Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis

How does the COVID-19-related restriction affect the spatiotemporal variability of ambient air quality in a tropical city?

The ambient air, a significant hazard to human health in most Indian cities, including Rourkela, is something we are strangely neglecting in the age of industrialization and urbanization. High levels of particulate matter released from various anthropogenic sources over the past decade have had a significant negative impact on the city. The COVID-19 lockdown situation brings understanding and realization towards the improvement of air quality and its subsequent effects. The present study investigates the impact of the COVID-19-related lockdown on the spatiotemporal variation of the ambient air quality in Rourkela City with a tropical climatic setup. The concentration and distribution of various pollutants are well explained by the wind rose and Pearson correlation. There is considerable spatiotemporal variation in the city's ambient air quality, as determined by a two-way ANOVA test comparing sampling sites and months. During the COVID-19 lockdown phases, the air quality of Rourkela witnessed an improvement in annual AQI ranging from 12.64 to 26.85% across the city. However, the air quality in the city deteriorated by 13.76-65.79% after the revocation of COVID-19 restrictions. The paired sample T-test justified that the air quality of Rourkela was significantly healthier in 2020 compared to both 2019 and 2021. Spatial interpolation reveals that the ambient air quality of Rourkela ranged from satisfactory to moderate categories throughout the entire study period. 31.93% area of the city has experienced an improvement in AQI from the Moderate to the satisfying category from 2019 to 2020, whereas about 68.78% area of the city has witnessed a decline in AQI from satisfactory to moderate category from 2020 to 2021.

The impact of meteorological factors on the spread of COVID-19

Background

Clinical studies suggest that warmer climates slow the spread of viral infections. In addition, exposure to cold weakens human immunity.

Aim

This study describes the relationship between meteorological indicators, the number of cases, and mortality in patients with confirmed coronavirus disease 2019 (COVID-19).

Patients and Methods

This was a retrospective observational study. Adult patients who presented to the emergency department with confirmed COVID-19 were included in the study. Meteorological data [mean temperature, minimum (min) temperature, maximum (max) temperature, relative humidity, and wind speed] for the city of Istanbul were collected from the Istanbul Meteorology 1^st Regional Directorate.

Results

The study population consisted of 169,058 patients. The highest number of patients were admitted in December (n = 21,610) and the highest number of deaths (n = 46) occurred in November. In a correlation analysis, a statistically significant, negative correlation was found between the number of COVID-19 patients and mean temperature (rho = -0.734, P < 0.001), max temperature (rho = -0.696, P < 0.001) or min temperature (rho = -0.748, P < 0.001). Besides, the total number of patients correlated significantly and positively with the mean relative humidity (rho = 0.399 and P = 0.012). The correlation analysis also showed a significant negative relationship between the mean, maximum, and min temperatures and the number of deaths and mortality.

Conclusion

Our results indicate an increased number of COVID-19 cases during the 39-week study period when the mean, max, and min temperatures were consistently low and the mean relative humidity was consistently high.

Spatial shifting of COVID-19 clusters and disease association with environmental parameters in India: A time series analysis

BACKGROUND

The viability and virulence of COVID-19 are complex in nature. Although the relationship between environmental parameters and COVID-19 is well studied across the globe, in India, such studies are limited. This research aims to explore long-term exposure to weather conditions and the role of air pollution on the infection spread and mortality due to COVID-19 in India.

METHOD

District-level COVID-19 data from April 26, 2020 to July 10, 2021 was used for the study. Environmental determinants such as land surface temperature, relative humidity (RH), Sulphur dioxide (SO₂), Nitrogen dioxide (NO₂), Ozone (O₃), and Aerosol Optical Depth (AOD) were considered for analysis. The bivariate spatial association was used to explore the spatial relationship between Case Fatality Rate (CFR) and these environmental factors. Further, the Bayesian multivariate linear regression model was applied to observe the association between environmental factors and the CFR of COVID-19.

RESULTS

Spatial shifting of COVID-19 cases from Western to Southern and then Eastern parts of India were well observed. The infection rate was highly concentrated in most of the Western and Southern regions of India, while the CFR shows more concentration in Northern India along with Maharashtra. Four main spatial clusters of infection were recognized during the study period. The time-series analysis indicates significantly more CFR with higher AOD, O₃, and NO₂ in India.

CONCLUSIONS

COVID-19 is highly associated with environmental parameters and air pollution in India. The study provides evidence to warrant consideration of environmental parameters in health models to mediate potential solutions. Cleaner air is a must to mitigate COVID-19.