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Título : Precision mapping of COVID-19 vulnerable locales by epidemiological and socioeconomic risk factors, developed using South Korean data
Autor : Weinstein, Bayarmagnai
Silva, Alan Ricardo da
Kouzoukas, Dimitrios E.
Bose, Tanima
Kim, Gwang-Jin
Correa, Paola A.
Pondugula, Santhi
Lee, YoonJung
Kim, Jihoo
Carpenter, David O.
metadata.dc.identifier.orcid: https://orcid.org/0000-0003-3035-649X
https://orcid.org/0000-0002-1922-670X
https://orcid.org/0000-0003-1151-1140
https://orcid.org/0000-0003-4841-394X
Assunto:: Covid-19
Epidemias
Fatores socioeconômicos
Estatística
Coreia do Sul
Fecha de publicación : 12-ene-2021
Editorial : MDPI
Citación : 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.
Abstract: 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.
Licença:: 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/).
DOI: https://doi.org/10.3390/ijerph18020604
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UnB - Covid-19

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