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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.
  • Irini F; Transgero Limited, Newcastle West, Limerick, Ireland.
  • Kia AN; Kemmy Business School, University of Limerick, Ireland.
  • Shannon D; Kemmy Business School, University of Limerick, Ireland.
  • Jannusch T; Kemmy Business School, University of Limerick, Ireland.
  • Murphy F; Kemmy Business School, University of Limerick, Ireland.
  • Sheehan B; Institut for Insurance Studies, TH, Köln, Germany.
Array (N Y) ; 11: 100075, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1300624
ABSTRACT

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.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Array (N Y) Year: 2021 Document Type: Article Affiliation country: J.array.2021.100075

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Array (N Y) Year: 2021 Document Type: Article Affiliation country: J.array.2021.100075