Interventions and Calibration Coursera

Overview

Building on the SIR model, you will learn how to incorporate additional compartments to represent the effects of interventions, such the effect of vaccination in reducing susceptibility. You will learn about ‘leaky’ vaccines and how to model them, as well as different types of vaccine and treatment effects. 

The Interventions and Calibration course offered by Coursera in partnership with Imperial College London is important to consider basic relationships between models and data, so, using the basic SIR model you have developed in course 1, you will calibrate this model to epidemic data. Performing such a calibration by hand will help you gain an understanding of how model parameters can be adjusted in order to capture real-world data. 

Lastly in this course, you will learn about two simple approaches to computer-based model calibration - the least-squares approach and the maximum-likelihood approach; you will perform model calibrations under each of these approaches in R.

What you will learn

• Identify the relationship between models and real-world epidemiological data 
• Incorporate treatment or vaccination into an SIR model, accounting for imperfect efficacy, and for different mechanisms of action
• Perform simple calibrations of an SIR model against time-series data, selecting parameters to maximise the fit of the model to the data 
• Recognise two simple approaches to computer-based model calibration and perform model calibrations under each of these approaches in R.