Air pollution and temperature are associated with increased COVID-19 incidence: A time series study
Objectives: Although COVID-19 is known to be caused by human-to-human transmission, it remains largely unclear whether ambient air pollutants and meteorological parameters could promote its transmission. Methods: A retrospective study was conducted to study whether air quality index (AQI), four ambient air pollutants (PM2.5, PM10, NO2 and CO) and five meteorological variables (daily temperature, highest temperature, lowest temperature, temperature difference and sunshine duration) could increase COVID-19 incidence in Wuhan and XiaoGan between Jan 26th to Feb 29th in 2020. Results: First, a significant correlation was found between COVID-19 incidence and AQI in both Wuhan (R2 = 0.13, p < 0.05) and XiaoGan (R2 = 0.223, p < 0.01). Specifically, among four pollutants, COVID-19 incidence was prominently correlated with PM2.5 and NO2 in both cities. In Wuhan, the tightest correlation was observed between NO2 and COVID-19 incidence (R2 = 0.329, p < 0.01). In XiaoGan, in addition to the PM2.5 (R2 = 0.117, p < 0.01) and NO2 (R2 = 0.015, p < 0.05), a notable correlation was also observed between the PM10 and COVID-19 incidence (R2 = 0.105, p < 0.05). Moreover, temperature is the only meteorological parameter that constantly correlated well with COVID-19 incidence in both Wuhan and XiaoGan, but in an inverse correlation (p < 0.05). Conclusions: AQI, PM2.5, NO2, and temperature are four variables that could promote the sustained transmission of COVID-19..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:97 |
|---|---|
| Enthalten in: |
International Journal of Infectious Diseases - 97(2020), Seite 278-282 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
He Li [VerfasserIn] |
|---|
| Links: |
doi.org [kostenfrei] |
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| Themen: |
AQI |
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| doi: |
10.1016/j.ijid.2020.05.076 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
DOAJ005915775 |
|---|
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| 245 | 1 | 0 | |a Air pollution and temperature are associated with increased COVID-19 incidence: A time series study |
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| 520 | |a Objectives: Although COVID-19 is known to be caused by human-to-human transmission, it remains largely unclear whether ambient air pollutants and meteorological parameters could promote its transmission. Methods: A retrospective study was conducted to study whether air quality index (AQI), four ambient air pollutants (PM2.5, PM10, NO2 and CO) and five meteorological variables (daily temperature, highest temperature, lowest temperature, temperature difference and sunshine duration) could increase COVID-19 incidence in Wuhan and XiaoGan between Jan 26th to Feb 29th in 2020. Results: First, a significant correlation was found between COVID-19 incidence and AQI in both Wuhan (R2 = 0.13, p < 0.05) and XiaoGan (R2 = 0.223, p < 0.01). Specifically, among four pollutants, COVID-19 incidence was prominently correlated with PM2.5 and NO2 in both cities. In Wuhan, the tightest correlation was observed between NO2 and COVID-19 incidence (R2 = 0.329, p < 0.01). In XiaoGan, in addition to the PM2.5 (R2 = 0.117, p < 0.01) and NO2 (R2 = 0.015, p < 0.05), a notable correlation was also observed between the PM10 and COVID-19 incidence (R2 = 0.105, p < 0.05). Moreover, temperature is the only meteorological parameter that constantly correlated well with COVID-19 incidence in both Wuhan and XiaoGan, but in an inverse correlation (p < 0.05). Conclusions: AQI, PM2.5, NO2, and temperature are four variables that could promote the sustained transmission of COVID-19. | ||
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a Ambient air pollutant | |
| 650 | 4 | |a Temperature | |
| 650 | 4 | |a AQI | |
| 653 | 0 | |a Infectious and parasitic diseases | |
| 700 | 0 | |a Xiao-Long Xu |e verfasserin |4 aut | |
| 700 | 0 | |a Da-Wei Dai |e verfasserin |4 aut | |
| 700 | 0 | |a Zhen-Yu Huang |e verfasserin |4 aut | |
| 700 | 0 | |a Zhuang Ma |e verfasserin |4 aut | |
| 700 | 0 | |a Yan-Jun Guan |e verfasserin |4 aut | |
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