Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland

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Title: Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland
Authors: Madden, Jamie M.More, Simon JohnTeljeur, ConorGleeson, JustinWalsh, C. (Cathal)McGrath, Guy
Permanent link: http://hdl.handle.net/10197/12238
Date: 10-Jun-2021
Online since: 2021-06-17T11:50:37Z
Abstract: Like most countries worldwide, the coronavirus disease (COVID-19) has adversely affected Ireland. The aim of this study was to (i) investigate the spatio-temporal trend of COVID-19 incidence; (ii) describe mobility trends as measured by aggregated mobile phone records; and (iii) investigate the association between deprivation index, population density and COVID-19 cases while accounting for spatial and temporal correlation. Standardised incidence ratios of cases were calculated and mapped at a high spatial resolution (electoral division level) over time. Trends in the percentage change in mobility compared to a pre-COVID-19 period were plotted to investigate the impact of lockdown restrictions. We implemented a hierarchical Bayesian spatio-temporal model (Besag, York and Mollié (BYM)), commonly used for disease mapping, to investigate the association between covariates and the number of cases. There have been three distinct “waves” of COVID-19 cases in Ireland to date. Lockdown restrictions led to a substantial reduction in human movement, particularly during the 1st and 3rd wave. Despite adjustment for population density (incidence ratio (IR) = 1.985 (1.915–2.058)) and the average number of persons per room (IR = 10.411 (5.264–22.533)), we found an association between deprivation index and COVID-19 incidence (IR = 1.210 (CI: 1.077–1.357) for the most deprived quintile compared to the least deprived). There is a large range of spatial heterogeneity in COVID-19 cases in Ireland. The methods presented can be used to explore locally intensive surveillance with the possibility of localised lockdown measures to curb the transmission of infection, while keeping other, low-incidence areas open. Our results suggest that prioritising densely populated deprived areas (that are at increased risk of comorbidities) during vaccination rollout may capture people that are at risk of infection and, potentially, also those at increased risk of hospitalisation.
Type of material: Journal Article
Publisher: MDPI
Journal: International Journal of Environmental Research and Public Health
Volume: 18
Issue: 12
Copyright (published version): 2021 the Authors
Keywords: COVID-19Spatio-temporalSpatial statisticsStandardised incidence ratioDisease mappingCoronavirus
DOI: 10.3390/ijerph18126285
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by/3.0/ie/
Appears in Collections:Veterinary Medicine Research Collection
CVERA Research Collection

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