|ARTIGO_PrecisionMappingCOVID-19.pdf||4,02 MB||Adobe PDF||View/Open|
|Title:||Precision mapping of COVID-19 vulnerable locales by epidemiological and socioeconomic risk factors, developed using South Korean data|
Silva, Alan Ricardo da
Kouzoukas, Dimitrios E.
Correa, Paola A.
Carpenter, David O.
Coreia do Sul
|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.|
|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/).|
|Appears in Collections:||EST - Artigos publicados em periódicos|
UnB - Covid-19
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