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Climate indicators and COVID-19 recovery: A case of Wuhan during the lockdown

Author

Listed:
  • Zhai Shuai

    (Huzhou University)

  • Najaf Iqbal

    (Anhui University of Finance and Economics
    University of Aberdeen)

  • Rai Imtiaz Hussain

    (University of Okara)

  • Farrukh Shahzad

    (Guangdong University of Petrochemical Technology)

  • Yong Yan

    (Huzhou University)

  • Zeeshan Fareed

    (Huzhou University
    University of Aberdeen)

  • Bilal

    (Hubei University of Economics)

Abstract

The world needs to get out of the COVID-19 pandemic smoothly through a thorough socio-economic recovery. The first and the foremost step forward in this direction is the health recovery of the people infected. Our empirical study addresses this neglected point in the recent research on COVID-19 and specifically aims at exploring the impact of the environment on health recovery from COVID-19. The sample data are taken during the lockdown period in Wuhan, i.e., from 23rd January 2020 to 8th April 2020. The recently developed econometric technique of Quantile-on-Quantile regression, proposed by Shin and Zhu (2016) is employed to capture the asymmetric association between environmental factors (TEMP, HUM, PM2.5, PM10, CO, SO2, NO2, and O3) and the number of recovered patients from COVID-19. We observe significant heterogeneity in the association among variables across various quantiles. The findings suggest that TEMP, PM2.5, PM10, CO, NO2, and O3 are negatively related to the COVID-19 recovery, while HUM and SO2 show a positive association at most quantiles. The study recommends that maintaining a safe and comfortable environment for the patients may increase the chances of recovery from COVID-19. The success story of Wuhan, the initial epicenter of the novel coronavirus in China, can serve as an important case study for other countries to bring the outbreak under control. The current study could be conducive for the policymakers of those countries where the COVID-19 pandemic is still unrestrained.

Suggested Citation

  • Zhai Shuai & Najaf Iqbal & Rai Imtiaz Hussain & Farrukh Shahzad & Yong Yan & Zeeshan Fareed & Bilal, 2022. "Climate indicators and COVID-19 recovery: A case of Wuhan during the lockdown," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8464-8484, June.
  • Handle: RePEc:spr:endesu:v:24:y:2022:i:6:d:10.1007_s10668-021-01794-2
    DOI: 10.1007/s10668-021-01794-2
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    References listed on IDEAS

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    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    2. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    3. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
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    Cited by:

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