The Pasteur Museum is housed in the apartment where Louis Pasteur spent his final seven years and offers a rare behind-the-scenes look at the living and working environment of the world-renowned scientist. Visitors can gain a unique insight into his everyday life alongside his wife and can admire his rich and diverse scientific work.
The Institut Pasteur’s scientific strategy focuses on developing original and innovative topics and promoting interdisciplinary and multidisciplinary cooperation and approaches. The Institut Pasteur teams have access to the technological resources needed to speed up and further improve the quality of their outstanding research.
Ever since the introduction of the world’s first "Technical Microbiology" course in 1889, teaching has been a priority for the Institut Pasteur. The Institut Pasteur has an international reputation for quality teaching that attracts students from all over the world who come to further their training or top up their degree programs.
The mission of the Industrial Partnership team is to detect, promote, assist and protect the inventive activities from research (inventions, know-how and biological materials) conducted at the Institut Pasteur (and in some Institutes of its international network), and transfer there to industrial and/or institutional partners, in order to serve the patient needs and for the benefit of the society, as well as to contribute to sustainability of the Institut Pasteur’s resources.
With international courses, PhD and postdoctoral traineeship, each institute of the Institut Pasteur International Network (RIIP) contributes to the transmission of knowledge with the training of young researchers all around the world. In this context, doctoral and postdoctoral programmes, study and traineeship fellowships are available to scientists. Alongside training, dynamism and attractiveness of RIIP will result in the creation of 4-year group for the young researchers.
The state of the infection at the time of first detection
Abstract: We consider a stochastic model of infection spread, with a general probability distribution of infectious epochs (i.e., not necessarily exponential) and constant, per capita transmission rate and detection rate (medical examination, symptom appearance,...). We have developed a new technique for the analysis of such non-Markovian processes, that allows us to give simple formulae for the (probability of) the state of the infection (number of infectives, time since infection,...) at the first time when an infective is detected. These results have applications for characterizing outbreaks of antibiotic resistant bacteria in the hospital. In particular, we disprove the formerly believed uniformativeness of this kind of data. (Joint work with P. Trapman from Stockholm University).