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Whenever people congregate indoors, the likelihood of infection increases. Dwell time, ventilation, use or not of masks, conversation in a loud or low voice are the variables that most affect transmission via aerosol. Our interactive graphic shows how coronavirus spreads in the air
After days of uncertainty about how Christmas 2020 would have been, the latest government decree recommends spending the holidays with partners or at least inviting only a couple of people outside the family (those under 14 years old are not counted). Therefore, there are no large gatherings or parties. This year the celebrations will be decidedly more sober and on a smaller scale. The virus spreads much more easily indoors and with poor ventilation, and private homes in the dead of winter are the ideal place for the coronavirus to spread. When you are partying, you tend to speak out loud and the mask, even with good will, is not always worn. Between a chat and a glass of sparkling wine it is easy for attention to fall. So what could happen if multiple families came together under the same roof to toast as has always been done?
Suppose a group of 14 family members spends five hours together in a medium-sized, 60-square-meter living room, talking loudly, opening gifts, eating, and drinking. Hardly, as mentioned, in such a context everyone will always wear a mask. Windows will hardly stay wide open in the dead of winter. What if a person in the group unknowingly had coronavirus? How many more could it infect?
It is impossible to predict with certainty whether an infected person will transmit the virus to another person. However, it is possible to estimate the risk of this happening.
In the case just mentioned, according to the calculations of the statistical model used, an average of 3 family members would be infected if an infected person actually stayed in the room. The individual risk of contracting the infection would be very high: more than 23%. In that room, already with a meeting of only three people, we would have a value of Rt> 1
The risk would be slightly reduced by ventilating the rooms with the windows open for at least ten minutes every hour (2 infected relatives). 1.
However, it would be enough to speak in a low voice (almost like a whisper) to drastically reduce the risk, or to always keep the windows open or to always wear masks: but these are all unlikely situations in a festive context.
The model underlying the interactive graph is an AIRC (Airborne Infection Risk Calculator) tool and was developed by the University of Cassino and the Queensland University of Technology (Australia) under the direction of Professor Giorgio Buonanno. The researchers developed a theoretical model to estimate the emission of viral load of asymptomatic subjects and the consequent probability of contagion in different settings, with the possibility of introducing different variables such as the use of the mask, ventilation, residence time or the type of conversation. The two assumptions underlying the model are that there is an infected person and a minimum distance of one meter between people. The latter to minimize contagion at short distances due to both the droplets (larger particles) that we emit when coughing, sneezing, talking or singing but which, precisely because they are larger, fall to the ground by gravity, both aerosols, tiny invisible droplets that, floating in the air for a long time, however, can reach distances greater than a few meters.
If an asymptomatic positive relative enters the house, unfortunately others are likely to become infected and it is not possible to know how the disease will progress. The number expressed by the model is the statistically most probable value: things could also be much worse (up to four times the average number of infections) or much better (no contagion). The more people we invite, the greater the risk of a potentially contagious person being present among the guests, but once the individual risk of aerosol infection has entered, it will be the same for everyone.
The most advisable recommendation is to spend Christmas in your own family “bubble”, with your partners without inviting relatives who have not seen each other for a long time and who do not know if they have been exposed to risky contacts. And even within their own family, each individual member should avoid snacks, lunches with peers, and any kind of socializing in the days leading up to the holidays. If two families want to meet, the visit should be based on trust: everyone should avoid social activities in the days leading up to the meeting: reliability is essential. Someone may decide to do a rapid antigenic swab, but it must be clear that a negative result cannot give absolute certainty: much depends on the reliability of the tests and when it is performed. If you want to exchange gifts between friends, it is better to do it outdoors: perhaps in the park or sitting on the terrace of a bar: the outdoor spray is dispersed and the risk of contagion is very limited compared to closed environments.
Info:
The model estimates the statistically expected value of the individual risk of airborne infection. A minimum distance between people of at least one meter is assumed to ignore close-range contagion from aerosols and droplets.
Method and data:
The theoretical model underlying the AIRC (Airborne Infection Risk Calculator) tool was developed by a research group from the University of Cassino and Southern Lazio. AIRC has turned the model into a practical tool.
The AIRC tool calculations are based on studies by the University of Cassino and the Queensland University of Technology (Australia), conducted under the direction of prof. Giorgio Buonanno (Buonanno et al. 2020. Estimation of viral emission in air: SARS-CoV-2 quantum emission rate for infection risk assessment Environment International (https://www.sciencedirect.com/science/ article / pii / S0160412020312800; Buonanno et al., 2020. Environmental International (https://pubmed.ncbi.nlm.nih.gov/32927282/. Researchers developed a theoretical model to estimate viral load emission from asymptomatic and the consequent probability of infection in different scenarios The main objective of the tool is to show how changing parameters, for example, ventilating a room or wearing a mask, can reduce the individual risk of infection.
