As for Chapter 11, we use material from the short course Simulation-Based Inference for Epidemiological Dynamics (SBIED). We develop a concrete example of the general POMP modeling framework, and we see the theory and practice of implementing a simulator for the model.
The Susceptible-Infected-Recovered (SIR) model used for this chapter is a central concept for epidemiology. For the purposes of STATS/DATASCI 531, we view it as one example of a mechanistic model, which exemplifies a more general process of model development and data analysis. One epidemiological idea used without definition in the lecture is \(R_0\), defined to be the expected number of secondary infections arising from one infected individual in a fully susceptible population. The SIR model supposes that previously infected individuals cannot become reinfected, so those in compartment R are protected from infection.
The SIR model in epidemiology is closely related to predator-prey models in ecology. Similar models can be used to describe spread of ideas (including rumors or mis-information) on social networks.
| Slides | ||
| Annotated slides | ||
| Notes | ||
| R script | R | |
| Worked solutions to the Exercises | html | |
| Recording, Chapter 12, Part 1 | Compartment models | (17 mins) |
| Recording, Chapter 12, Part 2 | Eulerโs method for simulating Markov processes | (24 mins) |
| Recording, Chapter 12, Part 3 | Compartment models in the pomp package | (47 mins) |
| Recording, Chapter 12, Part 4 | Discussion of exercises | (10 mins) |
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