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 and how to code stochastic and deterministic epidemic models from scratch.

The two short courses Modern Techniques in Infectious Disease Modelling and Model Fitting and Inference for Infectious Disease Dynamics are offered back-to-back across two consecutive weeks. While either course can be taken on its own, students who take both courses will benefit from a comprehensive introduction to modern methods in infectious disease transmission modelling.

Course content

• 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
• Network models: reading adjacency matrices and simulation of Reed-Frost models
• Stochastic models in discrete time
• Stochastic models in continuous time

Who is this course for?

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.

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.

Teaching methods

The course is taught face-to-face or online as a series of lectures and hands-on computer practicals in R. Students should have some experience using R, but online introductory material on R, best practices in programming and version control with Git will be made available for those who need a refresher.

Course leaflet (pdf)

Testimonials

"I found this an informative and thrilling course. It has encouraged me to go further into the world of R-programming and my research. I would most certainly recommend it."

"The online format of the course was very good, and it is very useful to have had all sessions recorded to return to in future. The quality of teaching during lectures was very high and the lecturers were all very knowledgeable."

"The materials provided are very comprehensive and will enable me to build infectious disease models in R in future. The breadth of topics covered was overall very good. The lecturers and demonstrators were all fantastic."

"This course was fantastic overall. The overall sequence of topics and the pacing worked well. The alternation between lectures and practicals and the way the difficulty of the practicals gradually increased was very well executed. As someone with a very introductory background in mathematical modelling but a very strong foundation with R, I found that the combination of the lectures and the practicals helped me gain a more robust understanding of how each of these types of models work."

"I feel like the design and delivery of this model were very reflective of LSHTM's effort to promote decolonisation."