Tutorials on real-time analysis and forecasting for outbreak analytics with R developed by the Epiverse-TRACE initiative. These tutorials are visible at: https://epiverse-trace.github.io/tutorials-middle/.
More information about Epiverse-TRACE learning material is available at: https://epiverse-trace.github.io/learn.html
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.
Lesson content is published with a CC-BY license.
Current maintainers of these tutorials are:
- Andree Valle-Campos (Content)
- Hugo Gruson (Infrastructure)
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.
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:
Valle-Campos A, Minter A (2025). "Epiverse-TRACE Tutorials Middle:
Real-time analysis and forecasting for outbreak analytics with R."
<https://epiverse-trace.github.io/tutorials-middle/>.
A BibTeX entry for LaTeX users is:
@Misc{vallecampos_etall:2025,
title = {Epiverse-TRACE Tutorials Middle: Real-time analysis and forecasting for outbreak analytics with R},
author = {Andree Valle-Campos and Amanda Minter},
year = {2025},
url = {https://epiverse-trace.github.io/tutorials-middle/},
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,epidemiological-parameters,reproduction-number,forecasting,outbreak-severity,superspreading events,transmission chains,carpentries-workbench,rstats,english-language},
version = {v2025-03-11},
}
Please contact Andree Valle-Campos with any questions about this tutorial.