TY  - JOUR
PY  - 2021//
TI  - Associations between mobility patterns and COVID-19 deaths during the pandemic: a network structure and rank propagation modelling approach
JO  - Array (New York, N.Y.)
A1  - Irini, Furxhi
A1  - Kia, Arash Negahdari
A1  - Shannon, Darren
A1  - Jannusch, Tim
A1  - Murphy, Finbarr
A1  - Sheehan, Barry
SP  - e100075
EP  - e100075
VL  - 11
IS  - 
N2  - 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. <br><br>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. <br><br>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.<p />  <p>Language: en</p>
LA  - en
SN  - 2590-0056
UR  - http://dx.doi.org/10.1016/j.array.2021.100075
ID  - ref1
ER  -