SISMID 2026 · Pre-session materials 2
Introduction to MCMC 2
Please complete all materials below before your first synchronous session.

The materials on this page should be reviewed before your live lab sessions on June 22 and June 23. Work through the videos, readings, and problem sets at your own pace.

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Pre-session materials — Page 2



Pre-Course Work 3

Case Study 1: Serial Interval
Video
Introduction to MCMC – case studies in infectious disease modeling

Case Study 2: Poisson and NB Processes
Video
Poisson Process

Case Study 3: SIR and R0
Video
Compartment models: deterministic or stochastic

R Code
R script

Stan
Stan script 1

Stan
Stan script 2

Stan
Stan script 3

Stan
Stan script 4

Practical 6
Practical
Instructions

R Code
R script

Stan
Stan script 1

Stan
Stan script 2

Case Study 4: Metapopulation
Video
Modeling spatial spread using surveillance data

PDF
Goodness of fit

Practical 7
Practical
Instructions

R Code
R script

Stan
Stan script A

Stan
Stan script B

Stan
Stan script C



Readings

Minin, Volodymyr — Introduction to Rstan

⬇ mcmc_intro_to_stan.pdf

Gabry et al. (2019)
Visualization in Bayesian workflow. J. R. Statist. Soc. A 182, Part 2, pp. 389–402.

Breheny, P. (March 26, 2025)
GLM residuals and diagnostics.

⬇ mcmc_GLM Diagnostics.pdf

Hefferman, Smith & Wahl (2005)
Perspectives on the basic reproductive ratio. J R Soc Interface. Jun 7; 2(4): pp. 281–293. doi: 10.1098/rsif.2005.0042

Meyer, Held & Hohle (2017)

Wallinga & Lipsitch (2006)
How generation intervals shape the relationship between growth rates and reproductive numbers. Proc. R. Soc. B, 274, pp. 599–604. doi:10.1098/rspb.2006.3754

⬇ mcmc_Walliga & Lipsitch (2006)_Supp.pdf

White & Pagano (2008)

Optional: What is Hamiltonian Monte Carlo?
If you are curious about Hamiltonian Monte Carlo, these two YouTube videos are highly recommended:
Video 1

Video 2

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Return to Pre-Course Work 1 & 2

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