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(2 Ratings)

Introduction to Epidemic Modelling

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About Course

Mathematical models can be used to represent infection spread in different populations, but how do we write the equations that make up these models? What parameters are included in the equations? What assumptions are made about how infections occur?

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!

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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

Course Content

Introduction
What are mathematical models?

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

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

Predictions and assumptions
How do model assumptions change model behaviour

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

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

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

Course feedback
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Student Ratings & Reviews

5.0
Total 2 Ratings
5
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4
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1
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L
4 months ago
The course was very useful for my career and good training with R.
PG
9 months ago
like the pictorial model description