Avsnittsöversikt
-
More information may 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. See "Registration and Venue" page for further details.
Lecture times (includes also problem solving, tutorials, computer sessions, ...):
Wednesday June 24: 14.00-15.30, 16.00-17.30
Thursday June 25: 9.00-10.30, 11.00-12.30, 14.00-15.30, 16.00-17.30
Friday June 26: 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