This course covers approaches for modelling treatment of infectious disease, as well as for modelling vaccination. 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. It 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.
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- 5 stars75%
- 4 stars18.75%
- 3 stars2.08%
- 2 stars4.16%
来自INTERVENTIONS AND CALIBRATION的热门评论
A great learning experience, have to struggle a lot for the quiz, But in the end it helps to get better understanding of the concept and practice.
Stuck in last quiz for many hours, dig in many forums. Finally learn in-depth how and why model structure be like that. 5/5 would loss in thought again.
There are not lecture notes provided in this course.
Good content but some exercises and final quiz are designed poorly that sometimes don't even test your learning.
关于 Infectious Disease Modelling 专项课程
Mathematical modelling is increasingly being used to support public health decision-making in the control of infectious diseases. This specialisation aims to introduce some fundamental concepts of mathematical modelling with all modelling conducted in the programming language R - a widely used application today.