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Outbreak science and public health forecasting
1. Chapter One - Reed-Frost dynamics
2. Chapter Two - Compartmental models
3. Chapter Three - Simulating the Reed-Frost model
4. Chapter Four - Montecarlo sampling and the Reed-Frost model under intervention
5. Chapter Six - Simulating Compartmental models
6. Estimating Epidemic models from observations
7. A start to stochastic network models
8. Multi-species models
9. Discrete time Kermack-McKendrick Model
10. Fixed points and linear stability
11. Chapter 9 - Temporal forcing and time-dependent parameters
12. Chapter 10 - Stochastic epidemic models
13. Metapopulation models
14. LTCF application
15. Cellular automota
16. Bayesian Learning
17. Computational Posterior
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