move index page to setup

index.md

@@ -6,38 +6,3 @@ This is an [Epiverse-TRACE][epiversetrace] tutorial built with [The Carpentries
 
 [epiversetrace]: https://epiverse-trace.github.io/
 [workbench]: https://carpentries.github.io/workbench/
-
-## Epiverse-TRACE tutorials
-
-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.
-
-The tutorials are built around the workflow of outbreak analysis split into three stages : early tasks, middle tasks and late tasks.
-
-![An overview of the tutorial topics](https://epiverse-trace.github.io/task_pipeline-minimal.svg)
-
-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.
-
-Each episode contains:
-
-+ **Overview** : describes what questions will be answered and what are the objectives of the episode.
-+ **Prerequisites**: describes what episodes/packages need to be covered before the current episode.
-+ **Example R code** : work through the episodes on your own computer using the example R code.
-+ **Challenges** : complete challenges to test your understanding.
-+ **Explainers** : add to your understanding of mathematical and modelling concepts with the explainer boxes.
-
-Also check out the [glossary](../reference.md) for any terms you may be unfamiliar with. 
-
-## Related projects
-
-+ 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/).
-+ [How-to guides](https://epiverse-trace.github.io/howto/) : reproducible recipes with concrete steps to solve specific Outbreak Analysis questions.
-+ [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.
-+ *COMING SOON* case studies : reproducible case-studies of outbreak data analysis tasks using R packages.
-
-
-
-This tutorial was built with [The Carpentries Workbench][workbench]. 
-
-
-[workbench]: https://carpentries.github.io/sandpaper-docs
-

learners/setup.md

@@ -4,6 +4,38 @@ title: Setup
 
 ## Motivation
 
+**Outbreaks** appear with different diseases and in different contexts, but what all of them have in common are the key public health **questions** ([Cori et al. 2017](https://royalsocietypublishing.org/doi/10.1098/rstb.2016.0371#d1e605)). Common questions also require common data analysis **tasks**.
+
+Epiverse-TRACE's aim is to provide an 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.
+
+### Epiverse-TRACE tutorials
+
+The tutorials are built around the workflow of outbreak analysis split into three stages: **Early tasks**, **Middle tasks** and **Late tasks**.
+
+![An overview of the tutorial topics](https://epiverse-trace.github.io/task_pipeline-minimal.svg)
+
+Each task has its own tutorial website. Task topics consist of one or more episodes.
+
+| [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/) |
+|---|---|---|
+| Reading and cleaning case data | Real-time analysis and forecasting | Scenario modelling |
+| 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. |
+
+Each episode contains:
+
++ **Overview** : describes what questions will be answered and what are the objectives of the episode.
++ **Prerequisites**: describes what episodes/packages need to be covered before the current episode.
++ **Example R code** : work through the episodes on your own computer using the example R code.
++ **Challenges** : complete challenges to test your understanding.
++ **Explainers** : add to your understanding of mathematical and modelling concepts with the explainer boxes.
+
+Also check out the [glossary](../reference.md) for any terms you may be unfamiliar with.
+
+### Epiverse-TRACE R packages
+
+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.
+
+![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.png)
 
 :::::::::::::::::::::::::::: prereq