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

Abstract 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...

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Autores principales:	Corentin Cot, Giacomo Cacciapaglia, Francesco Sannino
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/17102d800341415bafc9f8b66a59c882
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id	oai:doaj.org-article:17102d800341415bafc9f8b66a59c882
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spelling	oai:doaj.org-article:17102d800341415bafc9f8b66a59c8822021-12-02T14:21:57ZMining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing10.1038/s41598-021-83441-42045-2322https://doaj.org/article/17102d800341415bafc9f8b66a59c8822021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83441-4https://doaj.org/toc/2045-2322Abstract 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.Corentin CotGiacomo CacciapagliaFrancesco SanninoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Corentin Cot Giacomo Cacciapaglia Francesco Sannino Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing
description	Abstract 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.
format	article
author	Corentin Cot Giacomo Cacciapaglia Francesco Sannino
author_facet	Corentin Cot Giacomo Cacciapaglia Francesco Sannino
author_sort	Corentin Cot
title	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_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_sort	mining google and apple mobility data: temporal anatomy for covid-19 social distancing
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/17102d800341415bafc9f8b66a59c882
work_keys_str_mv	AT corentincot mininggoogleandapplemobilitydatatemporalanatomyforcovid19socialdistancing AT giacomocacciapaglia mininggoogleandapplemobilitydatatemporalanatomyforcovid19socialdistancing AT francescosannino mininggoogleandapplemobilitydatatemporalanatomyforcovid19socialdistancing
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Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

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