Two Paths From Here

Continuing to NME-II

Next week you build the research models behind today’s applications: custom disease modules, multi-layer and open-population networks, data-driven parameterization, and a full COVID model.

The applications you just saw are what you will be able to build.

If NME-I Is Your Stopping Point

You can already estimate, simulate, and analyze built-in network models, which is the hardest conceptual step.

Keep going on your own with the prioritized path on the coming slides, plus the website and support channels.

The Statnet / EpiModel Family Tree

network · networkDynamic · sna · ergm · tergm · tsna · ndtv · EpiModel · EpiModelHIV · EpiModelCOVID

statnet.org  ·  CRAN: statnet

Statnet Tutorials

https://statnet.org/workshops

Main EpiModel Website

https://epimodel.org/

GitHub Repository

https://github.com/EpiModel/EpiModel

EpiModel Package Vignettes

EpiModel Package Vignettes

NME @ SISMID

Staying in touch after the course:

  • We keep the Slack workspace open as long as the SISMID organizers allow. Message us or your classmates there with any questions or comments.
  • Feel free to email us or open a GitHub issue.
  • The NME SISMID website stays available indefinitely, updated at least yearly.
  • We are currently working on a full-length book that expands on these materials and provides additional exercises and resources…

EpiModelCOVID

https://github.com/EpiModel/EpiModelCOVID

EpiModelHIV

https://github.com/EpiModel/EpiModelHIV

ARTnet Dataset for HIV Modeling of US MSM

https://github.com/EpiModel/ARTnet

EpiModelHPC

https://github.com/EpiModel/EpiModelHPC

If You Are Continuing on Your Own

  • Review the Journal of Statistical Software paper on EpiModel
  • Review these SISMID course materials in more depth
    • Work through tutorials and lab examples we did not cover in class
  • Consult the EpiModel Gallery for disease-extension examples
  • Build a basic model of your disease with a simple network parameterization
    • Incrementally add complexity to both the network and disease components
  • Source and implement real-world network data into your model
  • Consider a full-scale, research-level implementation
    • Take inspiration from extension packages like EpiModelHIV and CRAN vignettes
  • Ask for help!

Prefer it guided? NME-II walks through all of this with instructors in the room.

We are here to help!

  • A central mission of the EpiModel / Statnet platforms is to assist our users.
    • Ask for help in a semi-public forum so others can learn from your questions.
  • We request that you cite EpiModel if you use it.
    • Jenness SM, Goodreau SM, Morris M. EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks. Journal of Statistical Software. 2018;84(8):1-47.
    • Email us so we can add your work to our bibliography.
  • Consider using an open-source, open-development model yourself.

Thank you!

You can now build, simulate, and analyze dynamic network models of epidemics.

Stay in touch on Slack, email, or a GitHub issue, and the website stays online. One next step: open the Gallery, copy the closest example, and change one thing.

Remaining time is available for questions, project consultations, and small-group discussions.