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1. Poster preparation

Prepare a poster presentation to share your research.

• Poster preparation guidelines are available here.
• Be sure to submit your poster by the May 22 deadline, if you would like us to print it for you.
• See this page for poster session assignments.

2. Software installation

If you plan to bring a laptop to use during the Clinic, please install the following programs prior to arrival:

• Excel (or a compatible spreadsheet program)
• Git - version control software
  • Note that the latest versions of MacOS come with Git installed, so you may not need to install this program.
• SmartGit - a git client and graphical user interface available for Windows, MacOS, and Linux
• 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)
• R Studio - a user interface for R that will be needed for computer exercises (download link)

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

Note: Even if you are not bringing a laptop to the Clinic, you will need access to a computer with both R and R Studio installed to prepare for the Clinic.

3. Introductory tutorials

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

• Tutorial 0: Introduction to R Studio - provides an introduction to the user interface
• Tutorial 1: Introduction to R and its quirks (required)
• Tutorial 2: More on Vectors, Data Frames, and Functions (required)
• Tutorial 3: Probability Distributions and Control Structures (required)

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.

4. Recommended Readings

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

• Welte, A, B Williams, and G Hitchcock. Mathematical models of transmission and control of infectious agents, Chapter 5.18 in Oxford Textbook of Global Public Health (Sixth Edition, Eds. R Detels, M Gulliford, QA Karim, and CC Tan). Oxford University Press (February 2015). Print ISBN-13: 9780199661756