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https://github.com/epiforecasts/euro-hub-ensemble

Analysis of ensemble methods to aggregate Covid-19 forecasts across Europe.
https://github.com/epiforecasts/euro-hub-ensemble

article covid-19 covid19-forecast-hub-europe forecast-hub

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Analysis of ensemble methods to aggregate Covid-19 forecasts across Europe.

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README

          

# Predictive performance of multi-model ensemble forecasts of Covid-19 across European nations
[![DOI](https://zenodo.org/badge/434779787.svg)](https://zenodo.org/badge/latestdoi/434779787)

### Project guide

This repository provides code and data for analysing COVID-19 forecasts from the [European COVID-19 Forecast Hub](https://github.com/covid19-forecast-hub-europe/covid19-forecast-hub-europe). It is associated with the paper, "Predictive performance of multi-model ensemble forecasts of Covid-19 across European nations" (Sherratt and others, 2023).

- The paper is now published and available at [eLife](https://elifesciences.org/articles/81916) or [medRxiv](https://www.medrxiv.org/content/10.1101/2022.06.16.22276024).
- All code is open source and anyone is welcome to freely use and adapt any part of this codebase for any purpose.

You can find here:

- The latest manuscript in [pdf](output/latest.pdf) or [Rmarkdown](analysis/latest.Rmd)
- A [modular codebase](code) for downloading and summarising data from the European Forecast Hub

All feedback is very welcome - just open an [Issue](https://github.com/covid19-forecast-hub-europe/euro-hub-ensemble/issues) with your comments. We would especially appreciate thoughts on:

- Bugs or potential improvements to code or documentation
- Ease of use as an example for extracting, transforming, and loading Forecast Hub data (particularly from the perspective of users who are less/un-familiar with using data stored on Github)
- Further thoughts and priorities for the analysis of COVID-19 individual and ensemble forecasts

---

### Workflow

A brief guide to the files in this repository:

- [data](data): key datasets used in this study, including evaluation scores for ensemble and individual models downloaded from the [European COVID-19 Forecast Hub repository](https://github.com/covid19-forecast-hub-europe/covid19-forecast-hub-europe)
- [code](code#readme): data extraction, loading and transformation code used to support the main [analysis](analysis/latest.Rmd)
- [load](code/load): functions to download forecasts and evaluation scores from the Forecast Hub Github repository
- [summarise](code/summarise): uses the `load` functions to save key [datasets](data) and create figures and summary statistics used in the [analysis](analysis)
- [analysis](analysis#readme): raw `rmarkdown` files, containing blended text and code to produce the `output`
- [output](output#readme): The [latest manuscript](output/latest.pdf) and [supplement](output/supplementary.pdf), plus previous dated drafts of the text

Each folder has a README with a more detailed guide to its contents.

#### Code

All code is in R, tested in version 4.2.1.

The [DESCRIPTION](DESCRIPTION) lists packages used in the project. They are all available on CRAN, except `covidHubUtils`, the package used to load observed data. Install this with:
```
remotes::install_github("reichlab/covidHubUtils")
```

R session info

```
> sessionInfo()

R version 4.2.1 (2022-06-23 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22000)

Matrix products: default

locale:
[1] LC_COLLATE=English_United Kingdom.utf8
[2] LC_CTYPE=English_United Kingdom.utf8
[3] LC_MONETARY=English_United Kingdom.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United Kingdom.utf8

attached base packages:
[1] stats graphics grDevices utils datasets
[6] methods base

loaded via a namespace (and not attached):
[1] bookdown_0.29 digest_0.6.29 jsonlite_1.8.0
[4] magrittr_2.0.3 evaluate_0.16 rlang_1.0.4
[7] cli_3.3.0 renv_0.15.5 rstudioapi_0.13
[10] rmarkdown_2.14 tools_4.2.1 purrr_0.3.4
[13] xfun_0.32 yaml_2.3.5 fastmap_1.1.0
[16] compiler_4.2.1 htmltools_0.5.3 knitr_1.39
```