Course dates: 7 - 10 February 2022
This short course is taught by members of the Centre for the Mathematical Modelling of Infectious Diseases, a multidisciplinary grouping of more than 150 epidemiologists, mathematicians, economists, statisticians and clinicians.
Mathematical models are increasingly used to understand the transmission of infectious diseases in populations and to evaluate the potential impact of control programmes in reducing morbidity and mortality. With this short course we aim to bridge the gap between theoretical training in infectious disease modelling, and the specialist technical skills needed for research in this area.
Participants will gain a working knowledge of using R to code dynamic transmission models. They will learn key principles for best practice in model coding including version control. They will learn how to code stochastic and deterministic epidemic models from scratch. They will also learn how to present model output by implementing sensitivity analysis and graphing data, and they will be taught the fundamentals of debugging their models.
- Introduction to R (optional morning session)
- Using loops, functions, packages and sourcing in R
- Best practices in coding
- Discrete-time deterministic models
- Ordinary differential equation models, including using deSolve for integration
- Metapopulation models
- Simulation, sensitivity and sampling parameter sets, including Latin Hypercube sampling
- Processing outputs using ggplot: making graphs and stratifying outputs
- Network models: reading adjacency matrices and simulation of Reed-Frost models
- Stochastic models in discrete time
- Stochastic models in continuous time
- Version control: a hands-on introduction to Git and Github
Who is this course for?
This course is aimed at people who have had some exposure to the theory and use of infectious disease modelling and who would like to start coding their own models using R. Individuals who know some R but do not have experience using R to code infectious disease models will benefit. The course is ideal for those who will be conducting research using infectious disease models in R or who want a deeper understanding of techniques for implementing models.
This short course is particularly useful to PhD students, postdocs, and industry professionals who need to develop and run infectious disease transmission models.4
The course is taught online as a series of hands-on computer practicals in R. A 2-hour introductory session is available for those with no prior experience with R. We will provide some exercises before the course to help participants decide if they need to attend the introductory session.
£600 for a 4 day online course. A Certificate of Attendance will be provided.