vaccc19de

⚠️ we have stopped the development of the package and the accompanying dashboard. Functions in this package most likely do not work anymore. ⚠️

Why are we retiring the package / dashboard?

This project was a spontaneous collaboration between Fabio and me when we realized at the end of December 2020 that

data was not published as time series data but instead was being overwritten each day, i.e. no history was available to the public
no official dashboard or visualization existed

Re 1) there is this daily-updated archive which we have used for the dashboard in the past weeks

Re 2) Although the official dashboard is lacking in certain areas (e.g. no Bundesland-level analyses), it provides a good overview over the progress of the vaccinations.

Finally, given that the constantly changing format and quality of the Excel download requires constant adaptation of the code, we cannot realistically guarantee the integrity and correctness of our dashboard with our limited time resources.

The goal of vaccc19de (vaccinations covid 19 deutschland) was to provide functions to easily get and extract data on the progress of vaccinations in German Bundesländer that is provided daily by the Robert-Koch-Institut (RKI) on this page. The package was used to automatically collect data in the accompanying vaccc19de_rki_data repository.

The package was used in the vaccc19de_dashboard repository where you can also find the current version of the following two datasets:

Please refer to the README of the vaccc19de_dashboard for more information on the data.

Installation

vaccc19de is not on CRAN. You can install the development version from GitHub with:

remotes::install_github("friep/vaccc19de")

Usage

Download the currently available data from the RKI:

library(vaccc19de)
path <- rki_download_xlsx() # returns path to xlsx invisibly
# rki_extract_sheet_csvs(path) # optional to store the raw sheets as csvs
cumulative <- rki_extract_cumulative_data(path)

Or download the full time series from GitHub:

cumulative_ts <- rki_download_cumulative_ts()
cumulative_ts

“decumulate” it / create the time series of differences:

diffs_ts <- rki_extract_diffs(cumulative_ts)
diffs_ts

Finally, you can also download the “decumulated” data directly from GitHub:

cumulative_ts <- rki_download_diffs_ts()

Roadmap

function to “longify” the data by indication
more robust data cleaning

Contribute

Before filing an issue, please check the list of issues. When forking, please create your PR against the dev branch.

Licensing information

Data in folder tests/testthat/test_data was downloaded from the Robert Koch Institut’s website on 2020-12-30: https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Daten/Impfquotenmonitoring.html

pr130 / vaccc19de