tutorials-early

Tutorials to learn reading, cleaning and validating case data, and converting line list data to incidence for visualizing epidemic curves.

https://github.com/epiverse-trace/tutorials-early

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Tutorials to learn reading, cleaning and validating case data, and converting line list data to incidence for visualizing epidemic curves.

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

# Epiverse-TRACE Tutorials Early


[![](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
[![Project Status: Active - The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)


Tutorials on read and clean case data, and make line list for outbreak analytics with R developed by the Epiverse-TRACE initiative. These tutorials are visible at: . 

More information about Epiverse-TRACE learning material is available at: 

## Contributing

Please see the [CONTRIBUTING.md](CONTRIBUTING.md) for contributing guidelines and details on how to get involved with this project. Please adhere to this project's [Code of Conduct](CODE_OF_CONDUCT.md).

Also see the current list of [issues](https://github.com/epiverse-trace/tutorials-early/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](https://carpentries.github.io/sandpaper-docs/).





## License
Lesson content is published with a [CC-BY license](LICENSE.md).

## Maintainer(s)

Current maintainers of these tutorials are:

- [Andree Valle-Campos](https://github.com/avallecam/) (Content)
- [Hugo Gruson](https://github.com/Bisaloo/) (Infrastructure)





## Related

Epiverse-TRACE documentation:

+ [How-to guides](https://epiverse-trace.github.io/howto/): Reproducible recipes with concrete steps to solve specific Outbreak Analysis questions using multiple packages.
+ [Reference manuals and vignettes](https://epiverse-trace.github.io/getting-started.html#epiverse-trace-packages): Package-specific usage guides and function examples, along with explanatory articles.

Preliminary learning materials:

+ [Introductory R tutorials](https://appliedepi.org/resources/tutorials.html): Refresh your R knowledge with interactive online self-paced tutorials from the Applied Epi organization.
+ [The Epidemiologist R Handbook](https://www.epirhandbook.com/en/index.html): Online book on basics, data management, epidemiological analysis, visualization, and reporting from the Applied Epi organization.

## Citation

See [CITATION.cff](CITATION.cff) for citation information, including a list of authors.
([Read more about the Citation File Format and how to use it](https://citation-file-format.github.io/).)

To cite these tutorials in publications use:

```{r,eval=TRUE,echo=FALSE,comment=""}
cffr::as_bibentry(x = "CITATION.cff")
```

A BibTeX entry for LaTeX users is:

```{r,eval=TRUE,echo=FALSE,comment=""}
utils::toBibtex(cffr::as_bibentry(x = "CITATION.cff"))
```

## Contact
Please contact [Andree Valle-Campos](mailto:andree.valle-campos@lshtm.ac.uk) with any questions about this tutorial.

Owner

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: >-
  Epiverse-TRACE Tutorials Early: Read and clean case data,
  and make linelist for outbreak analytics with R
message: >-
  Please cite this lesson using the information in this file
  when you refer to it in publications, and/or if you
  re-use, adapt, or expand on the content in your own
  training material.
type: dataset
authors:
  - given-names: Abdoelnaser
    family-names: Degoot
    email: abdoelnaser-mahmood.degoot@lshtm.ac.uk
    orcid: 'https://orcid.org/0000-0001-8788-2496'
  - given-names: Andree
    family-names: Valle-Campos
    email: andree.valle-campos@lshtm.ac.uk
    orcid: 'https://orcid.org/0000-0002-7779-481X'
repository-code: 'https://github.com/epiverse-trace/tutorials-early'
url: 'https://epiverse-trace.github.io/tutorials-early/'
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
  - exploratory-data-analysis
  - data-cleaning
  - data-validation
  - data-visualization
  - carpentries
  - rstats
  - english-language
license: CC-BY-4.0
version: v2025-03-11
date-released: '2025-03-11'

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