A Study on the Association Between Air Pollutants and COVID-19 Across Different Provinces in Iran

Abstract

Background: Examining the potential association between the quantity and quality of air pollutants and COVID-19 prevalence may help inform prevention and monitoring strategies. Objectives: This study aimed to investigate the ecological association between air pollution levels and COVID-19 cases across the provinces of Iran. Methods: This ecological study used data collected from February 20 to April 20, 2020, in 31 provinces in Iran. Meteorological data, including average concentrations of carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM10 and PM2.5), were obtained from Iran’s meteorological system. The number of confirmed COVID-19 cases in each province was compared with air pollution parameters using Pearson correlation coefficients and multivariate linear regression adjusted for population density. Results: Most provinces reported high CO concentrations (16.68 - 28.78 mg/m3). High PM10 levels were observed in southeastern Iran, high SO2 levels in the southeast and northwest, and high PM2.5 levels in the southwest, central, and northeast regions. Significant ecological correlations were observed between several air pollutants, particularly PM2.5 and PM10, and provincial COVID-19 case counts. Conclusions: Significant ecological correlations were observed between several air pollutants, particularly PM2.5 and PM10, and provincial COVID-19 case counts. These findings suggest that air pollution modeling may help identify high-risk regions, although causation cannot be inferred at the individual level. Temporary reductions in traffic and industrial activities during the pandemic peak were associated with decreased levels of several air pollutants, indicating interactions among human activity, air quality, and infectious disease dynamics.