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Population mobility trends, deprivation index and the spatio-temporal spread of coronavirus disease 2019 in Ireland

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Show simple item record Madden, Jamie M. More, Simon J. Teljeur, Conor Gleeson, Justin Walsh, Cathal Dominic McGrath, Guy 2021-06-29T08:21:20Z 2021-06-29T08:21:20Z 2021
dc.description peer-reviewed en_US
dc.description.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. en_US
dc.language.iso eng en_US
dc.publisher MDPI en_US
dc.relation.ispartofseries International Journal of Environmental Research and Public Health;18, 6285
dc.subject COVID-19 en_US
dc.subject spatio-temporal en_US
dc.subject spatial statistics en_US
dc.title Population mobility trends, deprivation index and the spatio-temporal spread of coronavirus disease 2019 in Ireland en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.3390/ijerph18126285
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

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