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Big data insight on global mobility during the Covid-19 pandemic lockdown
The Covid-19 pandemic that began in the city of Wuhan in China has caused a huge number of deaths worldwide. Countries have introduced spatial restrictions on movement and social distancing in response to the rapid rate of SARS-Cov-2 transmission among its populations. Research originality lies in t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170440/ https://www.ncbi.nlm.nih.gov/pubmed/34094812 http://dx.doi.org/10.1186/s40537-021-00474-2 |
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author | Sadowski, Adam Galar, Zbigniew Walasek, Robert Zimon, Grzegorz Engelseth, Per |
author_facet | Sadowski, Adam Galar, Zbigniew Walasek, Robert Zimon, Grzegorz Engelseth, Per |
author_sort | Sadowski, Adam |
collection | PubMed |
description | The Covid-19 pandemic that began in the city of Wuhan in China has caused a huge number of deaths worldwide. Countries have introduced spatial restrictions on movement and social distancing in response to the rapid rate of SARS-Cov-2 transmission among its populations. Research originality lies in the taken global perspective revealing indication of significant relationships between changes in mobility and the number of Covid-19 cases. The study uncovers a time offset between the two applied databases, Google Mobility and John Hopkins University, influencing correlations between mobility and pandemic development. Analyses reveals a link between the introduction of lockdown and the number of new Covid-19 cases. Types of mobility with the most significant impact on the development of the pandemic are “retail and recreation areas", "transit stations", "workplaces" "groceries and pharmacies”. The difference in the correlation between the lockdown introduced and the number of SARS-COV-2 cases is 81%, when using a 14-day weighted average compared to the 7-day average. Moreover, the study reveals a strong geographical diversity in human mobility and its impact on the number of new Covid-19 cases. |
format | Online Article Text |
id | pubmed-8170440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-81704402021-06-02 Big data insight on global mobility during the Covid-19 pandemic lockdown Sadowski, Adam Galar, Zbigniew Walasek, Robert Zimon, Grzegorz Engelseth, Per J Big Data Research The Covid-19 pandemic that began in the city of Wuhan in China has caused a huge number of deaths worldwide. Countries have introduced spatial restrictions on movement and social distancing in response to the rapid rate of SARS-Cov-2 transmission among its populations. Research originality lies in the taken global perspective revealing indication of significant relationships between changes in mobility and the number of Covid-19 cases. The study uncovers a time offset between the two applied databases, Google Mobility and John Hopkins University, influencing correlations between mobility and pandemic development. Analyses reveals a link between the introduction of lockdown and the number of new Covid-19 cases. Types of mobility with the most significant impact on the development of the pandemic are “retail and recreation areas", "transit stations", "workplaces" "groceries and pharmacies”. The difference in the correlation between the lockdown introduced and the number of SARS-COV-2 cases is 81%, when using a 14-day weighted average compared to the 7-day average. Moreover, the study reveals a strong geographical diversity in human mobility and its impact on the number of new Covid-19 cases. Springer International Publishing 2021-06-02 2021 /pmc/articles/PMC8170440/ /pubmed/34094812 http://dx.doi.org/10.1186/s40537-021-00474-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Sadowski, Adam Galar, Zbigniew Walasek, Robert Zimon, Grzegorz Engelseth, Per Big data insight on global mobility during the Covid-19 pandemic lockdown |
title | Big data insight on global mobility during the Covid-19 pandemic lockdown |
title_full | Big data insight on global mobility during the Covid-19 pandemic lockdown |
title_fullStr | Big data insight on global mobility during the Covid-19 pandemic lockdown |
title_full_unstemmed | Big data insight on global mobility during the Covid-19 pandemic lockdown |
title_short | Big data insight on global mobility during the Covid-19 pandemic lockdown |
title_sort | big data insight on global mobility during the covid-19 pandemic lockdown |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170440/ https://www.ncbi.nlm.nih.gov/pubmed/34094812 http://dx.doi.org/10.1186/s40537-021-00474-2 |
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