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Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach
BACKGROUND: From February 2020, both urban and rural Ireland witnessed the rapid proliferation of the COVID-19 disease throughout its counties. During this period, the national COVID-19 responses included stay-at-home directives issued by the state, subject to varying levels of enforcement. METHODS:...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419690/ https://www.ncbi.nlm.nih.gov/pubmed/35083428 http://dx.doi.org/10.1016/j.array.2021.100075 |
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author | Irini, Furxhi Kia, Arash Negahdari Shannon, Darren Jannusch, Tim Murphy, Finbarr Sheehan, Barry |
author_facet | Irini, Furxhi Kia, Arash Negahdari Shannon, Darren Jannusch, Tim Murphy, Finbarr Sheehan, Barry |
author_sort | Irini, Furxhi |
collection | PubMed |
description | BACKGROUND: From February 2020, both urban and rural Ireland witnessed the rapid proliferation of the COVID-19 disease throughout its counties. During this period, the national COVID-19 responses included stay-at-home directives issued by the state, subject to varying levels of enforcement. METHODS: In this paper, we present a new method to assess and rank the causes of Ireland COVID-19 deaths as it relates to mobility activities within each county provided by Google while taking into consideration the epidemiological confirmed positive cases reported per county. We used a network structure and rank propagation modelling approach using Personalised PageRank to reveal the importance of each mobility category linked to cases and deaths. Then a novel feature-selection method using relative prominent factors finds important features related to each county's death. Finally, we clustered the counties based on features selected with the network results using a customised network clustering algorithm for the research problem. FINDINGS: Our analysis reveals that the most important mobility trend categories that exhibit the strongest association to COVID-19 cases and deaths include retail and recreation and workplaces. This is the first time a network structure and rank propagation modelling approach has been used to link COVID-19 data to mobility patterns. The infection determinants landscape illustrated by the network results aligns soundly with county socio-economic and demographic features. The novel feature selection and clustering method presented clusters useful to policymakers, managers of the health sector, politicians and even sociologists. Finally, each county has a different impact on the national total. |
format | Online Article Text |
id | pubmed-8419690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Authors. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84196902021-09-07 Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach Irini, Furxhi Kia, Arash Negahdari Shannon, Darren Jannusch, Tim Murphy, Finbarr Sheehan, Barry Array (N Y) Article BACKGROUND: From February 2020, both urban and rural Ireland witnessed the rapid proliferation of the COVID-19 disease throughout its counties. During this period, the national COVID-19 responses included stay-at-home directives issued by the state, subject to varying levels of enforcement. METHODS: In this paper, we present a new method to assess and rank the causes of Ireland COVID-19 deaths as it relates to mobility activities within each county provided by Google while taking into consideration the epidemiological confirmed positive cases reported per county. We used a network structure and rank propagation modelling approach using Personalised PageRank to reveal the importance of each mobility category linked to cases and deaths. Then a novel feature-selection method using relative prominent factors finds important features related to each county's death. Finally, we clustered the counties based on features selected with the network results using a customised network clustering algorithm for the research problem. FINDINGS: Our analysis reveals that the most important mobility trend categories that exhibit the strongest association to COVID-19 cases and deaths include retail and recreation and workplaces. This is the first time a network structure and rank propagation modelling approach has been used to link COVID-19 data to mobility patterns. The infection determinants landscape illustrated by the network results aligns soundly with county socio-economic and demographic features. The novel feature selection and clustering method presented clusters useful to policymakers, managers of the health sector, politicians and even sociologists. Finally, each county has a different impact on the national total. The Authors. Published by Elsevier Inc. 2021-09 2021-07-07 /pmc/articles/PMC8419690/ /pubmed/35083428 http://dx.doi.org/10.1016/j.array.2021.100075 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Irini, Furxhi Kia, Arash Negahdari Shannon, Darren Jannusch, Tim Murphy, Finbarr Sheehan, Barry Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach |
title | Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach |
title_full | Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach |
title_fullStr | Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach |
title_full_unstemmed | Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach |
title_short | Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach |
title_sort | associations between mobility patterns and covid-19 deaths during the pandemic: a network structure and rank propagation modelling approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419690/ https://www.ncbi.nlm.nih.gov/pubmed/35083428 http://dx.doi.org/10.1016/j.array.2021.100075 |
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