Associations between mobility patterns and COVID-19 deaths during the pandemic: A network structure and rank propagation modelling approach.

Furxhi Irini,Arash Negahdari Kia,Darren Shannon,Finbarr Murphy,Barry Sheehan,Tim Jannusch

doi:10.1016/j.array.2021.100075

Furxhi Irini, Arash Negahdari Kia + Show 4 more

Open Access

https://doi.org/10.1016/j.array.2021.100075

Copy DOI

Abstract

BackgroundFrom 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.MethodsIn 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.FindingsOur 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.

Highlights

As of January 16, 2021, more than two million people have died from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), widely known as COVID-19 [1]
Human mobility is among the key drivers fostering the rapid spread of disease. This is the first time that rank propagation modelling has been coupled with a clustering approach and used to analyse the transmission patterns of COVID-19
The graphical analyses demonstrate that mobility channels with looser restrictions had a causal impact on COVID-19 related deaths

Summary

Introduction

As of January 16, 2021, more than two million people have died from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), widely known as COVID-19 [1]. 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. Findings: Our analysis reveals that the most important mobility trend categories that exhibit the strongest as sociation 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. Each county has a different impact on the national total

Methods

Results

Discussion

Conclusion