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Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy
Italy was one of the European countries most afflicted by the COVID-19 pandemic. From 2020 to 2022, Italy adopted strong containment measures against the COVID-19 epidemic and then started an important vaccination campaign. Here, we extended previous work by applying the COVID-19 Community Temporal...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460631/ https://www.ncbi.nlm.nih.gov/pubmed/35997341 http://dx.doi.org/10.3390/biotech11030033 |
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author | Milano, Marianna Agapito, Giuseppe Cannataro, Mario |
author_facet | Milano, Marianna Agapito, Giuseppe Cannataro, Mario |
author_sort | Milano, Marianna |
collection | PubMed |
description | Italy was one of the European countries most afflicted by the COVID-19 pandemic. From 2020 to 2022, Italy adopted strong containment measures against the COVID-19 epidemic and then started an important vaccination campaign. Here, we extended previous work by applying the COVID-19 Community Temporal Visualizer (CCTV) methodology to Italian COVID-19 data related to 2020, 2021, and five months of 2022. The aim of this work was to evaluate how Italy reacted to the pandemic in the first two waves of COVID-19, in which only containment measures such as the lockdown had been adopted, in the months following the start of the vaccination campaign, the months with the mildest weather, and the months affected by the new COVID-19 variants. This assessment was conducted by observing the behavior of single regions. CCTV methodology allows us to map the similarities in the behavior of Italian regions on a graph and use a community detection algorithm to visualize and analyze the spatio-temporal evolution of data. The results depict that the communities formed by Italian regions change with respect to the ten data measures and time. |
format | Online Article Text |
id | pubmed-9460631 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94606312022-09-10 Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy Milano, Marianna Agapito, Giuseppe Cannataro, Mario BioTech (Basel) Article Italy was one of the European countries most afflicted by the COVID-19 pandemic. From 2020 to 2022, Italy adopted strong containment measures against the COVID-19 epidemic and then started an important vaccination campaign. Here, we extended previous work by applying the COVID-19 Community Temporal Visualizer (CCTV) methodology to Italian COVID-19 data related to 2020, 2021, and five months of 2022. The aim of this work was to evaluate how Italy reacted to the pandemic in the first two waves of COVID-19, in which only containment measures such as the lockdown had been adopted, in the months following the start of the vaccination campaign, the months with the mildest weather, and the months affected by the new COVID-19 variants. This assessment was conducted by observing the behavior of single regions. CCTV methodology allows us to map the similarities in the behavior of Italian regions on a graph and use a community detection algorithm to visualize and analyze the spatio-temporal evolution of data. The results depict that the communities formed by Italian regions change with respect to the ten data measures and time. MDPI 2022-08-11 /pmc/articles/PMC9460631/ /pubmed/35997341 http://dx.doi.org/10.3390/biotech11030033 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Milano, Marianna Agapito, Giuseppe Cannataro, Mario Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy |
title | Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy |
title_full | Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy |
title_fullStr | Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy |
title_full_unstemmed | Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy |
title_short | Application of CCTV Methodology to Analyze COVID-19 Evolution in Italy |
title_sort | application of cctv methodology to analyze covid-19 evolution in italy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460631/ https://www.ncbi.nlm.nih.gov/pubmed/35997341 http://dx.doi.org/10.3390/biotech11030033 |
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