http://repositorio.unb.br/handle/10482/39908
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dc.contributor.author | Weinstein, Bayarmagnai | - |
dc.contributor.author | Silva, Alan Ricardo da | - |
dc.contributor.author | Kouzoukas, Dimitrios E. | - |
dc.contributor.author | Bose, Tanima | - |
dc.contributor.author | Kim, Gwang-Jin | - |
dc.contributor.author | Correa, Paola A. | - |
dc.contributor.author | Pondugula, Santhi | - |
dc.contributor.author | Lee, YoonJung | - |
dc.contributor.author | Kim, Jihoo | - |
dc.contributor.author | Carpenter, David O. | - |
dc.date.accessioned | 2021-01-14T14:01:21Z | - |
dc.date.available | 2021-01-14T14:01:21Z | - |
dc.date.issued | 2021-01-12 | - |
dc.identifier.citation | WEINSTEIN, 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.uri | https://repositorio.unb.br/handle/10482/39908 | - |
dc.language.iso | Inglês | pt_BR |
dc.publisher | MDPI | pt_BR |
dc.rights | Acesso Aberto | pt_BR |
dc.title | Precision mapping of COVID-19 vulnerable locales by epidemiological and socioeconomic risk factors, developed using South Korean data | pt_BR |
dc.type | Artigo | pt_BR |
dc.subject.keyword | Covid-19 | pt_BR |
dc.subject.keyword | Epidemias | pt_BR |
dc.subject.keyword | Fatores socioeconômicos | pt_BR |
dc.subject.keyword | Estatística | pt_BR |
dc.subject.keyword | Coreia do Sul | pt_BR |
dc.rights.license | Copyright: © 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.doi | https://doi.org/10.3390/ijerph18020604 | pt_BR |
dc.description.abstract1 | COVID-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.orcid | https://orcid.org/0000-0003-3035-649X | pt_BR |
dc.identifier.orcid | https://orcid.org/0000-0002-1922-670X | pt_BR |
dc.identifier.orcid | https://orcid.org/0000-0003-1151-1140 | pt_BR |
dc.identifier.orcid | https://orcid.org/0000-0003-4841-394X | pt_BR |
Collection(s) : | Artigos publicados em periódicos e afins UnB - Covid-19 |
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