Schedule: link here
Background Materials:
Please download R here: https://www.r-project.org/
Download R Studio here: https://www.rstudio.com/
We recommend the Sublime text editor for reviewing R code: https://www.sublimetext.com/
Here is a short R tutorial: tutorial file
Background reading on modeling infectious diseases by Heesterbeek et al: link to paper
Day 1 Materials:
Lecture 1: Intro lecture by Micaela Martinez: link 1 and link 2
Lecture 2: Basic SIR dynamics by Matt Ferrari: link here
R Session 1: Intro to modeling by Tiggy Menkir: link to files (link to updated handout)
Lecture 3: Vaccination & Interventions by Micaela Martinez: link 1 and link 2
Group Assignment: link here
Day 1 Recording: recording 1 and recording 2
Day 2 Materials:
Lecture 4: Heterogeneity in SES lecture by Tiggy Menkir: link here
Lecture 4 background reading: link to paper
Lecture 5: Heterogeneity expanded (age structure and the force of infection) by Matt Ferrari: link here
R Session 2: Heterogeneity and age structure by Deepit Bhatia and Matt Ferrari: link to files
Lecture 6: Parameter Estimation (estimating R0) by Matt Ferrari: link here
R Session 3: Parameter estimation by Deepit Bhatia: link to files
Answer key for Day 2 R sessions: link here
Day 2 Recordings: link here
Day 2 R session updated materials (link here). The updated worksheets and answers address the following student feedback:
- General:
- Removing Rmd files as they were confusing for many participants to work on
- Estimation:
- Explicit re-naming of variables in the Niamey data so they are easier to run a regression model with
- Removing extraneous information that isn’t needed to work on the exercises
- Age Heterogeneity
- Removed age transition matrix visualization
- Parameter values are consistent across worksheets
Day 3 Materials:
Lecture 7: Confronting models with data by Micaela Martinez: link here
Lecture 8: Stochasticity and Uncertainty lecture by Micaela Martinez and Matt Ferrari: link 1
Day 3 Recording: link here
Additional Materials
An Introduction to Infectious Disease Modeling (link here). Recommended sections include:
Chapter 3 – intro to setting up model equations
Chapter 4.1-4.2 – identifying properties that can be gleaned from early epidemic dynamics
Chapter 4.3 – evaluating long-term dynamics
Chapter 5.1-5.2 & Chapter 7.3-7.4 – age structure; analyzing age trends from data, incorporating age structure in models, and estimating key model parameters when such heterogeneities are present
Chapter 8.1-8.5 – modeling STIs
Chapter 6.1 -6.7 – approaches for incorporating stochasticity
Epidemics: Models and Data using R: https://link.springer.com/book/10.1007/978-3-319-97487-3
Link to R code for each chapter from the book: https://github.com/objornstad/epimdr
Link to Shiny apps showcasing specific types of models: https://github.com/objornstad/ecomodelmarkdowns
Certificates of Completion
Certificates of completion for each module can be downloaded from your dashboard shortly after you complete the online evaluation. Immediately after a module concludes, an evaluation for that module will appear on your dashboard. After you complete the last module in an institute, the evaluation will include evaluation questions for both the module and the overall institute (i.e., proceed through both sets of questions to generate the final certificate of completion).
Certificates are generated through the registration system and, occasionally, names and module titles lose their formatting. If this happens, please email nelsod6@uw.edu and we will get you a corrected copy.
The Martinez Lab 