Association of greenness with COVID-19 deaths in India: An ecological study at district level.

BACKGROUND: The world has witnessed a colossal death toll due to the novel coronavirus disease-2019 (COVID-19). A few environmental epidemiology studies have identified association of environmental factors (air pollution, greenness, temperature, etc.) with COVID-19 incidence and mortality, particularly in developed countries. India, being one of the most severely affected countries by the pandemic, still has a dearth of research exploring the linkages of environment and COVID-19 pandemic. OBJECTIVES: We evaluate whether district-level greenness exposure is associated with a reduced risk of COVID-19 deaths in India. METHODS: We used average normalized difference vegetation index (NDVI) from January to March 2019, derived by Oceansat-2 satellite, to represent district-level greenness exposure. COVID-19 death counts were obtained through May 1, 2021 (around the peak of the second wave) from an open portal: covid19india.org. We used hierarchical generalized negative binomial regressions to check the associations of greenness with COVID-19 death counts. Analyses were adjusted for air pollution (PM2.5), temperature, rainfall, population density, proportion of older adults (50 years and above), sex ratio over age 50, proportions of rural population, household overcrowding, materially deprived households, health facilities, and secondary school education. RESULTS: Our analyses found a significant association between greenness and reduced risk of COVID-19 deaths. Compared to the districts with the lowest NDVI (quintile 1), districts within quintiles 3, 4, and 5 have respectively, around 32% [MRR = 0.68 (95% CI: 0.51, 0.88)], 39% [MRR = 0.61 (95% CI: 0.46, 0.80)], and 47% [MRR = 0.53 (95% CI: 0.40, 0.71)] reduced risk of COVID-19 deaths. The association remains consistent for analyses restricted to districts with a rather good overall death registration (>80%). CONCLUSION: Though cause-of-death statistics are limited, we confirm that exposure to greenness was associated with reduced district-level COVID-19 deaths in India. However, material deprivation and air pollution modify this association.

Household air pollution during COVID-19 pandemic: A concern in India.

Household air pollution is a serious public health concern in India with more than half of the Indian households relying on solid fuel use. The long periods of lockdown related measures to control COVID-19 pandemic in India further aggravated the adverse health effects of household air pollution as millions Indians were exposed to high level of health-damaging air pollutants inside their homes. This commentary discusses the vulnerability of the socioeconomically disadvantaged population forced to stay indoors during the pandemic. Exposure to household air pollution has detrimental effects on health, which might put individuals at higher risk for complications related to COVID-19. A large proportion of socioeconomically disadvantaged section of the population were exposed to critical levels of household air pollution and more vulnerable to severe health effects of COVID-19. There is a pressing need to understand the aggravated health consequences of household air pollution in association with COVID-19.

Fractional SIR-Model for Estimating Transmission Dynamics of COVID-19 in India

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model’s transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.