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Modern Techniques for Modelling Infectious Disease Dynamics

Overview
Overview
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Course dates: 10-12 February 2020

A short course taught by members of the Centre for the Mathematical Modelling of Infectious Diseases.

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 best practices for writing coherent code and using version control.

Course content

Day 1:

  • Introduction to R (optional morning session)
  • Using loops, functions, packages and sourcing in R
  • Best practices in coding
  • Discrete-time deterministic models

Day 2:

  • Ordinary differential equation models, including using deSolve for integration
  • Metapopulation models
  • Simulation, sensitivity and sampling parameter sets, including Latin Hypercube sampling
  • Processing outputs using ggplot2: making graphs and stratifying outputs

Day 3:

  • 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

Teaching methods

The course is taught 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.

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.

Fees

£720 for 3 day course, includes coffee breaks but not lunch or accommodation.

How to apply
How to apply
How to apply - Modern Techniques for Modelling Infectious Diseases Dynamics
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We are no longer accepting applications for 2020.

Please read LSHTM's Admissions policies prior to submitting your application.

Short courses - visas, accommodation, disclaimer
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Visas

The student is responsible for obtaining any visa or other permissions to attend the course, and is encouraged to start the application process as early as possible as obtaining a visa for the UK can sometimes take a long time. The Short Courses team can provide supporting documentation if requested.

Accommodation and meals

A list of hotels located in the vicinity of LSHTM, along with further resources for short term accommodation, can be found on our accommodation pages. Tea and coffee vouchers will be provided during breaks.

Evening meals are not catered for at LSHTM, however there is a large choice of restaurants, cafés and shops nearby.

Important information

Please note:

  • If you have been offered a place on the course you will not be able to register without bringing formal ID (Passport) and without having obtained the correct visa if required.
  • It is essential that you read the current visa requirements for short course students.
  • LSHTM may cancel courses two weeks before the first day of the course if numbers prove insufficient.  In those circumstances, course fees will be refunded.
  • LSHTM cannot accept responsibility for accommodation, travel and other losses incurred as a result of the course being cancelled.