Topic outline

  • Infectious disease data analysis (June 26-28)

    This course page is not finalized: more information will appear later


    Course Instructors

    Simon Cauchemez, Institut Pasteur

    Marc Baguelin, Imperial College

    Course contents:

    This course provides an in-depth introduction to methods used for the analysis and modelling of infectious disease data, aiming to estimate key transmission parameters and characterize epidemic dynamics. During the course, the students will learn:

    - General principles of Bayesian inference in the context of infectious disease data analysis

    - Methods for the calibration of transmission models to epidemic time series

    - Methods to reconstruct the history of pathogen circulation from serological data

    - Bayesian data augmentation methods to address missing data in outbreak investigations

    - Methods for the estimation of the reproduction number R from various types of data

    Students will actively apply these concepts and methods during hands-on practical sessions, using recent R packages dedicated to the field. Interactive discussions of scientific articles, fostering a deeper understanding of the material, will be integrated into the course. The module aims to provide a robust foundation for further exploration of specific topics of interest.


    Time and Place

    All lectures take place at Stockholm University in Campus Albano, house 1, level 2, room ??. See Registration and Venue for further details.

    Lecture times (includes also problem solving, tutorials, computer sessions, ...): 

    Wednesday June 26: 14.00-15.30, 16.00-17.30

    Thursday June 27: 9.00-10.30, 11.00-12.30, 14.00-15.30, 16.00-17.30

    Friday June 28: 9.00-10.30, 11.00-12.30, 14.00-15.30, 16.00-17.30

    General prerequisites

    It is expected that course participants have basic knowledge of statistics and mathematics and rudimentary knowledge of infectious disease epidemiology. It is also expected that participants have basic computer software knowledge and preferably are familiar with the software R. 

    IMPORTANT: All participants are expected to bring a laptop with R installed on it.

    Additional prerequisites for this course

     

    Relevant literature


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  • Sources for R

    Instructions for installing R, introduction to R?

  • Wednesday, June 26

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  • Thursday, June 27

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  • Friday, June 28

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