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Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is a worldwide epidemiological emergency, and the risk factors for the multiple waves with new COVID-19 strains are concerning. This study aims to identify the most significant risk factors for spreading COVID-19 to help policymakers take...

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Autores principales: Mashrur, Fazla Rabbi, Roy, Amit Dutta, Chhoan, Anisha Parsub, Sarker, Sumit, Saha, Anamika, Hasan, S.M. Naimul, Saha, Shumit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. on behalf of INDIACLEN. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236127/
https://www.ncbi.nlm.nih.gov/pubmed/34222717
http://dx.doi.org/10.1016/j.cegh.2021.100811
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author Mashrur, Fazla Rabbi
Roy, Amit Dutta
Chhoan, Anisha Parsub
Sarker, Sumit
Saha, Anamika
Hasan, S.M. Naimul
Saha, Shumit
author_facet Mashrur, Fazla Rabbi
Roy, Amit Dutta
Chhoan, Anisha Parsub
Sarker, Sumit
Saha, Anamika
Hasan, S.M. Naimul
Saha, Shumit
author_sort Mashrur, Fazla Rabbi
collection PubMed
description BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is a worldwide epidemiological emergency, and the risk factors for the multiple waves with new COVID-19 strains are concerning. This study aims to identify the most significant risk factors for spreading COVID-19 to help policymakers take early measures for the next waves. METHODS: We conducted the study on randomly selected 29 countries where the pandemic had a downward trend in the daily active cases curve as of June 10, 2020. We investigated the association with the standardized spreading index and demographical, environmental, socioeconomic, and government intervention. To standardize the spreading index, we accounted for the number of tests and the timeline bias. Furthermore, we performed multiple linear regression to identify the relative importance of the variables. RESULTS: In the correlation analysis, air pollution, PM(2.5) (r = 0.37, p = 0.0466), number of days to impose lockdown from first case (r = 0.38, p = 0.0424) and total confirmed cases on the first lockdown (r = 0.61, p = 0.0004) were associated with outcome measures. In the adjusted model, air pollution ([Formula: see text]  = 4.5, p = 0.0127, |t| = 3.1) and overweight prevalence ([Formula: see text]  = 4.7, p = 0.0187, |t| = 2.9) were the most significant exposure variable for spreading of COVID-19. CONCLUSION: Our findings showed that countries with larger PM(2.5) values and comparatively more overweight populations are at higher risk of spreading COVID-19. Proper preventive measures may reduce the spreading.
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spelling pubmed-82361272021-06-28 Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19 Mashrur, Fazla Rabbi Roy, Amit Dutta Chhoan, Anisha Parsub Sarker, Sumit Saha, Anamika Hasan, S.M. Naimul Saha, Shumit Clin Epidemiol Glob Health Article BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is a worldwide epidemiological emergency, and the risk factors for the multiple waves with new COVID-19 strains are concerning. This study aims to identify the most significant risk factors for spreading COVID-19 to help policymakers take early measures for the next waves. METHODS: We conducted the study on randomly selected 29 countries where the pandemic had a downward trend in the daily active cases curve as of June 10, 2020. We investigated the association with the standardized spreading index and demographical, environmental, socioeconomic, and government intervention. To standardize the spreading index, we accounted for the number of tests and the timeline bias. Furthermore, we performed multiple linear regression to identify the relative importance of the variables. RESULTS: In the correlation analysis, air pollution, PM(2.5) (r = 0.37, p = 0.0466), number of days to impose lockdown from first case (r = 0.38, p = 0.0424) and total confirmed cases on the first lockdown (r = 0.61, p = 0.0004) were associated with outcome measures. In the adjusted model, air pollution ([Formula: see text]  = 4.5, p = 0.0127, |t| = 3.1) and overweight prevalence ([Formula: see text]  = 4.7, p = 0.0187, |t| = 2.9) were the most significant exposure variable for spreading of COVID-19. CONCLUSION: Our findings showed that countries with larger PM(2.5) values and comparatively more overweight populations are at higher risk of spreading COVID-19. Proper preventive measures may reduce the spreading. The Author(s). Published by Elsevier B.V. on behalf of INDIACLEN. 2021 2021-06-27 /pmc/articles/PMC8236127/ /pubmed/34222717 http://dx.doi.org/10.1016/j.cegh.2021.100811 Text en © 2021 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Mashrur, Fazla Rabbi
Roy, Amit Dutta
Chhoan, Anisha Parsub
Sarker, Sumit
Saha, Anamika
Hasan, S.M. Naimul
Saha, Shumit
Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19
title Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19
title_full Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19
title_fullStr Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19
title_full_unstemmed Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19
title_short Impact of demographic, environmental, socioeconomic, and government intervention on the spreading of COVID-19
title_sort impact of demographic, environmental, socioeconomic, and government intervention on the spreading of covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236127/
https://www.ncbi.nlm.nih.gov/pubmed/34222717
http://dx.doi.org/10.1016/j.cegh.2021.100811
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