COVID-19 transmission due to interplay between PM2.5 and weather conditions

Gulshan Sharma, Era Upadhyay, Akshay Kulkarni, Archna Sagalgile
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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.
PM2.5和天气条件相互作用导致的COVID-19传播
背景:空气污染与 COVID-19 大流行的关联主要导致呼吸系统疾病,这也是 COVID-19 感染的主要后果之一。此外,气象因素在暴露于空气污染物的人群中传播 COVID-19 感染中也发挥了重要作用。研究目的:本研究旨在估计和理解 PM 2.5 浓度和气象参数对印度受 COVID-19 大流行严重影响的城市古鲁格拉姆冠状病毒感染传播的影响之间的联系。材料和方法:我们对 2020 年 3 月至 2022 年 2 月期间 PM2.5 浓度和气象条件的日均数据与 COVID-19 病例的日均数据进行了统计分析。为了优化与 COVID-19 病例相关的 PM2.5 浓度,我们进行了时间序列分析。Pearson相关性检验调查了PM2.5水平、气象数据和COVID-19实例之间的关系。应用 PCA 方法揭示了影响 COVID-19 在古鲁格拉姆传播速度的最重要因素。结果:2022 年 2 月,PM2.5 浓度为 286.6µg/m3 ,气温为 12.64 摄氏度,相对湿度为 73.81%,风速为 68.265 公里/小时,COVID-19 案例数最多(250,000 例);2020 年 3 月,PM2.5 浓度为 18.18µg/m3 ,气温为 10.62 摄氏度,相对湿度为 50.05%,风速为 83.295 公里/小时,COVID-19 案例数最少(3125 例)。结论主成分分析有助于得出结论,结果显示每日 COVID-19 案例与 PM2.5 浓度、相对湿度和温度呈显著正相关。然而,COVID-19 的每日病例与风速呈负相关或低相关。COVID-19 大流行主要受 PM 2.5 影响,而相对湿度和温度则是显著影响其人际传播的重要气象因素。这项研究可为监管机构修改环境卫生政策提供有用的指示。
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