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Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain
Background: As of 7 January 2022, it is estimated that 5.5 million people worldwide have died from COVID-19. Although the full impact of SARS-CoV-2 (COVID-19) on healthcare systems worldwide is still unknown, we must consider the socio-economic impact. For instance, it has resulted in an 11% decreas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9655530/ https://www.ncbi.nlm.nih.gov/pubmed/36360863 http://dx.doi.org/10.3390/ijerph192113981 |
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author | Martin-Delgado, Jimmy Mula, Aurora Manzanera, Rafael Mira, Jose Joaquin |
author_facet | Martin-Delgado, Jimmy Mula, Aurora Manzanera, Rafael Mira, Jose Joaquin |
author_sort | Martin-Delgado, Jimmy |
collection | PubMed |
description | Background: As of 7 January 2022, it is estimated that 5.5 million people worldwide have died from COVID-19. Although the full impact of SARS-CoV-2 (COVID-19) on healthcare systems worldwide is still unknown, we must consider the socio-economic impact. For instance, it has resulted in an 11% decrease in the GDP (Gross Domestic Product) in the European Union. We aim to provide valuable information for policymakers by analysing widely available epidemiological and socioeconomic indicators using Spanish data. Methods: Secondary analysis of routinely available data from various official data sources covering the period from 1 March 2020 to 31 March 2021. To measure the impact of COVID-19 in the population, a set of epidemiological and socioeconomic indicators were used. The interrelationships between these socioeconomic and epidemiological indicators were analysed using Pearson’s correlation. Their behaviour was grouped according to their greater capacity to measure the impact of the pandemic and was compared to identify those that are more appropriate to monitor future health crises (primary outcome) using multivariate analysis of canonical correlation for estimating the correlation between indicators using different units of analysis. Results: Data from different time points were analysed. The excess of mortality was negatively correlated with the number of new companies created during the pandemic. The increase in COVID-19 cases was associated with the rise of unemployed workers. Neither GDP nor per capita debt was related to any epidemiological indicators considered in the annual analysis. The canonical models of socioeconomic and epidemiological indicators of each of the time periods analysed were statistically significant (0.80–0.91 p < 0.05). Conclusions: In conclusion, during the COVID-19 pandemic in Spain, excess mortality, incidence, lethality, and unemployment constituted the best group of indicators to measure the impact of the pandemic. These indicators, widely available, could provide valuable information to policymakers and higher management in future outbreaks. |
format | Online Article Text |
id | pubmed-9655530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96555302022-11-15 Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain Martin-Delgado, Jimmy Mula, Aurora Manzanera, Rafael Mira, Jose Joaquin Int J Environ Res Public Health Article Background: As of 7 January 2022, it is estimated that 5.5 million people worldwide have died from COVID-19. Although the full impact of SARS-CoV-2 (COVID-19) on healthcare systems worldwide is still unknown, we must consider the socio-economic impact. For instance, it has resulted in an 11% decrease in the GDP (Gross Domestic Product) in the European Union. We aim to provide valuable information for policymakers by analysing widely available epidemiological and socioeconomic indicators using Spanish data. Methods: Secondary analysis of routinely available data from various official data sources covering the period from 1 March 2020 to 31 March 2021. To measure the impact of COVID-19 in the population, a set of epidemiological and socioeconomic indicators were used. The interrelationships between these socioeconomic and epidemiological indicators were analysed using Pearson’s correlation. Their behaviour was grouped according to their greater capacity to measure the impact of the pandemic and was compared to identify those that are more appropriate to monitor future health crises (primary outcome) using multivariate analysis of canonical correlation for estimating the correlation between indicators using different units of analysis. Results: Data from different time points were analysed. The excess of mortality was negatively correlated with the number of new companies created during the pandemic. The increase in COVID-19 cases was associated with the rise of unemployed workers. Neither GDP nor per capita debt was related to any epidemiological indicators considered in the annual analysis. The canonical models of socioeconomic and epidemiological indicators of each of the time periods analysed were statistically significant (0.80–0.91 p < 0.05). Conclusions: In conclusion, during the COVID-19 pandemic in Spain, excess mortality, incidence, lethality, and unemployment constituted the best group of indicators to measure the impact of the pandemic. These indicators, widely available, could provide valuable information to policymakers and higher management in future outbreaks. MDPI 2022-10-27 /pmc/articles/PMC9655530/ /pubmed/36360863 http://dx.doi.org/10.3390/ijerph192113981 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Martin-Delgado, Jimmy Mula, Aurora Manzanera, Rafael Mira, Jose Joaquin Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain |
title | Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain |
title_full | Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain |
title_fullStr | Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain |
title_full_unstemmed | Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain |
title_short | Measuring the Impact of Future Outbreaks? A Secondary Analysis of Routinely Available Data in Spain |
title_sort | measuring the impact of future outbreaks? a secondary analysis of routinely available data in spain |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9655530/ https://www.ncbi.nlm.nih.gov/pubmed/36360863 http://dx.doi.org/10.3390/ijerph192113981 |
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