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Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic
BACKGROUND: The spread of COVID-19 has been characterized by unprecedented global lock-downs. Although, the extent of containment policies cannot be explained only through epidemic data. Previous studies already focused on the relationship between the economy and healthcare, focusing on the impact o...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9174749/ https://www.ncbi.nlm.nih.gov/pubmed/35692347 http://dx.doi.org/10.3389/fpubh.2022.872704 |
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author | Santini, Giunio Fordellone, Mario Boffo, Silvia Signoriello, Simona De Vito, Danila Chiodini, Paolo |
author_facet | Santini, Giunio Fordellone, Mario Boffo, Silvia Signoriello, Simona De Vito, Danila Chiodini, Paolo |
author_sort | Santini, Giunio |
collection | PubMed |
description | BACKGROUND: The spread of COVID-19 has been characterized by unprecedented global lock-downs. Although, the extent of containment policies cannot be explained only through epidemic data. Previous studies already focused on the relationship between the economy and healthcare, focusing on the impact of diseases in countries with a precarious economic situation. However, the pandemic caused by SARS-CoV-2 drew most countries of the world into a precarious economic situation mostly caused by the global and local lock-downs policies. METHODS: A discriminant analysis performed via partial least squares procedure was applied to evaluate the impact of economic and healthcare variables on the containment measures adopted by 39 countries. To collect the input variables (macroeconomic, healthcare, and medical services), we relied on official databases of international organizations, such as The World Bank and WHO. RESULTS: The stringency lock-down policies could not only be influenced by the epidemical data, but also by previous features of the selected countries, such as economic and healthcare conditions. CONCLUSIONS: Indeed, economic and healthcare variables also contributed to shaping the implemented lock-down policies. |
format | Online Article Text |
id | pubmed-9174749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91747492022-06-09 Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic Santini, Giunio Fordellone, Mario Boffo, Silvia Signoriello, Simona De Vito, Danila Chiodini, Paolo Front Public Health Public Health BACKGROUND: The spread of COVID-19 has been characterized by unprecedented global lock-downs. Although, the extent of containment policies cannot be explained only through epidemic data. Previous studies already focused on the relationship between the economy and healthcare, focusing on the impact of diseases in countries with a precarious economic situation. However, the pandemic caused by SARS-CoV-2 drew most countries of the world into a precarious economic situation mostly caused by the global and local lock-downs policies. METHODS: A discriminant analysis performed via partial least squares procedure was applied to evaluate the impact of economic and healthcare variables on the containment measures adopted by 39 countries. To collect the input variables (macroeconomic, healthcare, and medical services), we relied on official databases of international organizations, such as The World Bank and WHO. RESULTS: The stringency lock-down policies could not only be influenced by the epidemical data, but also by previous features of the selected countries, such as economic and healthcare conditions. CONCLUSIONS: Indeed, economic and healthcare variables also contributed to shaping the implemented lock-down policies. Frontiers Media S.A. 2022-05-25 /pmc/articles/PMC9174749/ /pubmed/35692347 http://dx.doi.org/10.3389/fpubh.2022.872704 Text en Copyright © 2022 Santini, Fordellone, Boffo, Signoriello, De Vito and Chiodini. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Santini, Giunio Fordellone, Mario Boffo, Silvia Signoriello, Simona De Vito, Danila Chiodini, Paolo Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic |
title | Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic |
title_full | Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic |
title_fullStr | Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic |
title_full_unstemmed | Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic |
title_short | Modeling for the Stringency of Lock-Down Policies: Effects of Macroeconomic and Healthcare Variables in Response to the COVID-19 Pandemic |
title_sort | modeling for the stringency of lock-down policies: effects of macroeconomic and healthcare variables in response to the covid-19 pandemic |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9174749/ https://www.ncbi.nlm.nih.gov/pubmed/35692347 http://dx.doi.org/10.3389/fpubh.2022.872704 |
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