Mircea Sofonea: “Modeling is simply another form of quantitative data analysis, not a form of divination.”
Mircea Sofonea is an epidemiologist at the Infectious Diseases and Vectors: Ecology, Genetics, Evolution, and Control (Mivegec[i]) laboratory. For nearly 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 certainly been an unusual year.
How did you get into epidemiology?
After studying biology at the École normale supérieure, I defended my dissertation in evolutionary epidemiology at the University of Montpellier in 2017. It is a city with an exceptional vibrancy in the life sciences, ranging from population biology to public health. And epidemiology, which is the study of health determinants over time and space, lies at the intersection of many disciplines. The epidemiology of infectious diseases, in particular, requires the involvement of clinicians, microbiologists, and public health physicians, as well as ecologists, evolutionary biologists, and applied mathematicians… In Montpellier, I found a very supportive environment for developing interdisciplinary approaches.
Has the COVID-19 pandemic changed the way you work?
The situation took an unprecedented turn very quickly; on March 12, 2020, the bulk of the research conducted by the Theoretical & Experimental Evolution team led by Samuel Alizon at the Mivegec laboratory shifted to focus on COVID-19. Our team was among the first to publicly release research and software for France: on April 6, we launched an online simulator to estimate 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 thus one of the few French teams to have applied expertise in modeling the epidemic at the national level, and by 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 guard against assuming a monopoly; we contribute to the dissemination of science but we are not prescribers of public policy, even if many media outlets push us to speak in that vein.
Speaking of which, you’ve been in high demand from the media regarding COVID-19—were you familiar with this kind of interaction with the press?
At first, the media and journalists weren’t familiar with epidemiology, and we were mainly contacted through word of mouth regarding our educational materials on the subject. Then the need for understanding and quantitative projections of the epidemic led to daily requests, primarily from the media but also from healthcare professionals and even the private sector. We thought this exposure would last a few weeks, but nearly a year later and after more than 300 interviews, the requests show no sign of slowing down, and I have to turn them down due to a lack of time to maintain my research activities in an unprecedented scientific landscape, as well as 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 narratives, which not only erode public trust in the scientific community but also weaken the public’s understanding of and support for public health measures.
What do you think of the various statements—which haven’t always been consistent—that we’ve heard?
We must not exploit the sense of urgency or the media hype
to fill the void, and some scientists took advantage of this frenzy to assert unproven claims outside their area of expertise. Such statements ultimately lost the support of the public. For example, a lockdown is not a decision to be made on a whim, but one that must be based on quantitative arguments, data, and appropriate scientific analysis.
We’ve seen a lot of media articles featuring interviews with you under headlines like“We need to lock down”—do you recognize yourself in those quotes?
This is one of the challenges encountered when dealing with the media: we often find that our words are not reproduced entirely accurately, and the published article omits both the conditional tense we used and our rhetorical caveats—even though we strive to convey a nuanced and balanced perspective on research, which is, by definition, exploratory. It is, in fact, crucial to distinguish between science and research. The former represents a body of knowledge that is established and accepted as such by a specialist community, whereas research is a human activity like any other, with a unique approach to conducting it for each individual—ranging from intuition to preliminary results, but not yet at the level of a consensus-based fact. All too often, the media confuses these two concepts.
How do you envision your work evolving in the post-COVID era?
I hope we can once again commit to long-term research and contribute to a transdisciplinary scientific understanding of infectious diseases, as well as to the dissemination 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 investing in prevention before an epidemic emerges and spreads is crucial. There is a certain ingratitude in public health: if you predict and anticipate an event, everything is done to prevent it from happening, and you are labeled a doomsayer. If you do not foresee it and it happens, you have failed in your job. It is important to keep in mind that epidemiology answers three questions: understanding the past, describing the present, and shedding light on the future—but not predicting it. Modeling is essentially just another form of quantitative data analysis, not a form of divination as some observers like to label it—observers who forget that behind every interpretation of the numbers lies a model, however simplistic and implicit it may be.
Had you ever dealt with other epidemics before COVID-19?
Together with Samuel Alizon and two interns from the MEME master’s program, we studied the Ebola epidemic that occurred in West Africa from 2013 to 2016. This outbreak was unprecedented in its scale and duration, making it important to examine its long-term consequences. It serves as 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 shift to chronic diseases. The COVID-19 pandemic has proven us wrong.
[i] Mivegec: UM, CNRS, IRD