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How the global health security index and environment factor influence the spread of COVID-19: A country level analysis
The progress of viral diseases such as the new coronavirus (COVID-19) can be influenced not only by social isolation policies, but also by climatic factors. Understanding how these factors affect the progress of the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943391/ https://www.ncbi.nlm.nih.gov/pubmed/33723518 http://dx.doi.org/10.1016/j.onehlt.2021.100235 |
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author | Leichtweis, Bruno Grespan de Faria Silva, Letícia da Silva, Felipe Lopes Peternelli, Luiz Alexandre |
author_facet | Leichtweis, Bruno Grespan de Faria Silva, Letícia da Silva, Felipe Lopes Peternelli, Luiz Alexandre |
author_sort | Leichtweis, Bruno Grespan |
collection | PubMed |
description | The progress of viral diseases such as the new coronavirus (COVID-19) can be influenced not only by social isolation policies, but also by climatic factors. Understanding how these factors affect the progress of the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be essential to know the risks each country is facing because of the disease. In this study, we verified the existence of a relationship between the basic reproduction number (R0) of SARS-CoV-2 with different climate variables, while also considering the Global Health Security Index (GHS). We collected data from confirmed cases of COVID-19 along with their respective GHS notes and climate data, from December 31, 2019 to April 13, 2020, for 52 countries. The generalized additive model (GAM) was applied to explore the effect of temperature, relative humidity, solar radiation index, and GHS score on the spread rate of COVID-19. The countries that showed similarity to each other were grouped into clusters using the Kohonen self-organizing map methodology to investigate the importance of each variable in the dissemination of the disease. The temperature variable presented a linear relationship (p < 0.001) with the R0, with an explained variation of 36.2%, while the relative humidity variable did not present a significant relationship with the R0. The response curve of the solar radiation variable presented a significant nonlinear relationship (p < 0.001) with an explained variation of 32.3%. The GHS index variable, with a significant nonlinear relationship (p < 0.001), presented the largest explanatory response in the control of COVID-19, with an explained variation of 38.4%; further, it was observed that the countries with the largest GHS index scores were less influenced by climate variables. |
format | Online Article Text |
id | pubmed-7943391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-79433912021-03-11 How the global health security index and environment factor influence the spread of COVID-19: A country level analysis Leichtweis, Bruno Grespan de Faria Silva, Letícia da Silva, Felipe Lopes Peternelli, Luiz Alexandre One Health Research Paper The progress of viral diseases such as the new coronavirus (COVID-19) can be influenced not only by social isolation policies, but also by climatic factors. Understanding how these factors affect the progress of the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be essential to know the risks each country is facing because of the disease. In this study, we verified the existence of a relationship between the basic reproduction number (R0) of SARS-CoV-2 with different climate variables, while also considering the Global Health Security Index (GHS). We collected data from confirmed cases of COVID-19 along with their respective GHS notes and climate data, from December 31, 2019 to April 13, 2020, for 52 countries. The generalized additive model (GAM) was applied to explore the effect of temperature, relative humidity, solar radiation index, and GHS score on the spread rate of COVID-19. The countries that showed similarity to each other were grouped into clusters using the Kohonen self-organizing map methodology to investigate the importance of each variable in the dissemination of the disease. The temperature variable presented a linear relationship (p < 0.001) with the R0, with an explained variation of 36.2%, while the relative humidity variable did not present a significant relationship with the R0. The response curve of the solar radiation variable presented a significant nonlinear relationship (p < 0.001) with an explained variation of 32.3%. The GHS index variable, with a significant nonlinear relationship (p < 0.001), presented the largest explanatory response in the control of COVID-19, with an explained variation of 38.4%; further, it was observed that the countries with the largest GHS index scores were less influenced by climate variables. Elsevier 2021-03-10 /pmc/articles/PMC7943391/ /pubmed/33723518 http://dx.doi.org/10.1016/j.onehlt.2021.100235 Text en © 2021 Published by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Leichtweis, Bruno Grespan de Faria Silva, Letícia da Silva, Felipe Lopes Peternelli, Luiz Alexandre How the global health security index and environment factor influence the spread of COVID-19: A country level analysis |
title | How the global health security index and environment factor influence the spread of COVID-19: A country level analysis |
title_full | How the global health security index and environment factor influence the spread of COVID-19: A country level analysis |
title_fullStr | How the global health security index and environment factor influence the spread of COVID-19: A country level analysis |
title_full_unstemmed | How the global health security index and environment factor influence the spread of COVID-19: A country level analysis |
title_short | How the global health security index and environment factor influence the spread of COVID-19: A country level analysis |
title_sort | how the global health security index and environment factor influence the spread of covid-19: a country level analysis |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943391/ https://www.ncbi.nlm.nih.gov/pubmed/33723518 http://dx.doi.org/10.1016/j.onehlt.2021.100235 |
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