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dc.contributor.authorWeinstein, Bayarmagnai-
dc.contributor.authorSilva, Alan Ricardo da-
dc.contributor.authorKouzoukas, Dimitrios E.-
dc.contributor.authorBose, Tanima-
dc.contributor.authorKim, Gwang-Jin-
dc.contributor.authorCorrea, Paola A.-
dc.contributor.authorPondugula, Santhi-
dc.contributor.authorLee, YoonJung-
dc.contributor.authorKim, Jihoo-
dc.contributor.authorCarpenter, David O.-
dc.date.accessioned2021-01-14T14:01:21Z-
dc.date.available2021-01-14T14:01:21Z-
dc.date.issued2021-01-12-
dc.identifier.citationWEINSTEIN, Bayarmagnai et al. Precision mapping of COVID-19 vulnerable locales by epidemiological and socioeconomic risk factors, developed using South Korean data. International Journal of Environmental Research and Public Health, v. 18, n. 2, 604, 2021. DOI: https://doi.org/10.3390/ijerph18020604. Disponível em: https://www.mdpi.com/1660-4601/18/2/604. Acesso em: 14 jan. 2021.pt_BR
dc.identifier.urihttps://repositorio.unb.br/handle/10482/39908-
dc.language.isoInglêspt_BR
dc.publisherMDPIpt_BR
dc.rightsAcesso Abertopt_BR
dc.titlePrecision mapping of COVID-19 vulnerable locales by epidemiological and socioeconomic risk factors, developed using South Korean datapt_BR
dc.typeArtigopt_BR
dc.subject.keywordCovid-19pt_BR
dc.subject.keywordEpidemiaspt_BR
dc.subject.keywordFatores socioeconômicospt_BR
dc.subject.keywordEstatísticapt_BR
dc.subject.keywordCoreia do Sulpt_BR
dc.rights.licenseCopyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons. org/licenses/by/4.0/).pt_BR
dc.identifier.doihttps://doi.org/10.3390/ijerph18020604pt_BR
dc.description.abstract1COVID-19 has severely impacted socioeconomically disadvantaged populations. To support pandemic control strategies, geographically weighted negative binomial regression (GWNBR) mapped COVID-19 risk related to epidemiological and socioeconomic risk factors using South Korean incidence data (January 20, 2020 to July 1, 2020). We constructed COVID-19-specific socioeconomic and epidemiological themes using established social theoretical frameworks and created composite indexes through principal component analysis. The risk of COVID-19 increased with higher area morbidity, risky health behaviours, crowding, and population mobility, and with lower social distancing, healthcare access, and education. Falling COVID-19 risks and spatial shifts over three consecutive time periods reflected effective public health interventions. This study provides a globally replicable methodological framework and precision mapping for COVID-19 and future pandemics.pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-3035-649Xpt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-1922-670Xpt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-1151-1140pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0003-4841-394Xpt_BR
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