CIRB - Équipe de recherche

Evolutionary Epidemiology of Infectious Diseases

Epidémiologie évolutive des maladies infectieuses

Principal Investigator: François Blanquart


Understanding the rapid adaptation of infectious pathogens is crucial to design better management policies and anticipate future changes. Adaptation to optimize transmission, resist drugs or escape the host immune system profoundly impacts epidemiological dynamics and the efficacy of stewardship policies.

In our team, we address two important knowledge gaps to understand pathogen adaptation: deciphering the ecological and epidemiological drivers of pathogen adaptation, and detecting adaptation from genomic data.

Example of projects:

Escherichia coli adaptation

E. coli is a commensal of the human gut and an opportunistic pathogen causing infections responsible for more than a million deaths worldwide per year. E. coli has rapidly evolved over the last four decades. From the 1980s, starting from an almost fully sensitive population, multiple antibiotic resistances have emerged and stabilised at an intermediate frequency. Virulence, the propensity to cause infections, may have also evolved. To elucidate the drivers of the evolution of commensal E. coli, we currently develop a prospective cohort of 200 longitudinally followed healthy volunteers in close collaboration with the center for Clinical Investigation of the Bichat hospital.

HIV adaptation

We also aim to unravel the adaptation of HIV-1 group M over decades. HIV is characterized by a very large genetic diversity, but the drivers of adaptation at the epidemiological level have been elusive. We develop various analyses including GWAS and new genomic methods to discover whether virulence evolved in the HIV-1 epidemics in Europe and Sub-Saharan Africa, and what drove this evolution.

SARS-CoV-2 adaptation

Finally, we investigate the evolution of SARS-CoV-2 and its multiple variants of concern over short timescales. We modelled the spread of the Alpha variant in France, developed new methods to infer both the relative transmissibility and mean generation time of emerging variants, and are now working on the characterization of immune escape variants.