Table of contents

Here there are a few topics covered within this repo. A more indeep explanation of resuls and methodologies as well as the tech stack is offered in the project documentation under major revision

• Description
• Installation
• Usage
• Contribute and Conduct
• Sponsors
• License

Description

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The project is articulated into 3 parts:

• set up a new KPI i.e. Indicatore di Stress Regionale
• build ab ETL (Extraction, Trasnformation & Loading) pipeline sourcing and merging (then computing Indicatore di Stress) 3 data Sources
• visualize & design a frontend with [DataWrapper])(https://www.datawrapper.de/) based on aggregated data

the newly created Indicatore di Stress will be measuring the overall stress undertaken by the SSN (Servizio Sanitario Nazionale e.g. italian NHS) which results in a combination of the Vaccination and the Incidence effects computed per region. Both of the 2 dimensions can reflect hospital Saturation and define criteria according to which regions are labelled as either yellow, orange or red zones (Zona Gialla, Zona Arancione e Zona Rossa), in compliance with the most recent orders (D.L. 52/2021). This presumably will help decision makers have a neat undestranding of the current situation and an updated perspective on future scenarios.

The etl pipeline joins and cleans up 3 data sources:

• pcm-dpc, dati regioni
• pcm-dpc, dati statistici di riferimento
• COVID 19 open data vaccini, somministrazioni vaccini

Data is extracted, cleanded and aggregated every 6 hours. At the end of the pipeline within the ./data folder the output file is written in a .csv format. Methodology and software choices are outlined in the documentation which is currently under major revision

Visualizations (barcharts, arrowplots, custom tables and more) are made with Datawrapper whose data source points to the urls at ./data/data-graph.

Installation

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You might have noticed the *Back to top** button(if not, please notice, it’s right there above!). This is a good idea because it makes this README easy to navigate.* If you are willing to install this project on your machine the recommendend choice is to git pull it from github:

git init

git clone https://github.com/Data-Network-Lab/indicatore_zona_gialla.git

Then once you have cloned this repo on your machine you might execute:

``` r if(!require(renv)){ install.packages("renv") }

renv::restore() ```

Author Disclaimer: renv is not a panacea for reproducibility, as many people believe. Reproducible projects can be made easier with this tool, which records the versions of R + R packages being used in a project and provides tools for reinstalling those packages in a project to their declared versions.

Usage

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The whole repository data as well as cleaning process can be utilized under the license prescription.

Contribute and Conduct

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Please note that the indicatore_zona_gialla project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Sponsors

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The project is sponsored by ALTEMS (Alta Scuola di Economia e Management dei Sistemi Sanitari ), but if you too are willing to support our open source work tap the button above or simply donate at the link you find in the upper right hand site of this repo (i.e. DN donations). If you are interested to be contacted for future works or collaboration please reach out at @ datanetworkxyz@gmail.com for any sort of enquiry or question you might bump into.

License

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Please visit the LICENSE.md file.