within areas with a high population density such as airports or stations (designed to optimize logistical efficiency, not to reduce crowds), the areas most at risk from the point of view of the transmission of infectious diseases.
In their article, the scientists studied Heathrow airport in London, one of the busiest in Europe. Using anonymized data concerning the movement within the airport of more than 200,000 people and coming from the geolocation of mobile phones, their model allowed them to visualize the journeys of individuals with a spatial visualization of 10 meters, reconstruct the networks of contacts between them and, thus, detect the places where these contacts were the most intense, with a greater risk of contamination. The spread inside the airport of two infectious diseases, the H1N1 flu and Covid-19, might then be concretely analyzed, by integrating data from epidemiology into the mathematical model.
Target areas at risk
This work showed that the areas most at risk were bars and restaurants, places that put travelers and airport workers in contact for long periods of time. Modeling then established that by targeting these high-risk areas – which are only 2% of Heathrow’s accessible area – with spatial immunization measures, such as air filtering, the systematic disinfection of surfaces or the use of Far-UVC lamps, it was possible to reduce by 50% the risk of having a secondary case of H1N1 following a first case imported into the airport, and by 40% for the Covid-19.
“Well targeted and implemented in places identified as most at risk, these measures would make it possible to contain and/or delay the spread of infectious agents to the rest of the world via airports and other centers of affluence”, explains Mattia Mazzoli, Inserm researcher and first author of the study. If this first study only concerns Heathrow airport and the two diseases mentioned, the underlying mathematical model can be used to study other strategic centers and other pathogens. One more weapon in our fight once morest the hypothetical “Big One”.
