Lee“Heard immunity” occurs when enough people are vaccinated against the virus in a given population that the virus cannot spread rapidly. The method of calculating it is very simple, but suppose that it is the same for this figure as it is for others: it has uses, but it is also necessary to understand its limitations.

Each infectious disease spreads at a unique “rate” – some germs are highly contagious, others less so. Epidemiologists measure it with an indicator that they are poetically called R0 or “base fertility rate”. This is the number of people a patient will infect on average, in a population where no one is immunized and where no action is taken to slow the spread. For example, measles R0, a highly contagious disease, is about 15, meaning that each person who has measles will infect an average of 15 other people (again, if no one has antibodies and if nothing else is done). Influenza, by comparison, is much less transmitted, with an R0 of about 1.5.

The well-known “threshold” of mass immunity is the percentage of people who have to be immunized to fall below 1 of R – meaning that the disease naturally loses ground. For infectious viruses such as measles, almost all require vaccination to achieve it. The mathematical formula to calculate it is: 1 – (1 / R0), so for measles, we get: 1 – (1/15) = 14/15, or 93%. For the flu, it is clearly very low: 1 – (1 / 1.5) = 33%.

What about COVID-19? “This has changed over time due to variations,” explains Dr. Alex Carignon, an infectious disease specialist and researcher at Sherbrooke University. Before the variants, we worked with an R0 of around 2.5, which gave a collective immunity limit of 60% [ndlr : 1 – (1 / 2,5) = 0,6, donc 60 %], But the versions that are airing now are more contagious, with around 4K R0. So now we are talking about more than 75%. [ndlr : 1 – (1 / 4) = 0,75]. »

However, warns Dr. Carrigan, it is an indicator “that is still very theoretical and very simple. It gives a general idea and it helps to establish objectives, but there are certainly a lot of things that Does not take into consideration ”.
For example, this limit essentially considers only the transmission of R0, or COVID-19, regardless of severity. However, vaccines do not appear to be as effective in preventing infection as they are in preventing disease and complications.

According to the American Public Health (CDC) website, some works suggest about 90% effectiveness in preventing the disease, but perhaps only for 55–80% of transmission, one would be inclined to conclude that ‘to get vaccinated Number of ones should be. And increased. Except that if the disease rarely causes more hospitalizations and deaths, it may not be as desirable as before to reduce R0 to 1, as the results are now lower – but for the “threshold”. He does not say anything alone.

Also, the figure assumes that social interactions are the same for all, which is clearly not the case. For example, young adults have more social contact than older people. From one culture to another, there is not the same level of interplay between generations. The economic fabric of a country can affect the amount and type of contact people have in the workplace – for example, factory work is thought to be associated with several COVID-19 outbreaks across the country. World, but some economies are more industrial than others. And so on

In 2017, a trio of researchers from Singapore and the UK published in the scholarly journal PLOS – Computational Biology A model taking into account many of these factors to get an idea of ​​what a “transition network” might look like in 152 countries. And in 2020, other researchers applied it to COVID-19, which gave them R0s, which varied wildly from country to country. In some places the fertility rate was naturally around 1 while in other places it could be higher than 4.

Which shows that, as Dr. Carrigan says, this “collective immunity limit” is a very crude tool – regardless of its uses.