Mircea Sofonea: "Modeling is just another form of quantitative data analysis, not some kind of divination."
Mircea Sofonea is an epidemiologist at the Infectious Diseases and Vectors: Ecology, Genetics, Evolution, and Control (Mivegec[i]) laboratory. For almost a year now, his field has been in the spotlight, and the Montpellier-based researcher has been in high demand from the media. He looks back on what has been a decidedly unusual year.
How did you get into epidemiology?
After studying biology at the École Normale Supérieure, I defended my thesis in evolutionary epidemiology at the University of Montpellier in 2017. It is a city with exceptional momentum in the life sciences, from population biology to health. Epidemiology, which is the study of health determinants over time and space, is at the crossroads of many disciplines. The epidemiology of infectious diseases in particular requires the involvement of clinicians, microbiologists, public health doctors, but also ecologists, evolutionary biologists, and applied mathematicians. In Montpellier, I found a very favorable environment for developing interdisciplinary approaches.
Has the COVID-19 pandemic changed your work?
The situation very quickly took an unprecedented turn. On March 12, 2020, most of the research carried out by the Theoretical & Experimental Evolution team led by Samuel Alizon at the Mivegec laboratory shifted its focus to COVID-19. Our team was among the first to produce publicly available work and software for France: on April 6, we posted a simulator online that estimated how many people had been infected in order to determine if and when herd immunity would be achieved and when hospital occupancy would peak. We were one of the few French teams to have expertise in modeling the epidemic at the national level, and at the end of April we were contacted bythe Parliamentary Office for the Evaluation of Scientific and Technological Choices (OPECST, chaired by Cédric Villani). However, a scientific discipline must be careful not to take on a monopoly. We contribute to the dissemination of science, but we are not public policy makers, even if many media outlets push us to express ourselves in this way.
You were heavily sought after by the media regarding COVID-19. Were you familiar with this relationship with the press?
At first, the media and journalists were not familiar with epidemiology, and we were contacted mainly through word of mouth for our educational notes on the subject. Then the need for understanding and quantitative projections of the epidemic translated into daily requests, mainly from the media but also from healthcare professionals and even the private sector. We thought this exposure would last a few weeks, but almost a year later and more than 300 interviews, the requests are still coming in, and I have to turn them down because I don't have enough time to keep up with my research in this unprecedented context of scientific production and a full teaching load. I have also observed the effect of taking a break from responding to media requests: the observation shared by other colleagues is that scientific analysis quickly gives way to misleading discourse, which not only undermines public confidence in the scientific community but also weakens the population's understanding of and adherence to health measures.
What do you think of the various, not always consistent, statements that have been made?
Do not use urgency and media hype
to fill the void, and some scientists took advantage of this excitement to assert unproven theories outside their field of expertise. These statements ultimately lost public support. For example, lockdown is not a decision that can be made on a whim, but must be based on quantitative arguments, data, and appropriate scientific analysis.
There have been many articles in the media in which you were interviewed with headlines such as "We must go into lockdown." Do you agree with what you said?
This is one of the difficulties encountered in dealing with the media: often, we find that our words are not reproduced entirely accurately, and the published article does not reflect the conditional tense we used or the rhetorical precautions we took, even though we try to convey a nuanced and balanced view of research, which is exploratory by definition. It is also essential to distinguish between science and research. The former represents a body of knowledge that has been established and accepted as such by a community of specialists, while research is a human activity like any other, with each individual producing it in their own way, from intuition to preliminary results that have not yet reached the level of consensus. Too often, the media confuses the two.
How do you envision your work evolving in the post-COVID era?
I hope that we will once again be able to engage in long-term research and contribute to a transdisciplinary scientific understanding of infectious diseases, as well as to the transmission of this knowledge, in particular by promoting better health education for future generations. More generally, researchers in epidemiology and the evolution of infectious diseases are currently seen as bearers of bad news, even though many of these diseases are preventable and investment in prevention before the emergence and spread of an epidemic is crucial. There is a certain degree of ingratitude in public health: if you predict and anticipate an event, everything is done to prevent it from happening and you are seen as a doomsayer. If you don't predict it and it happens, you haven't done your job properly. It is important to bear in mind that epidemiology answers three questions: understanding the past, describing the present, and informing the future, but not predicting it. Modeling is essentially a form of quantitative data analysis like any other, and not a divinatory practice as observers who forget that behind every interpretation of the figures lies a model, however simplistic and implicit it may be, like to describe it.
Had you ever dealt with other epidemics before COVID-19?
Together with Samuel Alizon and two MEME master's students, we worked on the Ebola epidemic that occurred in West Africa from 2013 to 2016. This epidemic was unprecedented in its scope and duration, so it was important to study its long-term consequences. It is a good example of the interaction between public health and viral evolution. In developed countries, it was believed that antibiotics and vaccines would quickly solve the problem of infectious diseases and that the focus should now be on chronic diseases. The COVID-19 epidemic has proven the opposite.
[i] Mivegec: UM, CNRS, IRD