COVID-19 infection affects respiratory system; thus, air pollution and meteorological factors also contribute majorly to its transmission. This study is aiming to estimate and comprehend the linkages between contribution of PM 2.5 concentrations and meteorological parameters to spreading coronavirus infection in Gurugram, a badly affected city of India due to COVID-19 pandemic. We employed some statistical analysis on daily average data of PM 2.5 concentrations and meteorological constraints with daily COVID-19 cases during March 2020-February 2022. Time series analysis was conducted to optimize PM 2.5 concentrations associated with COVID-19 cases. The Pearson correlation test was applied to investigate the correlations between PM 2.5 concentrations, meteorological parameters, and COVID-19 cases. The PCA was applied to reveal the most significant factor attributable to affect the rate of COVID-19 transmission in Gurugram. The highest cases of COVID-19 (25,7375) were observed in the month of February when PM 2.5 concentration was 286.6µg/m 3, 12.64˚C temperature, 73.81% RH and 68.265 km/h wind speed; while minimum cases (3125) were found in the month of March with the 18.18µg/m3 PM 2.5 concentration, 10.62˚C temperature, 50.05% RH, and 83.295km/h wind speed. The principal component analysis 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 as important meteorological factors significantly affect its human-to-human transmission. This study may provide the useful indications to regulatory bodies to modify the environmental health policies.