Welcome!

Alex Edwards
Zane Billings

Welcome to SISMID Workshop: R Programming for Infectious Disease Modeling!

Alex Edwards (Any)

PhD Candidate, Division of Epidemiology and Health Sciences, Stellenbosch University

Email: Alex.edwards@emory.edu


Zane Billings (he/him)

PhD Candidate, Department of Epidemiology and Biostatistics

Email: Wesley.Billings@uga.edu

Introductions

  • Name?
  • Current position / institution?
  • Most interesting pathogen/condition/exposure to you?

Course website

  • All of the materials for this course can be found online here: https://wzbillings.github.io/SISMID-2025/.
  • This contains the schedule, course resources, and online versions of all of our slide decks.
  • The Course Resources page contains download links for all of the data, exercises, and slides for this class.
  • Please feel free to download these resources and share them – all of the course content is under the Creative Commons BY-NC 4.0 license.

Overall Workshop Objectives

By the end of this workshop, you should be able to

  1. Write code that uses advanced R programming tools like control flow and custom functions.
  2. Use advanced R programming tools to answer interesting epidemiology questions.
  3. Be (more) prepared to use R in other SISMID modules

Workshop Overview

Multiple modules that will each:

  • Start with learning objectives
  • End with summary slides
  • Include mini-exercises or practice problems

Themes that will show up throughout the workshop:

  • Reproducibility
  • Good coding techniques
  • Thinking algorithmically

Note that we listed a lot of topics on the course description, we won’t have time to get in-depth with most of them. What are you most interested in learning?

Course structure

  • We’ll start the course with some fundamentals.
  • These include advanced programming techniques, applications of those programming techniques, and just some neat things we think will help prepare you for infectious disease modeling.
  • Some examples are: using R packages to improve your life, simulating power, bootstrap confidence intervals.
  • We’ll have time for some other advanced topics too, but maybe not all of them depending. These could be: disease mapping, maximum likelihood, differential equations, and advanced linear models.

Useful (+ Free) Resources

Want more?

  • R for Data Science: http://r4ds.had.co.nz/
    (great general information)

  • Fundamentals of Data Visualization: https://clauswilke.com/dataviz/

  • R for Epidemiology: https://www.r4epi.com/

  • The Epidemiologist R Handbook: https://epirhandbook.com/en/

  • R basics by Rafael A. Irizarry: https://rafalab.github.io/dsbook/r-basics.html (great general information)

  • Open Case Studies: https://www.opencasestudies.org/
    (resource for specific public health cases with statistical implementation and interpretation)

Useful (+Free) Resources

Need help?

  • Various “Cheat Sheets”: https://github.com/rstudio/cheatsheets/

  • R reference card: http://cran.r-project.org/doc/contrib/Short-refcard.pdf

  • R jargon: https://link.springer.com/content/pdf/bbm%3A978-1-4419-1318-0%2F1.pdf

  • R vs Stata: https://link.springer.com/content/pdf/bbm%3A978-1-4419-1318-0%2F1.pdf

  • R terminology: https://cran.r-project.org/doc/manuals/r-release/R-lang.pdf

Installing R

Hopefully everyone has pre-installed R and RStudio (and Quarto if needed). Let’s take a minute to make sure everyone is set up and then jump in!