Preparation for the Clinic

You should complete the following steps in preparation for the clinic before the first day of the Clinic.

1. Research Pitch

  • Prepare a short oral presentation summarizing your research (2 minutes max, 1 slide in PDF format)
    • You may summarize recent, completed research that forms the basis for ongoing work, or you may give an overview of ongoing work or of a new project that’s in development.
    • We recommend selecting 1-2 visual aids (eg, figures or diagrams) that will help you explain key aspects of the research. Please keep the text on your slide to a minimum.
    • Do not attempt to explain all of the details of your project - stick to the essentials and keep it simple. You will be kept to time.
  • Prepare a more detailed description of your research
    • We recommend using an existing description of your research, rather than creating something from scratch. For example, you could use a poster you have presented elsewhere, a project proposal you have written, or even compile abstracts from 2-3 projects you’ve published or presented at meetings.
    • The intent here is not for you to spend hours preparing something new to share, rather to provide an easy way for others who are interested to learn more about your research and interests.
    • Please do keep it brief (1-3 pages would be best).
  • Upload the PDF version of your 1-slide research pitch to the 01_pitchSlides folder on the MMED Participants Team on Microsoft Teams. Use the file naming convention 01_SurnameFirstname_pitch.pdf.
  • Upload the PDF version of your more detailed description of your research to the 02_reserachInfo folder on the MMED Participants Team, using the file naming convention 02_SurnameFirstname_info.pdf.
  • Please contact Faikah if you have any trouble accessing the MMED Participants Team or uploading your material.

2. Software installation

Please install the following programs on the computer you will use during the Clinic, prior to the opening session:

  • Excel (or a compatible spreadsheet program)
  • Git - version control software
    • Note that recent versions of MacOS come with Git installed, so you may not need to install this program.
  • Git Bash (Recommended for Windows users only) - command line access to Git on Windows
  • R - a statistical programming language (download links for Windows, Linux, and MacOS)
    • If you already have R, please check that you have a recent version, or else update. Versions starting with 3.5 or 3.6 should be OK.
  • R Studio - a user interface for R that will be needed for computer exercises (download link)
  • ICI3D R package - a package containing interactive tutorials for use at the Clinic; to install, run the following lines of code from the R or Rstudio command line:
install.packages('remotes') # if not already installed
remotes::install_github('ICI3D/ici3d-pkg') # DO NOT DO THIS IF YOU NEED TO UPDATE R VERSION (see above)

Please let us know if you have trouble installing any of the above software!

Please note that you will need to have administrative permissions on the computer you use for the Clinic. You may need to arrange this through your IT department if you are using an institutional computer.

3. Introductory tutorials

Introduction to R and R Studio

When you have successfully installed both R and R Studio, please work through these tutorials:

If you are unfamiliar with or rusty on your understanding of the Binomial Distribution, you may also want to work through the introductory Binomial Distribution tutorial.

Tip: To download all of the tutorials at once into a single directory on your computer, you can clone the ICI3D R tutorials repository. You can get started quickly by opening the RTutorials.Rproj file within that directory.

Introduction to Git

In addition, please complete all 4 lessons in this free, browser-based tutorial from Codecademy. You will learn the foundations of how to work with git to improve your workflow and collaborate on projects that involve code.

  • Basic Git Workflow teaches you how to create a repository for a project and keep track of changes you make to files.
  • How to Backtrack in Git shows you how to correct mistakes in coding projects or revert to an older version of your code if you decide to change directions.
  • Git Branching introduces a workflow that allows you to have multiple working versions of your code, how to bring them back together, and what to do if your versions have conflicting changes.
  • Git Teamwork teaches you how to collaborate on a project using git.

If you are already comfortable using git, you can skip this activity, but if you’re new to git or your skills are rusty, please take the time to work through all four lessons.

For all participants

  • Heesterbeek, JAP, RM Anderson, V Andreasen, S Bansal, D De Angelis, C Dye, KTD Eames, WJ Edmunds, SDW Frost, S Funk, TD Hollingsworth, T House, V Isham, P Klepac, J Lessler, JO Lloyd-Smith, CJE Metcalf, D Mollison, L Pellis, JRC Pulliam, MG Roberts, C Viboud, and the Isaac Newton Institute IDD Collaboration. (2015) Modeling infectious disease dynamics in the complex landscape of global health. Science 347(6227): aaa4339. doi:10.1126/science.aaa4339
  • We have put together an introductory overview, which includes excerpts from the below papers.

    • Bellan, SE, JRC Pulliam, JC Scott, J Dushoff and the MMED Organizing Committee. How to make epidemiological training infectious. PLoS Biology 2012; 10: e1001295.
    • Susser, M and E Susser. Choosing a future for epidemiology: I. Eras and paradigms. Am J Public Health 1996; 86: 668–73.
    • Koopman, JS and JW Lynch. Individual causal models and population system models in epidemiology. Am J Public Health 1999; 89: 1170–4.
    • Brauer, F. Mathematical epidemiology is not an oxymoron. BMC Public Health 2009; 9: S2.

Especially for those new to dynamical modeling