COVID-19 mortality and exposure to airborne PM2.5 : A lag time correlation
Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved..
COVID-19 has escalated into one of the most serious crises in the 21st Century. Given the rapid spread of SARS-CoV-2 and its high mortality rate, here we investigate the impact and relationship of airborne PM2.5 to COVID-19 mortality. Previous studies have indicated that PM2.5 has a positive relationship with the spread of COVID-19. To gain insights into the delayed effect of PM2.5 concentration (μgm-3) on mortality, we focused on the role of PM2.5 in Wuhan City in China and COVID-19 during the period December 27, 2019 to April 7, 2020. We also considered the possible impact of various meteorological factors such as temperature, precipitation, wind speed, atmospheric pressure and precipitation on pollutant levels. The results from the Pearson's correlation coefficient analyses reveal that the population exposed to higher levels of PM2.5 pollution are susceptible to COVID-19 mortality with a lag time of >18 days. By establishing a generalized additive model, the delayed effect of PM2.5 on the death toll of COVID-19 was verified. A negative correction was identified between temperature and number of COVID-19 deaths, whereas atmospheric pressure exhibits a positive correlation with deaths, both with a significant lag effect. The results from our study suggest that these epidemiological relationships may contribute to the understanding of the COVID-19 pandemic and provide insights for public health strategies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:806 |
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| Enthalten in: |
The Science of the total environment - 806(2022), Pt 3 vom: 01. Feb., Seite 151286 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Shao, Longyi [VerfasserIn] |
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| Links: |
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| Themen: |
Air Pollutants |
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| Anmerkungen: |
Date Completed 03.12.2021 Date Revised 17.12.2022 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.scitotenv.2021.151286 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved. | ||
| 520 | |a COVID-19 has escalated into one of the most serious crises in the 21st Century. Given the rapid spread of SARS-CoV-2 and its high mortality rate, here we investigate the impact and relationship of airborne PM2.5 to COVID-19 mortality. Previous studies have indicated that PM2.5 has a positive relationship with the spread of COVID-19. To gain insights into the delayed effect of PM2.5 concentration (μgm-3) on mortality, we focused on the role of PM2.5 in Wuhan City in China and COVID-19 during the period December 27, 2019 to April 7, 2020. We also considered the possible impact of various meteorological factors such as temperature, precipitation, wind speed, atmospheric pressure and precipitation on pollutant levels. The results from the Pearson's correlation coefficient analyses reveal that the population exposed to higher levels of PM2.5 pollution are susceptible to COVID-19 mortality with a lag time of >18 days. By establishing a generalized additive model, the delayed effect of PM2.5 on the death toll of COVID-19 was verified. A negative correction was identified between temperature and number of COVID-19 deaths, whereas atmospheric pressure exhibits a positive correlation with deaths, both with a significant lag effect. The results from our study suggest that these epidemiological relationships may contribute to the understanding of the COVID-19 pandemic and provide insights for public health strategies | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a Correlation analysis | |
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| 700 | 1 | |a Silva, Luis F O |e verfasserin |4 aut | |
| 700 | 1 | |a Ge, Shuoyi |e verfasserin |4 aut | |
| 700 | 1 | |a da Boit, Kátia |e verfasserin |4 aut | |
| 700 | 1 | |a Feng, Xiaolei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Mengyuan |e verfasserin |4 aut | |
| 700 | 1 | |a BéruBé, Kelly |e verfasserin |4 aut | |
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