Spring 2026

Syllabus in progress

Week 1: Jan 12 - 16

Lecture: Introduction: Phylogenetic insights into infectious disease dynamics
Lab: Wrangling and aligning sequence data, building ML phylogenies

Week 2: Jan 19 - 23

No class Jan 19th: MLK Day
Lecture: The statistical underpinnings of Bayesian and ML inference: Part I

Week 3: Jan 26 - 30

Lecture: The statistical underpinnings of Bayesian and ML inference: Part II
Lab: MCMC in BEAST: priors, posteriors, mixing, convergence, ect.

Week 4: Feb 2 - 6

Lecture (pre-recorded): Exploring the origins of epidemics with phylogeography
Lab: Discrete trait models for phylogeographic analysis

Week 5: Feb 9 - 13

Lecture: Coalescent theory and the population genetics of molecular evolution
Lab: Bayesian skyline plots in BEAST
Bonus Lab (optional): Structured coalescent models with MASCOT

Week 6: Feb 16 - 20

Lecture: Inferring transmission trees and who’s infecting whom
Side topic: Accounting for within-host diversity
Lab: Transmission tree reconstruction with SCOTTI

Week 7: Feb 23 - 27

Lecture: Non-tree like evolution: Recombination, clonal frames and ancestral recombination graphs
Lab: Detecting recombination in RDP4

Week 8: March 2 - 6

Lecture: Mobilize your genome: Horizontal transfers, mobile elements and genome evolution in bacterial and eukaryotic pathogens
Lab: Organize mini research projects

Week 9: March 9 - 13

Lecture: Multi-type birth-death models and adaptive molecular evolution
Lab: Estimating the fitness of drug resistance mutations in BDMM

March 16 - 20: SPRING BREAK

Week 10: March 23 - 27

Lecture: Modeling transmission dynamics with SIR models
Lab: SIR model practical; simulating epidemics in Python/Jupyter

Week 11: March 30 - April 3

Lecture: Modeling and simulating evolution with generative models
Lab: How good is BEAST? Simulating trees and sequence data to test our algorithms

Week 12: April 6 - 10

Lecture: Putting it all together with phylodynamics: phylogenetics meets epidemic modeling
Lab: Fitting SIR models to phylogenies

Week 13: April 13 - 17

Lecture: After the data deluge: scaling strategies for massive genomic datasets
Lab: Tracking viral movement using massive genomic datasets

Week 14: April 20 - 24

Lecture: Predicting the (very near) future: Forecasting pathogen evolution
Lab: Discussion of Lusckza and Lassig (Nature, 2015) and Morris et al. (Trends in Micro, 2018)

Week 15: April 27

Last day of class: Team presentations