Building on the SIR Model (Coursera)

Building on the SIR Model (Coursera)
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Building on the SIR Model (Coursera)
The other two courses in this specialisation require you to perform deterministic modelling - in other words, the epidemic outcome is predictable as all parameters are fully known. However, this course delves into the many cases – especially in the early stages of an epidemic – where chance events can be influential in the future of an epidemic.

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So, you'll be introduced to some examples of such ‘stochasticity’, as well as simple approaches to modelling these epidemics using R. You will examine how to model infections for which such ‘population structure’ plays an important role in the transmission dynamics, and will learn some of the basic approaches to modelling vector-borne diseases, including the Ross-McDonald Model.

Even if you are not designing and simulating mathematical models in future, it is important to be able to critically assess a model so as to appreciate its strengths and weaknesses, and identify how it could be improved. One way of gaining this skill is to conduct a critical peer review of a modelling study as a reviewer, which is an opportunity you'll get by taking this course.

WHAT YOU WILL LEARN

- Distinguish between stochastic and deterministic models, explain when either are appropriate, and perform simple simulations of a stochastic model

- Identify where it is important to incorporate population structure in a model and design and simulate a transmission model capturing such structure

- Evaluate the assumptions behind the Ross MacDonald model, and code such a model using R to simulate the dynamics of a vector-borne disease

- Critically evaluate a modelling study and communicate its strengths and weaknesses to a scientifically literate audience

Course 3 of 3 in the Infectious Disease Modelling Specialization.


Syllabus


WEEK 1

Building on the SIR Model: Stochasticity

The other two courses in this specialisation have focused on performing deterministic modelling - that is, the epidemic outcome is predictable as all parameters are fully known. However, there are many cases, especially in the early stages of an epidemic, where chance events can be influential in the future of an epidemic. In this module, you will be introduced to some examples of such ‘stochasticity’, as well as, simple approaches to modelling these epidemics using R.


WEEK 2

Building on the SIR model: Heterogeneity

In the basic deterministic SIR model, all susceptible individuals in a population are subject to the same risks of infection. However, there are many important infectious diseases where certain groups of the population account for a disproportionate amount of transmission: these are not always the same groups that bear the greatest amount of morbidity and mortality. In this module, you will examine how to model infections for which such ‘population structure’ plays an important role in the transmission dynamics.


WEEK 3

Building on the SIR model: Vector-borne Diseases

Many important diseases are not directly transmitted between hosts, but depend on ‘vectors’ to pass infection between hosts, for example biting insects. It is important to be able to extend the modelling approaches you have studied so far to capture these more complex forms of natural history. In this module, you will learn some of the basic approaches to modelling vector-borne diseases, including the Ross-McDonald model, which is a framework that provides an important foundation for such diseases.


WEEK 4

Assignment: Modelling Study Critique

Even if you are not designing and simulating mathematical models in future, it is important to be able to critically assess a model, to appreciate its strengths and weaknesses, and to identify how it could be improved. One way of gaining this skill is to conduct a critical peer review of a modelling study in the position of a reviewer evaluating it for publication in a journal. This module is reserved for the completion of your assignment - for you to apply the knowledge and skills you've developing throughout this specialisation.



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