EPI 501 Dynamics of Infectious Disease (Review)

Table of Contents (reverse chronological)

• Common Error Messages

• Final Review (March 2, 2018)
  • Slides for final review [PDF]
    • Tips
    • \(R_0\) review
    • Practice Exam (Part A)
    • Practice Exam (Part B)
    • Quick note about deterministic models
  • A simulation showing impact of latent period on your infectious curve
• Week 3 (Februrary 9, 2018)
  • Review session:
    • Went over Week 1 and Week 2 slides in class, line-by-line. Please review those if you didn’t attend the lab.
    • In addition, we spent a lot of time on the ebola time-varying transmission model.
      • I made a notebook to answer the two questions we didn’t have time for: (1) What happens when you delay intervention? (2) What happens when you change the rate of decay?
    • As a reminder, I made an interactive infectious disease app you can play with. Play with parameters, especially the relationship between the latent period and the infectious period, to get a better sense of when we need a latent compartment.
• Week 2 (January 29, 2018)
  • Ebola and SEIR models [PDF] [Code and Data Files]
    • SEIR model with case fatality ratio
    • Plotting SEIR lines
    • COunting total cases and total deaths
    • Time-varying transmission
    • Calculate changing \(R_0\)
    • Time-varying beta
• Week 1 (January 22, 2018)
  • Introduction to ODE models in R [PDF] [Code Files]
    • SIR code review
    • Visualize your results
    • Make an SI model
    • Make an SIS model
    • Make an SIR model with births/deaths
  • Introduction to R, discrete time models, non-infectious ODE models.
  • Download headache_exercises.zip
    • Or download the code here (not recommended):
      • discrete_births_and_deaths.R
      • headache_discrete.R
      • headache_ode.R
  • Annotated code:
    • For the headache_discrete.R file.
    • For the headache_ode.R file.
• Week 0 (January 16, 2018)
  • Software Carpentry: Strongly recommend you do sections 0 to 3 if you’ve never used R before. This will get you up and running with the software and introduce you to RStudio.
  • Swirl Tutorial: If you’ve never used R before, we highly recommend doing this tutorial and the SW tutorial (above).
  • Super quick R Review: If you’ve used R in the past but need a refresher, this is a tutorial I made for Spring 2017. It is not nearly as thorough as the above two.
  • Shiny app for ODE models: Example of what we’ll be doing throughout the course.

Source / Archive

• You can find the source code along with all class code and PDFs on this project’s GitHub page.
• You can find slides from Spring 2017 here.