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. 2023 Apr 1:222:115288.
doi: 10.1016/j.envres.2023.115288. Epub 2023 Jan 19.

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

Affiliations

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

Arup Jana et al. Environ Res. .

Abstract

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.

Keywords: COVID-19; Environmental parameters; Pandemic; Spatial association; Time series.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Markov Chain Monte Carlo (MCMC) convergence diagnostic plots of CFR and other covariates.
Fig. 2
Fig. 2
Spatial distribution of the pollutants during the study period (April 26, 2020 to July 10, 2021) over India; (a) NO2, (b) SO2, (c) O3 and (d) AOD.
Fig. 3
Fig. 3
Temporal distribution of the pollutants during the study period (April 26, 2020–July 10, 2021) over India.
Fig. 4
Fig. 4
Spatio-temporal distribution of cumulative infected cases of COVID-19 during the study period (April 26, 2020 to July 10, 2021) in India.
Fig. 5
Fig. 5
Time series plot of CFR in India during the study period, April 26, 2020 to July 10, 2021 in India.
Fig. 6
Fig. 6
Spatial distribution of (a) infection rate and (b) CFR of COVID-19 on July 10, 2021 in India.
Fig. 7
Fig. 7
Bivariate spatial association between CFR and (a) Temperature, (b) RH, (c) AOD, (d) NO2, (e) SO2 and (f) O3 during the study period, April 26, 2020 to July 10, 2021 in India.
Fig. 8
Fig. 8
Predicted case fatality rate (CFR) after model fitting.

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