Learning outcomes

This course aims to bring together different skills related to the mathematical modeling of infectious diseases, and in particular covid-19.

Goals

The objective for the student would be to acquire a certain autonomy regarding the design and construction of a mathematical model on infectious diseases, using machine learning techniques applied to real data.

Content

• General introduction to epidemiology
• Simple SIR-like compartmental mathematical models
• Complex age-structured compartmental models
• Blackbox optimisation and MCMC
• Scenarios and interpretation of results

Teaching methods

Magistral lectures (4H to 6h/week) during the first weeks. Then, the student will have to implement their own model in a free language, under the supervision of an assistant.
 

Assessment method

The exam will consist of a presentation of the work carried out regarding the implementation of the model and the results obtained.
 

Sources, references and any support material

Slides on webcampus.
Handbook of Infectious Disease Data Analysis, Leonhard Held, Niel Hens, Philip O'Neill, Jacco Wallinga, Chapman & Hall/CRC handbooks of modern statistical methods, CRC Press, 2019

Language of instruction

French