Mathematical Modelling in Epidemiology

Course content

Epidemiology may be thought of as the study of patterns of health and disease in populations. Mathematical modelling is one of the cornerstones of modern epidemiology, and in this course we will cover various analytic techniques used to interrogate and understand epidemics. Particular topics may include: deterministic and stochastic modelling; simulation and analysis; transmission dynamics; agent-based models; compartmental models; network models; vector-based models.

Education

MSc Programme in Statistics
 

 

Learning outcome

 

KNOWLEDGE

  1. Knowledge of modelling, simulation and analysis techniques used in epidemiology
  2.  

SKILLS

  1. Ability to create appropriate models to analyse epidemic behaviour
  2. Ability to undertake critical analysis and validation of models
  3. Ability to interpret the output of models
  4. Ability to undertake self-directed research for mathematical modelling approaches

 

COMPETENCES

  1. Create, parameterise, fit, evaluate, and interpret the results of models for understanding population disease dynamics

 

Lectures and exercise classes

See Absalon for a list of course literature

Written
Individual
Continuous feedback during the course of the semester
ECTS
7,5 ECTS
Type of assessment
Written examination, 4 hrs. under invigilation
Supervised written exam of 4hrs, including the use of computers for modelling
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
One internal examiner
Criteria for exam assessment

To achieve a 12, students must convincingly demonstrate that they have attained the knowledge, skills, and competences described here. 

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 35
  • Preparation
  • 107
  • Practical exercises
  • 35
  • Project work
  • 25
  • Exam
  • 4
  • English
  • 206