Abstract

Background: The association of air pollution with the COVID-19 pandemic majorly caused respiratory diseases among the major outcomes of COVID-19 infection. In addition, meteorological factors play an important role in spreading COVID-19 infection in humans who have been exposed to air pollutants. Objectives: This study aims to estimate and comprehend the linkages between the contribution of PM 2.5 concentrations and meteorological parameters to the spreading coronavirus infection in Gurugram, a badly affected city in India due to the COVID-19 pandemic. Materials and methods: We employed some statistical analysis on daily average data of PM 2.5 concentrations and meteorological conditions with daily COVID-19 cases from March 2020 to February 2022. To optimize PM2.5 concentrations linked with COVID-19 instances, a time series analysis was performed. The Pearson correlation test investigated the relationships between PM2.5levels, meteorological data, and COVID-19 instances. The PCA was applied to reveal the most significant factor attributable to affecting the rate of COVID-19 transmission in Gurugram. Results: The highest cases of COVID-19 (250,000) were observed in February 2022 when PM 2.5 concentration was 286.6µg/m3, 12.64 oC temperature, 73.81% RH, and 68.265 km/h wind speed while minimum cases (3125) were found in March 2020 with the 18.18µg/m3 PM2.5 concentration, 10.62.oC temperature, 50.05% RH, and 83.295km/h wind speed. Conclusion: The principal component analysis helped conclude the results, which revealed that the daily COVID-19 cases were significantly positively correlated with PM 2.5 concentrations, RH, and temperature. However, daily COVID-19 cases were negatively or poorly correlated with wind speed. COVID-19 pandemic is prominently affected by PM 2.5, while RH and temperature were found to be important meteorological factors significantly affecting its human-to-human transmission. This study may provide useful indications to regulatory bodies to modify environmental health policies.

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