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Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?
Kolluru, Soma Sekhara Rao; Nagendra, S M Shiva; Patra, Aditya Kumar; Gautam, Sneha; Alshetty, V Dheeraj; Kumar, Prashant.
  • Kolluru SSR; Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India.
  • Nagendra SMS; Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India.
  • Patra AK; Department of Mining Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India.
  • Gautam S; Department of Civil Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu India.
  • Alshetty VD; Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India.
  • Kumar P; Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, GU2 7XH Surrey UK.
Stoch Environ Res Risk Assess ; : 1-16, 2022 Sep 22.
Article in English | MEDLINE | ID: covidwho-2232015
ABSTRACT
The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM2.5 67 µg m-3 (lockdown) versus 81 µg m-3 (pre-lockdown); PM10 171 µg m-3 versus 235 µg m-3; CO 0.9 mg m-3 versus 1.1 mg m-3) except ozone which increased during the lockdown period (57 µg m-3 versus 39 µg m-3). The variation in pollutant concentrations revealed that PM2.5, PM10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: Stoch Environ Res Risk Assess Year: 2022 Document Type: Article Affiliation country: S00477-022-02308-w

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: Stoch Environ Res Risk Assess Year: 2022 Document Type: Article Affiliation country: S00477-022-02308-w