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This two-week course provides a thorough introduction to mathematical modeling of infectious diseases for students and professionals in science, medicine and public health.
A Master or BSc degree is required. Basic knowledge of algebra (matrices), calculus (derivatives) and probabilities is recommended. Notes covering these topics at the level needed for the class are avaliable for download : square matrices (PDF - 75 Ko), derivatives (PDF - 90 Ko).
Lectures alternate with modeling case studies from the scientific literature and computing exercises. Special attention is devoted to developing compartmental models within either a deterministic or stochastic framework. The class also covers models of disease transmission networks based on homogeneous branching processes. More sophisticated models of transmission networks embedded within complex networks of social contacts are discussed as well. Uncertainty and sensitivity analyses of modeling output are explained and illustrated. The notion of the basic reproduction ratio R0 is introduced for models of various types. Methods to calculate R0 from epidemiological data and the impact of control measures on R0 are discussed.
The program of the course organized the previous year can be downloaded for more detailed information on the general frame of the course; some topics and practical works may change from year to year.
All complete applications will be evaluated by the teaching committee.
Members of the teaching committee :
P.-Y. Boëlle (Université P. et M. Curie),
R. Breban (Institut Pasteur),
E. Coeffier (Institut Pasteur),
M. Sala (Institut Pasteur),
H. Waxin (Institut Pasteur),
V. Ponticelli (Institut Pasteur).
|Title of the course||Modeling of infectious diseases|
Université Pierre et Marie Curie
Emerging disease epidemiology
|Dates||April 18 to April 29, 2016|
|Closing date for application||January 1, 2016|
Institut Pasteur Diploma
ECTS for students registered in the Mastere in Public health from the Pasteur/ Cnam school of public health (Pasteur-Cnam).
The course is validated as a "module d'école doctorale" for students registered at partner universities.