University School of Management Studies, Guru Gobind Singh Indraprastha University, New Delhi, 110078, India.
Environ Sci Pollut Res Int. 2021 Jun;28(22):28624-28639. doi: 10.1007/s11356-021-12668-5. Epub 2021 Feb 5.
This paper examines the nexus between the Covid-19 confirmed cases, deaths, meteorological factors, including an air pollutant among the world's top 10 infected countries, from 1 February 2020 through 30 June 2020, using advanced econometric techniques to address heterogeneity across the nations. The findings of the study suggest that there exists a strong cross-sectional dependence between Covid-19 cases, deaths, and all the meteorological factors for the countries under study. The findings also reveal that a long-term relationship exists between all the meteorological factors. There exists a bi-directional causality running between the Covid-19 cases and all the meteorological factors. With Covid-19 death cases as the dependent variable, there exists bi-directional causality running between the Covid-19 death cases and Covid-19 confirmed cases, air pressure, humidity, and temperature. Temperature and air pressure exhibit a statistically significant and negative impact on the Covid-19 confirmed cases. Air pollutant PM2.5 also exhibits a significant but positive impact on the Covid-19 confirmed cases. Temperature indicates a statistically significant and negative impact on the Covid-19 death cases. At the same time, Covid-19 confirmed cases and air pollutant PM2.5 exhibit a statistically significant and positive impact on the Covid-19 death cases across the ten countries under study. Hence, it is possible to postulate that cool and dry weather conditions with lower temperatures may promote indoor activities and human gatherings (assembling), leading to virus transmission. This study contributes both practically and theoretically to the concerned field of pandemic management. Our results assist in taking appropriate measures in implementing intersectoral policies and actions as necessary in a timely and efficient manner. Causal relations of Meteorological factors and Covid-19 (2 models used in the study).
本文考察了 2020 年 2 月 1 日至 6 月 30 日期间，全球十大感染国家的确诊病例、死亡人数、气象因素（包括一种空气污染物）之间的关系，使用先进的计量经济学技术来解决各国之间的异质性问题。研究结果表明，在所研究的国家中，新冠病毒确诊病例、死亡人数与所有气象因素之间存在很强的横截面依赖性。研究结果还表明，所有气象因素之间存在长期关系。新冠病毒确诊病例与所有气象因素之间存在双向因果关系。以新冠病毒死亡病例为因变量，新冠病毒死亡病例与新冠病毒确诊病例、气压、湿度和温度之间存在双向因果关系。温度和气压对新冠病毒确诊病例有显著的负向影响。空气污染物 PM2.5 对新冠病毒确诊病例也有显著的正向影响。温度对新冠病毒死亡病例有显著的负向影响。同时，新冠病毒确诊病例和空气污染物 PM2.5 对十大研究国家的新冠病毒死亡病例有显著的正向影响。因此，可以推测，凉爽干燥的天气条件和较低的温度可能会促进室内活动和人群聚集（聚集），从而导致病毒传播。本研究在实践和理论上都为大流行管理这一相关领域做出了贡献。我们的研究结果有助于及时、有效地采取适当措施，实施跨部门政策和行动。气象因素与新冠病毒的因果关系（本研究中使用的 2 个模型）。
