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‎index.md

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site: sandpaper::sandpaper_site
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---
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## Epiverse-TRACE tutorials
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The Epiverse-TRACE tutorials are training materials for Outbreak Analysis tasks aimed at [learners](../profiles.md) who are willing to achieve basic competence in modelling and analytics.
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The tutorials are built around the workflow of outbreak analysis split into three stages : early tasks, middle tasks and late tasks.
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![An overview of the tutorial topics](https://epiverse-trace.github.io/task_pipeline-minimal.svg)
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Task topics consist of one or more episodes. You can navigate to different episodes using the menu on the left hand side. Alternatively, you may find the topic you are interested in the [key points](../key-points.md) of each episode.
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Each episode contains:
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+ **Overview** : describes what questions will be answered and what are the objectives of the episode.
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+ **Prerequisites**: describes what episodes/packages need to be covered before the current episode.
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+ **Example R code** : work through the episodes on your own computer using the example R code.
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+ **Challenges** : complete challenges to test your understanding.
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+ **Explainers** : add to your understanding of mathematical and modelling concepts with the explainer boxes.
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Also check out the [glossary](../reference.md) for any terms you may be unfamiliar with.
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## Related projects
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+ R package vignettes : for R package `{package}` find the vignette located at `https://epiverse-trace.github.io/{package}/`. [Look at all Epiverse-TRACE packages in our developer space](https://epiverse-trace.github.io/).
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+ [How-to guides](https://epiverse-trace.github.io/howto/) : reproducible recipes with concrete steps to solve specific Outbreak Analysis questions.
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+ [The Epidemiologist R Handbook](https://www.epirhandbook.com/en/index.html) : Quick R code reference manual with task-centered examples that address common epidemiological problems.
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+ *COMING SOON* case studies : reproducible case-studies of outbreak data analysis tasks using R packages.
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This tutorial was built with [The Carpentries Workbench][workbench].
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[workbench]: https://carpentries.github.io/sandpaper-docs
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This is an [Epiverse-TRACE][epiversetrace] tutorial built with [The Carpentries Workbench][workbench].
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[epiversetrace]: https://epiverse-trace.github.io/
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[workbench]: https://carpentries.github.io/workbench/

