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Introduction to Epidemic Modelling

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About Course

Mathematical models can be used to represent infection spread in different populations. This course is for those wishing to learn the basics of ordinary differential equation epidemic models and how to implement these models in R.

Starting from the simple Susceptible-Infectious model, at the end of this course you will understand how to add additional complexities such as demography and make model predictions using R. Learn with worked examples, exercises, quizzes and tutor support – use the Q&A box to ask questions.

This course is CPD certified!

What Will You Learn?

  • What assumptions different epidemic models make about infection
  • How to read and write ordinary differential equations for epidemics
  • How to implement ODE models in R
  • The concept of the basic reproduction number

About the instructor

These courses aim to equip you with the confidence to apply skills in mathematical modelling and data analytics in high-quality research, based on my experience working as an infectious disease modeller at the Big Data Institute University of Oxford, London School of Hygiene and Tropical Medicine (LSHTM) and the University of Warwick. I have taught mathematical modelling, statistics and R programming to audiences ranging from undergraduate students to professionals. I have designed and led courses internationally (University of Malaya and Federal University of Bahia, Brazil) and in the UK (University of Leeds, Warwick, LSHTM). Prior to this, I completed a doctorate in mathematical modelling of infectious disease at the University of Liverpool, following a Master’s degree in applied statistics from the University of Lancaster.

Course Curriculum

What are mathematical models?

Epidemic models
Formulating the SI and SIR models from assumptions to equations

  • SI model
  • SI model II
  • SI model
  • SIR model
  • SIR model

Solving models in R
How to use the deSolve package to solve ODE models in R

  • SI model in R
  • SIR model in R
  • SIR model code
  • SIR code
  • Quiz answers

Predictions and assumptions
How do model assumptions change model behaviour

  • Frequency or density dependence
  • Examples in R
  • Summary and other assumptions

The basic reproduction number
Learn about R0, effective reproduction numbers and herd immunity thresholds

  • Introduction
  • The SIR model
  • Frequency and density dependent transmission
  • Effective reproduction number
  • Herd immunity threshold
  • The basic reproduction number

Including demographic processes
How to add demographic processes to models and the impact on model behaviour

  • SIR model with demography
  • Equilibrium states
  • Importance of demographic processes
  • SIR model with demography

Test your understanding
Check your understanding of model equations and model code

  • Understanding equations
  • Solution – equations
  • Understanding code
  • Understanding code
  • Solution – code

Course feedback
Help to improve the course with your feedback

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  • Review

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4 months ago
like the pictorial model description