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:...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-09-01
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| Series: | Array |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590005621000230 |
| _version_ | 1819016098224275456 |
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| author | Furxhi Irini Arash Negahdari Kia Darren Shannon Tim Jannusch Finbarr Murphy Barry Sheehan |
| author_facet | Furxhi Irini Arash Negahdari Kia Darren Shannon Tim Jannusch Finbarr Murphy Barry Sheehan |
| author_sort | Furxhi Irini |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-21T02:42:13Z |
| format | Article |
| id | doaj.art-97763387590e4740a2dfadb2a9b1a73d |
| institution | Directory Open Access Journal |
| issn | 2590-0056 |
| language | English |
| last_indexed | 2024-12-21T02:42:13Z |
| publishDate | 2021-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Array |
| spelling | doaj.art-97763387590e4740a2dfadb2a9b1a73d2022-12-21T19:18:40ZengElsevierArray2590-00562021-09-0111100075Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approachFurxhi Irini0Arash Negahdari Kia1Darren Shannon2Tim Jannusch3Finbarr Murphy4Barry Sheehan5Transgero Limited, Newcastle West, Limerick, Ireland; Kemmy Business School, University of Limerick, IrelandKemmy Business School, University of Limerick, Ireland; Corresponding author.Kemmy Business School, University of Limerick, IrelandKemmy Business School, University of Limerick, Ireland; Institut for Insurance Studies, TH, Köln, GermanyKemmy Business School, University of Limerick, Ireland; Transgero Limited, Newcastle West, Limerick, IrelandKemmy Business School, University of Limerick, IrelandBackground: 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.http://www.sciencedirect.com/science/article/pii/S2590005621000230COVID-19Mobility reportsPersonalised PageRankNetwork modellingFeature selectionHierarchical clustering |
| spellingShingle | Furxhi Irini Arash Negahdari Kia Darren Shannon Tim Jannusch Finbarr Murphy Barry Sheehan Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach Array COVID-19 Mobility reports Personalised PageRank Network modelling Feature selection Hierarchical clustering |
| 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 | COVID-19 Mobility reports Personalised PageRank Network modelling Feature selection Hierarchical clustering |
| url | http://www.sciencedirect.com/science/article/pii/S2590005621000230 |
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