‎learners/setup.md

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title: Setup
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---
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## Software Setup
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## Motivation
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**Outbreaks** appear with different diseases and in different contexts, but what all of them have in common is the key public health questions ([Cori et al. 2017](https://royalsocietypublishing.org/doi/10.1098/rstb.2016.0371#d1e605)). We can relate these key public health questions to outbreak data analysis tasks.
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Epiverse-TRACE aims to provide a software ecosystem for [**outbreak analytics**](reference.md#outbreakanalytics) 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.
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### Epiverse-TRACE tutorials
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The tutorials are built around an outbreak analysis pipeline split into three stages: **Early tasks**, **Middle tasks** and **Late tasks**.
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![An overview of the tutorial topics](https://epiverse-trace.github.io/task_pipeline-minimal.svg)
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Each task has its tutorial website. Each tutorial website consists of a set of episodes.
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| [Early task tutorials ➠](https://epiverse-trace.github.io/tutorials-early/) | [Middle task tutorials ➠](https://epiverse-trace.github.io/tutorials-middle) | [Late task tutorials ➠](https://epiverse-trace.github.io/tutorials-late/) |
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|---|---|---|
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| Reading and cleaning case data | Real-time analysis and forecasting | Scenario modelling |
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| Read and clean linelist data, Access delay distributions, and Estimate transmission metrics. | Forecast cases, Estimate severity, and Estimate superspreading. | Simulate disease spread and Investigate interventions. |
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Each episode contains:
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+ **Overview** : describes what questions will be answered and what are the objectives of the episode.
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+ **Prerequisites**: describes what episodes/packages need to be covered before the current episode.
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+ **Example R code** : work through the episodes on your own computer using the example R code.
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+ **Challenges** : complete challenges to test your understanding.
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+ **Explainers** : add to your understanding of mathematical and modelling concepts with the explainer boxes.
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Also check out the [glossary](../reference.md) for any terms you may be unfamiliar with.
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### Epiverse-TRACE R packages
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Our strategy is to gradually incorporate specialised **R packages** into our traditional analysis pipeline. These packages should fill the gaps in these epidemiology-specific tasks in response to outbreaks.
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![In **R**, the fundamental unit of shareable code is the **package**. A package bundles together code, data, documentation, and tests and is easy to share with others ([Wickham and Bryan, 2023](https://r-pkgs.org/introduction.html))](episodes/fig/pkgs-hexlogos-2.png)
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:::::::::::::::::::::::::::: prereq
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This course assumes intermediate R knowledge. This workshop is for you if:
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- You can use the magrittr pipe `%>%` and/or native pipe `|>`
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- You are familiar with functions from `{dplyr}`, `{tidyr}`, and `{ggplot2}`
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- You can read data into R, transform and reshape data, and make a wide variety of graphs
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We expect participants to have some exposure to basic Statistical, Mathematical and Epidemic theory concepts, but NOT intermediate or expert familiarity with modeling.
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::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: instructor
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::::::::::::::::::::::::::::
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Setup instructions live in this document. Please specify the tools and the data sets the learner needs to have installed. If you want to hide different setup instructions, you can use a `solution` tag.
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## Software Setup
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Follow these two steps:
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### Install R and RStudio
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### 1. Install or upgrade R and RStudio
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R and RStudio are two separate pieces of software:
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* **R** is a programming language and software used to run code written in R.
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* **RStudio** is an integrated development environment (IDE) that makes using R easier. In this tutorial, we use RStudio to interact with R.
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* **RStudio** is an integrated development environment (IDE) that makes using R easier. We recommend to use RStudio to interact with R.
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To install R and RStudio, follow these instructions <https://posit.co/download/rstudio-desktop/>.
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If you don't already have `R` and `RStudio` installed, follow the instructions for your operating system at <https://posit.co/download/rstudio-desktop/>.
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::::::::::::::::::::::::::::: callout
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### Update R and RStudio
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### Already installed?
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This tutorial requires R version 4.0.0 or later.
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Hold on: This is a great time to make sure your R installation is current.
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If you already have R and RStudio installed, first check if your R version is up to date:
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This tutorial requires **R version 4.0.0 or later**.
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:::::::::::::::::::::::::::::
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* When you open RStudio your R version will be printed in the console on the [console window](https://docs.posit.co/ide/user/ide/guide/code/console.html). Alternatively, you can type `sessionInfo()` into the console.
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To check if your R version is up to date:
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* If your version of R is older than the one required, download and install the latest version of R from the [R project website](https://cran.rstudio.com/) for your operating system.
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- In RStudio your R version will be printed in [the console window](https://docs.posit.co/ide/user/ide/guide/code/console.html). Or run `sessionInfo()` there.
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* After installing a new version of R, you will have to reinstall all your packages with the new version. For Windows, there is a package called `installr` that can help you with upgrading your R version and migrating your package library.
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- **To update R**, download and install the latest version from the [R project website](https://cran.rstudio.com/) for your operating system.
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* To update RStudio to the latest version, open RStudio and click on
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- After installing a new version, you will have to reinstall all your packages with the new version.
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- For Windows, the `{installr}` package can upgrade your R version and migrate your package library.
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- **To update RStudio**, open RStudio and click on
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`Help > Check for Updates`. If a new version is available follow the
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instructions on the screen. By default, RStudio will also automatically notify you
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of new versions every once in a while.
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instructions on the screen.
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### Check for Updates regularly
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While this may sound scary, it is **far more common** to run into issues due to using out-of-date versions of R or R packages. Keeping up with the latest versions of R, RStudio, and any packages you regularly use is a good practice.
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### Install required R packages
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### 2. Install the required R packages
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<!--
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During the tutorial, we will need a number of R packages. Packages contain useful R code written by other people. We will use packages from the [Epiverse-TRACE](https://epiverse-trace.github.io/).
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-->
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To try to install these packages, open RStudio and copy and paste the following code chunk into the [console window](https://docs.posit.co/ide/user/ide/guide/code/console.html), then press the <kbd>Enter</kbd> (Windows and Linux) or <kbd>Return</kbd> (MacOS) to execute the command.
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Open RStudio and **copy and paste** the following code chunk into the [console window](https://docs.posit.co/ide/user/ide/guide/code/console.html), then press the <kbd>Enter</kbd> (Windows and Linux) or <kbd>Return</kbd> (MacOS) to execute the command:
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```r
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if(!require("pak")) install.packages("pak")
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"tidyverse"
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)
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pak::pak(new_packages)
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pak::pkg_install(new_packages)
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```
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These installation steps could ask you `? Do you want to continue (Y/n)` write `Y` and press <kbd>Enter</kbd>.
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::::::::::::::::::::::::::::: spoiler
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### error with {epiparameter}
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If you see an error when installing {epiparameter}, try this alternative code:
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```r
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if(!require("devtools")) install.packages("devtools")
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devtools::install_github("epiverse-trace/epiparameter")
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```
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You should update **all of the packages** required for the tutorial, even if you installed them relatively recently. New versions bring improvements and important bug fixes.
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When the installation has finished, you can try to load the packages by pasting the following code into the console:
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The data files for the tutorial can be downloaded manually here:
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- <https://epiverse-trace.github.io/tutorials/data/ebola_cases.csv>
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- <https://epiverse-trace.github.io/tutorials-middle/data/ebola_cases.csv>
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## Your Questions
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