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. 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.
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이 강좌에 대하여
배울 내용
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
귀하가 습득할 기술
- Mathematical Model
- R Programming
- Infectious Diseases
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Imperial College London is a world top ten university with an international reputation for excellence in science, engineering, medicine and business. located in the heart of London. Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges.
석사 학위 취득 시작
강의 계획표 - 이 강좌에서 배울 내용
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.
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.
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.
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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BUILDING ON THE SIR MODEL의 최상위 리뷰
I thought it was clear, the syntax problems were about the same topic and needed the solution talked about in the videos. The subject was completely covered. I already recommended it to like 5 people.
I have found it useful for increasing my insights into infectious disease modelling.
A great learning opportunity. Advanced content presented in a convincing and understandable manner. Simply amazing.
a great follow up to the R coding course and a good entree into the world of public health
Infectious Disease Modelling 특화 과정 정보
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.

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