Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach
| Autor: | Tim Jannusch, Arash Negahdari Kia, Furxhi Irini, Barry Sheehan, Darren Shannon, Finbarr Murphy |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Network modelling
Computer engineering. Computer hardware General Computer Science Rank (computer programming) COVID-19 Feature selection QA75.5-76.95 Article Hierarchical clustering law.invention TK7885-7895 Geography PageRank Mobility reports law Electronic computers. Computer science Pandemic Regional science Enforcement Cluster analysis Recreation Personalised PageRank |
| Zdroj: | Array, Vol 11, Iss, Pp 100075-(2021) Array |
| ISSN: | 2590-0056 |
| Popis: | 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. Graphical abstract Image 1 |
| Databáze: | OpenAIRE |
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