Welcome to the course!
We are excited to welcome you to the series of sessions
Before the first session, please ensure you have completed the pre-course videos and readings on Canvas, and that your R environment is fully set up.
During the live sessions, we will work through practical outbreak exercises using Quarto (.qmd) files, based on a simulated Ebola outbreak.
There is a .qmd file per lab session, named lab_1.qmd, lab_2.qmd, ... You should review the .qmd files and attempt the exercises in advance. Certain exercises - those marked with the 🧠 symbol - we will collaboratively complete together during the sessions.
If you have any questions ahead of the sessions on any of the materials, please post them on Canvas so we can address them during the live discussions. We have set up specific threads for each lab, as well as a general questions thread.
See you soon!
Carl, Cy, Degoot
For this workshop, we assume you are using RStudio - please ensure you have RStudio (and by implication, R) available on the computer you are using for the course; follow the directions from Posit in that link to accomplish an install. We have tested this material using the latest version Rstudio and R, so we recommend you install or upgrade to those, but we understand you may have restrictions about what you are allowed to do on your machine.
To get all files relevant to the course, you can simply clone this repository. You should be able to use RStudio's project interface to do so (these screenshots might vary slightly from your interface):
- create a new project:
- select the version control option:
- select the
gitoption:
- enter the info for this repository, "https://github.com/ACCIDDA/SISMID_course":
Alternatively, if you are generally familiar with git, feel free to use whatever approach you like to clone this repository.
In the R project you just created, open the install_script.R file. This contains all the packages that you will need for this course. There is one library, sodium which requires some steps outside R, but once you have done those, you can source this file to manage all the installation steps. Note: there is a lot to install, so expect this will take a bit.
If you need to more carefully manage your R environment, you may want to use a tool like renv or pak - feel free to use those tools.
If you are having issues with installation, please post in the Canvas Discussion board.
This two-part lab focuses on outbreak reconstruction using the outbreaker2 package.