Spatial and temporal analysis of COVID-19 in the elderly living in residential care homes in Portugal

dc.contributor.authorde Mello-Sampayo, F.
dc.date.accessioned2022-06-27T15:15:26Z
dc.date.available2022-06-27T15:15:26Z
dc.date.issued2022
dc.date.updated2022-06-27T16:14:53Z
dc.description.abstractBackground: The goal of this study is to identify geographic areas for priority actions in order to control COVID-19 among the elderly living in Residential Care Homes (RCH). We also describe the evolution of COVID-19 in RHC throughout the 278 municipalities of continental Portugal between March and December 2020. Methods: A spatial population analysis of positive COVID-19 cases reported by the Portuguese National Health Service (NHS) among the elderly living in RCH. The data are for COVID-19 testing, symptomatic status, comorbidities, and income level by municipalities. COVID-19 measures at the municipality level are the proportion of positive cases of elderly living in RCH, positive cases per elderly living in RCH, symptomatic to asymptomatic ratio, and the share of comorbidities cases. Spatial analysis used the Kernel density estimation (KDE), space-time statistic Scan, and geographic weighted regression (GWR) to detect and analyze clusters of infected elderly. Results: Between 3 March and 31 December 2020, the high-risk primary cluster was located in the regions of Braganca, Guarda, Vila Real, and Viseu, in the Northwest of Portugal (relative risk = 3.67), between 30 September and 13 December 2020. The priority geographic areas for attention and intervention for elderly living in care homes are the regions in the Northeast of Portugal, and around the large cities, Lisbon and Porto, which had high risk clusters. The relative risk of infection was spatially not stationary and generally positively affected by both comorbidities and low-income. Conclusion: The regions with a population with high comorbidities and low income are a priority for action in order to control COVID-19 in the elderly living in RCH. The results suggest improving both income and health levels in the southwest of Portugal, in the environs of large cities, such as Lisbon and Porto, and in the northwest of Portugal to mitigate the spread of COVID-19.eng
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.3390/ijerph19105921
dc.identifier.issn1660-4601
dc.identifier.urihttp://hdl.handle.net/10071/25723
dc.journalInternational Journal of Environmental Research and Public Health
dc.language.isoeng
dc.number10
dc.peerreviewedyes
dc.publisherMDPI
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00315%2F2020/PT
dc.rightsopen access
dc.subjectCOVID-9eng
dc.subjectElderly in residential care homes (RCH)eng
dc.subjectSpatial-temporal analysiseng
dc.subjectGeographic weighted regression (GWR)eng
dc.subjectKernel density estimation (KDE)eng
dc.subject.fosDomínio/Área Científica::Ciências Sociais::Economia e Gestãopor
dc.titleSpatial and temporal analysis of COVID-19 in the elderly living in residential care homes in Portugaleng
dc.typearticle
dc.volume19
degois.publication.issue10
degois.publication.titleSpatial and temporal analysis of COVID-19 in the elderly living in residential care homes in Portugaleng
dspace.entity.typePublicationen
iscte.alternateIdentifiers.scopus2-s2.0-85129844859
iscte.alternateIdentifiers.wosWOS:000801723500001
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-89310
iscte.subject.odsSaúde de qualidadepor
iscte.subject.odsTrabalho digno e crescimento económicopor
iscte.subject.odsCidades e comunidades sustentáveispor

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