Epiverse-TRACE Tutorials Late

Tutorials on scenario modelling for outbreak analytics with R developed
by the Epiverse-TRACE initiative. These tutorials are visible at:
https://epiverse-trace.github.io/tutorials-late/.

More information about Epiverse-TRACE learning material is available at:
https://epiverse-trace.github.io/learn.html

Contributing

Please see the CONTRIBUTING.md for contributing
guidelines and details on how to get involved with this project. Please
adhere to this project’s Code of Conduct.

Also see the current list of
issues for
ideas on how to contribute to this training curriculum.

To learn more about how this lesson site is built and how you can edit
the pages, see the Introduction to The Carpentries
Workbench.

License

Lesson content is published with a CC-BY license.

Maintainer(s)

Current maintainers of these tutorials are:

• Andree Valle-Campos

Related

Epiverse-TRACE documentation:

• How-to guides: Reproducible
  recipes with concrete steps to solve specific Outbreak Analysis
  questions using multiple packages.
• Reference manuals and
  vignettes:
  Package-specific usage guides and function examples, along with
  explanatory articles.

Preliminary learning materials:

• Introductory R
  tutorials: Refresh
  your R knowledge with interactive online self-paced tutorials from the
  Applied Epi organization.
• The Epidemiologist R
  Handbook: Online book on
  basics, data management, epidemiological analysis, visualization, and
  reporting from the Applied Epi organization.

Citation

See CITATION.cff for citation information, including a
list of authors. (Read more about the Citation File Format and how to
use it.)

To cite these tutorials in publications use:

Minter A, Degoot A (2025). "Epiverse-TRACE Tutorials Late: Scenario
modelling for outbreak analytics with R."
<https://epiverse-trace.github.io/tutorials-late/>.

A BibTeX entry for LaTeX users is:

@Misc{minter_etall:2025,
  title = {Epiverse-TRACE Tutorials Late: Scenario modelling for outbreak analytics with R},
  author = {Amanda Minter and Abdoelnaser Degoot},
  year = {2025},
  url = {https://epiverse-trace.github.io/tutorials-late/},
  abstract = {The Epiverse-TRACE initiative aims to provide a software ecosystem for outbreak analytics with integrated, generalisable and scalable community-driven software. We support the development of R packages, make the existing ones interoperable for the user experience, and stimulate a community of practice. In the outbreak analytics curriculum, we built three tutorials around an outbreak analysis pipeline split into three stages: Early, Middle, and Late tasks. Early tasks include reading, cleaning and validating case data, and converting line list data to incidence for visualizing epidemic curves. Middle tasks host real-time analysis that includes accessing epidemiological delays, estimating transmission metrics, forecasting, and severity from incidence data, superspreading from line list and contact data, and simulating transmission chains. Late tasks include accessing and analyzing social contact matrices, scenario modelling to simulate disease spread and investigate interventions, and modelling disease burden.},
  keywords = {outbreak-analytics,scenario-modelling,contact-matrix,non-pharmaceutical-interventions,vaccination,disease-burden,carpentries-workbench,rstats,english-language},
  version = {v2025-03-11},
}

Contact

Please contact Andree
Valle-Campos with any questions
about this tutorial.