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COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown
Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outb...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343837/ https://www.ncbi.nlm.nih.gov/pubmed/32641758 http://dx.doi.org/10.1038/s41597-020-00575-2 |
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author | Pepe, Emanuele Bajardi, Paolo Gauvin, Laetitia Privitera, Filippo Lake, Brennan Cattuto, Ciro Tizzoni, Michele |
author_facet | Pepe, Emanuele Bajardi, Paolo Gauvin, Laetitia Privitera, Filippo Lake, Brennan Cattuto, Ciro Tizzoni, Michele |
author_sort | Pepe, Emanuele |
collection | PubMed |
description | Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outbreak and delaying the epidemic peak. On March 12, the government imposed a national lockdown. To aid the evaluation of the impact of interventions, we present daily time-series of three different aggregated mobility metrics: the origin-destination movements between Italian provinces, the radius of gyration, and the average degree of a spatial proximity network. All metrics were computed by processing a large-scale dataset of anonymously shared positions of about 170,000 de-identified smartphone users before and during the outbreak, at the sub-national scale. This dataset can help to monitor the impact of the lockdown on the epidemic trajectory and inform future public health decision making. |
format | Online Article Text |
id | pubmed-7343837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73438372020-07-13 COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown Pepe, Emanuele Bajardi, Paolo Gauvin, Laetitia Privitera, Filippo Lake, Brennan Cattuto, Ciro Tizzoni, Michele Sci Data Data Descriptor Italy has been severely affected by the COVID-19 pandemic, reporting the highest death toll in Europe as of April 2020. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outbreak and delaying the epidemic peak. On March 12, the government imposed a national lockdown. To aid the evaluation of the impact of interventions, we present daily time-series of three different aggregated mobility metrics: the origin-destination movements between Italian provinces, the radius of gyration, and the average degree of a spatial proximity network. All metrics were computed by processing a large-scale dataset of anonymously shared positions of about 170,000 de-identified smartphone users before and during the outbreak, at the sub-national scale. This dataset can help to monitor the impact of the lockdown on the epidemic trajectory and inform future public health decision making. Nature Publishing Group UK 2020-07-08 /pmc/articles/PMC7343837/ /pubmed/32641758 http://dx.doi.org/10.1038/s41597-020-00575-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Pepe, Emanuele Bajardi, Paolo Gauvin, Laetitia Privitera, Filippo Lake, Brennan Cattuto, Ciro Tizzoni, Michele COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown |
title | COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown |
title_full | COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown |
title_fullStr | COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown |
title_full_unstemmed | COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown |
title_short | COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown |
title_sort | covid-19 outbreak response, a dataset to assess mobility changes in italy following national lockdown |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343837/ https://www.ncbi.nlm.nih.gov/pubmed/32641758 http://dx.doi.org/10.1038/s41597-020-00575-2 |
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