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Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

We employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Appl...

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Autores principales: Cot, Corentin, Cacciapaglia, Giacomo, Sannino, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892828/
https://www.ncbi.nlm.nih.gov/pubmed/33602967
http://dx.doi.org/10.1038/s41598-021-83441-4
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author Cot, Corentin
Cacciapaglia, Giacomo
Sannino, Francesco
author_facet Cot, Corentin
Cacciapaglia, Giacomo
Sannino, Francesco
author_sort Cot, Corentin
collection PubMed
description We employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.
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spelling pubmed-78928282021-02-23 Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing Cot, Corentin Cacciapaglia, Giacomo Sannino, Francesco Sci Rep Article We employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US. Nature Publishing Group UK 2021-02-18 /pmc/articles/PMC7892828/ /pubmed/33602967 http://dx.doi.org/10.1038/s41598-021-83441-4 Text en © The Author(s) 2021 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Cot, Corentin
Cacciapaglia, Giacomo
Sannino, Francesco
Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
title Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
title_full Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
title_fullStr Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
title_full_unstemmed Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
title_short Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
title_sort mining google and apple mobility data: temporal anatomy for covid-19 social distancing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892828/
https://www.ncbi.nlm.nih.gov/pubmed/33602967
http://dx.doi.org/10.1038/s41598-021-83441-4
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