Novel stochastic numerical methods for complex multiscale dynamical systems with applications in microbiology

The opportunistic pathogen bacteria Pseudomonas aeruginosa is a major cause of nosocomial infections and is responsible for dramatic complications in immunocompromised people. A dramatic side effect of the bacteria defense against metals, such as Zinc, is a resistance of the bacteria to antibiotics, as discovered and studied by the group of investigator Perron at UNIGE. Indeed, Zinc is an element commonly present in the environment as a pollutant, in medical devices (catheters) in certain human secretions or during phagocytosis. Understanding this phenomenon with a mathematical model of bacteria behavior in patients is a great challenge, which will help the design of efficient medical treatments and dosages against this pathogen.

Despite multiscale stochastic differential equations naturally arising as mathematical models, their efficient and reliable numerical study remains an open problem and it represents a key target of this project.

Main Applicants

Georg Gottwald, University of Sydney

Gilles Vilmart, University of Geneva