SCIENCE – Started in early June, we can say this Tuesday, July 26 that the 7th wave of Covid-19 in France has reached son pic. On the side of positive cases such as hospitalizations, the indicators are down, as you can see in the graphic below.
Good news (if the trend continues), because this peak related to BA.5 variant just equaled the one linked to BA.2, far from the first “Omicron wave”, caused by BA.1. Good news too because, even if the situation in Portugal and South Africa made it possible not to be too alarmed, it was the first wave for which the Scientific Council (and therefore the government) had no modeling on which to lean on.
And for the moment, the Institut Pasteur does not have a model either for the future waves which will undoubtedly arrive as soon as the summer is over and our immunity will have slowly decreased.
This did not prevent the Scientific Council, in its last opinion issued on July 19 and detailed in a press conference, to work on three scenarios for the fall. But these trajectories are very generic: a return of the existing variants, a descendant variant of Omicron or, worse, a very different and possibly much more dangerous variant.
Models become too complex
But why does the Scientific Council no longer have projections allowing it to anticipate? “This BA.5 wave was the first where we did not have a model, because over the past two years we started with simple models, which gradually became more complex to integrate the impact on the epidemic of variants , vaccines, as well as the decline in immunity”, explains Simon Cauchemez, modeller at the Institut Pasteur and member of the Scientific Council. “These overly complex models are today uncertain”.
To make projections on the Covid-19 curves (more details in this interview with Simon Cauchemez from 2020), hypotheses are formulated on the virus (its contagiousness, duration of infection, severity, etc.), and on the target population (the number of contaminable people, the number of contacts at risk, age, etc.).
At the start of the epidemic, things were (unfortunately) simple: almost anyone might catch Covid-19. Even following the first wave which affected only 5% of the population. There were only two ways to reach the peak. Either let the virus spread until there are not enough people to be infected (thus leaving tens or even hundreds of thousands of people to die). Either take measures limiting our contacts at risk in order to break the chains of transmission of the coronavirus.
But since then, things have evolved in many ways. First, thanks to vaccines, which have given us very significant protection once morest serious forms and, in a lighter and more ephemeral way, once morest infection. There were also the variants to be integrated into the models. Did this new set of mutations make the virus more contagious? Less virulent? Able to escape the vaccine? To a previous infection?
“We know little regarding cross-immunity between variants”
All these parameters made the projections more complex, but the modellers still saw things clearly. “Until then, you might simplify by putting people in boxes. People vaccinated with one dose, two doses, a booster, those infected with natural immunity”, explains Samuel Alizon, Research Director at the CNRS, specialist in the modeling of infectious diseases. “But the Omicron waves blew up the categories.”
With the arrival of the highly contagious Omicron variant, most Western countries, widely vaccinated, tired of repeated confinements and unable to develop non-coercive braking measures, chose to let the epidemic slip away. By doing this, we accepted a very large wave of cases, of hospitalization, but with a much lower toll than for the previous variants on an unvaccinated population. There was also the vague and derisory hope that this wave would be the lastcausing “herd immunity”, preventing the coronavirus from circulating.
But reality has, once once more, very quickly caught up with the slim hopes. This natural immunity, as we already knew, does not last forever. It decreases and disappears over time (even if that once morest severe forms seems to stabilize following three doses or three infections).
And that’s a big part of the problem. “While vaccine immunity is easy to control and monitor, natural immunity is less known,” explains Samuel Alizon. Especially with the multiplication of variants and situations. In which box to put a vaccinated person, contaminated 3 months later, then who had a recall in January? How does his immunity compare to someone infected in 2020, vaccinated 2 times in 2021, then re-infected with BA.1 in January 2022? Or by BA.2 in March?
“We know little regarding cross-immunity between variants, for example we have seen that BA.5 can circumvent part of the immunity caused by an infection with BA.1”, illustrates Samuel Alizon. All these boxes therefore become very difficult to manage so that an epidemiological model can offer precise projections without risking going completely astray.
Simplify without distorting
However, it is always necessary to anticipate as much as possible. “The pandemic is not over. We are facing a virus which has a genetic evolution that is difficult to predict”, warned Jean-François Delfraissy, the president of the Scientific Council, as a preamble to presenting his latest opinion.
But can we even adapt the calculations to this new situation? “Today’s models are too complex and therefore unstable. A compromise must be found with more parsimonious models, taking into account these different immunity profiles. It’s a work in progress”, explains Simon Cauchemez.
In a article prepublished on June 15, Samuel Alizon and two colleagues tested a new concept in an attempt to take into account the decline in immunity. “The idea is to include in the model how long individuals have been in a particular state, for example how long ago their last dose of vaccine was,” he explains. “One of the results is that even in the absence of a new variant, large annual waves can be observed linked to winter and the (limited) decrease in immunity”.
Surprisingly, the scenarios where the whole population is vaccinated at the same time each fall lead to a more pronounced peak than if a booster is offered only to the elderly and frail (even if the more one vaccinates, the less there is of deceased). The reason put forward by the researchers: by vaccinating everyone at the same time, the level of immunity is synchronized. Clearly, we suddenly have many people who once more become susceptible to infection. Another lesson from the study, notes the researcher: “In addition, so-called non-pharmaceutical interventions (improving air quality, wearing a mask, etc.) can have an effectiveness comparable to annual vaccination campaigns. In the end, the best effectiveness is obtained by combining these interventions and vaccine boosters.”
Obviously, this type of general projection has limits. “The longer we project ourselves into the long term, the more qualitative the model becomes”, specifies Samuel Alizon. However, what the health authorities want are “quantitative” projections. To put it simply, let’s say that a qualitative model tries to imagine the general trend of the curve of the Covid-19 in the long term according to various assumptions. The quantitative model will try to anticipate the number of people infected or hospitalized. “But as soon as you go beyond the month, these quantitative models become tricky given the many unknowns, and you still have to explore different scenarios”.
To conclude, we must remember that we are obviously not powerless in monitoring this pandemic. “We will have to be vigilant with regard to the next emergences, because it is very difficult to say the dates and the magnitude of the peaks. Today, we are observing what is happening with our neighbors and it is very instructive”, recalled Arnaud Fontanet, epidemiologist and member of the Scientific Council, during the press conference. However, the future dominant variant must not emerge in France. “If we are on the front line, it will be difficult, we will have to keep in mind the possibility of a slightly more disruptive emergence”.
See also on Le HuffPost: Why vaccination of people over 60 is not superfluous
