7548922
doi
10.5281/zenodo.7548922
oai:zenodo.org:7548922
Moroni, Claudio
University of Turin
Piedmont COVID-19 Data Modelling and Management
Monticone, Pietro
University of Turin
url:https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/v1.0.0
url:https://www.csipiemonte.it/en/project/piedmont-region-covid-19-platform
url:https://github.com/regione-piemonte/gescovid19
url:https://www.masteradabi.it/images/CSI_Piattaforma_COVID_20210308_V2.pdf
doi:10.5281/zenodo.6564434
doi:10.5281/zenodo.5725301
doi:10.19191/EP20.5-6.S2.105
url:https://epiprev.it/5814
url:https://www.doi.org/10.1017/dap.2021.25
doi:10.1098/rsta.2021.0127
doi:10.1098/rsta.2021.0117
doi:10.1136/bmjgh-2021-005542
doi:10.1016/j.epidem.2022.100612
info:eu-repo/semantics/openAccess
MIT License
https://opensource.org/licenses/MIT
COVID-19
SARS-CoV-2
Epidemiology
Surveillance
Time Series
Pandemic Preparedness
Surveillance Data
Time Series
Data Modelling
Data Management
Infectious Diseases
COVID-19 Italy
Piedmont
<p><strong>OVERVIEW</strong></p>
<p>This repository contains the <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/main/src">code</a>, <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/main/docs">documentation manual</a> and <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/main/images/plots">data visualisations</a> for the design and operation of the Piedmont COVID-19 surveillance data modelling and management pipeline developed in collaboration with the Piedmont Epidemiological Service (<a href="https://www.epi.piemonte.it/">SEPI</a>).</p>
<p>For privacy purposes all the data in this repository are either <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/main/data/fake-input"><code>fake</code></a> (i.e. invented) or <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/main/data/synthetic-input"><code>synthetic</code></a> (i.e. simulated) in order to be structurally equivalent to the original individual-level data to accurately showcase the functionalities of the data modelling and management pipeline.</p>
<p>The only reference to the real data can be found in the plots located in the <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/main/images/plots/real-output"><code>images/real-output</code></a> folder.</p>
<p><strong>HOW TO ACCESS</strong></p>
<p>If you would like to access the real Piedmont COVID-19 surveillance data covering the year 2020 for your research project (i.e. sequences, incidences and empirical time delay distributions visualised <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/main/images/plots/real-output">here</a>), please feel free to contact us by sending us an <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/blob/main/inphyt@gmail.com">email</a>.</p>
<p><strong>HOW TO CITE</strong></p>
<p>If you use these contents in your work, please cite this repository using the metadata in <a href="https://github.com/UniTo-SEPI/COVID-19_Piedmont/blob/main/CITATION.bib"><code>CITATION.bib</code></a>.</p>
<p><strong>REFERENCES</strong></p>
<p><strong>Data</strong></p>
<ol>
<li>CSI Piemonte (2020) <a href="https://www.csipiemonte.it/en/project/piedmont-region-covid-19-platform">Piedmont Region COVID-19 Data Management Platform</a>. <em>CSI Piemonte</em></li>
<li>CSI Piemonte (2020) <a href="https://github.com/regione-piemonte/gescovid19">GESCOVID19: COVID-19 Data Management Platform in Piedmont</a>. <em>GitHub</em></li>
<li>Leproni (2021) <a href="https://www.masteradabi.it/images/CSI_Piattaforma_COVID_20210308_V2.pdf">The Piedmont Region COVID-19 Platform</a>. <em>CSI Piemonte</em></li>
<li>Moroni and Monticone (2022) <a href="https://doi.org/10.5281/zenodo.5748141">Italian COVID-19 Integrated Surveillance Dataset</a>. <em>Zenodo</em></li>
</ol>
<p><strong>Software</strong></p>
<ol>
<li>Monticone and Moroni (2022) <a href="https://doi.org/10.5281/zenodo.6564434">ICD_GEMs.jl: A Julia Package to Translate Between ICD-9 and ICD-10 Codes</a>. <em>Zenodo</em></li>
<li>Monticone and Moroni (2022) <a href="https://doi.org/10.5281/zenodo.5725301">UnrollingAverages.jl: A Julia Package to Deconvolve Time Series Data.</a>. <em>Zenodo</em></li>
</ol>
<p><strong>Papers</strong></p>
<ul>
<li>Del Manso et al. (2020) <a href="https://doi.org/10.19191/EP20.5-6.S2.105">COVID-19 integrated surveillance in Italy: outputs and related activities</a>. <em>Epidemiologia & Prevenzione</em></li>
<li>Milani et al. (2021). <a href="https://epiprev.it/5814">Characteristics of patients affecting the duration of positivity at SARS-CoV-2: a cohort analysis of the first wave of epidemic in Italy</a>. <em>Epidemiologia & Prevenzione</em></li>
<li>Starnini et al. (2021) <a href="https://www.doi.org/10.1017/dap.2021.25">Impact of data accuracy on the evaluation of COVID-19 mitigation policies</a>. <em>Data & Policy</em>, 3, E28.</li>
<li>Zhang et al. (2021) <a href="https://doi.org/10.1098/rsta.2021.0127">Data science approaches to confronting the COVID-19 pandemic: a narrative review</a>. <em>Philosophical Transactions of the Royal Society A</em></li>
<li>Vasiliauskaite et al. (2021) <a href="https://doi.org/10.1098/rsta.2021.0117">On some fundamental challenges in monitoring epidemics</a>. <em>Philosophical Transactions of the Royal Society A</em></li>
<li>Badker et al. (2021) <a href="http://dx.doi.org/10.1136/bmjgh-2021-005542">Challenges in reported COVID-19 data: best practices and recommendations for future epidemics</a>. <em>BMJ Global Health</em></li>
<li>Shadbolt et al. (2022) <a href="https://doi.org/10.1016/j.epidem.2022.100612">The Challenges of Data in Future Pandemics</a>. <em>Epidemics</em></li>
</ul>
Zenodo
2023-01-18
info:eu-repo/semantics/other
7548921
v1.0.0
1674181641.625748
130919915
md5:1a841436e0e29eead599adec84340c31
https://zenodo.org/records/7548922/files/UniTo-SEPI/COVID-19_Piedmont-v1.0.0.zip
public
https://github.com/UniTo-SEPI/COVID-19_Piedmont/tree/v1.0.0
Is supplement to
url
https://www.csipiemonte.it/en/project/piedmont-region-covid-19-platform
Cites
url
https://github.com/regione-piemonte/gescovid19
Cites
url
https://www.masteradabi.it/images/CSI_Piattaforma_COVID_20210308_V2.pdf
Cites
url
10.5281/zenodo.6564434
Cites
doi
10.5281/zenodo.5725301
Cites
doi
10.19191/EP20.5-6.S2.105
Cites
doi
https://epiprev.it/5814
Cites
url
https://www.doi.org/10.1017/dap.2021.25
Cites
url
10.1098/rsta.2021.0127
Cites
doi
10.1098/rsta.2021.0117
Cites
doi
10.1136/bmjgh-2021-005542
Cites
doi
10.1016/j.epidem.2022.100612
Cites
doi
10.5281/zenodo.7548921
isVersionOf
doi