Lectures
You can download the lectures here. We will try to upload lectures prior to their corresponding classes.
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Day 1 Lecture 1: Introduction to R session 1
Familiarise with the R language and the R Studio integrated development environment (IDE). Questions such as “why R?” will be discussed, in comparison to other programming languages used for epidemiological data analysis
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Day 1 Lecture 2: Introduction to R session 2
A technical overview of some of the basic data structures, packages and file manipulation procedures will also be covered, as well as help functions and other tips for helping participants independently explore R’s functionalities
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Day 2 Lecture 1: Introduction to modelling infectious diseases
Introduce to core concepts of infectious diseases dynamics and the use of mathematical systems to simulate transmission
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Day 2 Lecture 2: Basic concepts of compartmental models
In this session we will go step by step in the process of designing a compartmental model. We will apply concepts of probability, proportions, hazard rates and competing hazards. We will also discuss alternatives for capturing disease events and interventions.
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Day 3 Lecture 1: The SIR model
Understand why the SIR model is at the core of infectious disease dynamics. In its simplicity, SIR models are the gate to introduce more complex concepts like the basic reproductive number (R0) and herd immunity.
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Day 3 Lecture 2: Understanding epidemic phases with an SIR model
Cover the mathematical expressions governing the SIR model. In practice, we will use R to understand an SIR model, understanding model variables, and model parameters.
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Day 4 Lecture 1: Introduction to stochastic models session 1
Introduce concepts of stochasticity and its relevance for understanding epidemic surge and probability of extinction
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Day 4 Lecture 2: Introduction to stochastic models session 2
Cover types of stochastic models and modelling procedures
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Day 4 Lecture 3: Assessing model uncertainty and calibration
Explore uncertainty and methods to assess it in modelling
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