Spatio-temporal epidemiology and associated indicators of COVID-19 (wave-I and II) in India.

The spatio-temporal distribution of COVID-19 across India's states and union territories is not uniform, and the reasons for the heterogeneous spread are unclear. Identifying the space-time trends and underlying indicators influencing COVID-19 epidemiology at micro-administrative units (districts) will help guide public health strategies. The district-wise daily COVID-19 data of cases and deaths from February 2020 to August 2021 (COVID-19 waves-I and II) for the entire country were downloaded and curated from public databases. The COVID-19 data normalized with the projected population (2020) and used for space-time trend analysis shows the states/districts in southern India are the worst hit. Coastal districts and districts adjoining large urban regions of Mumbai, Chennai, Bengaluru, Goa, and New Delhi experienced > 50,001 cases per million population. Negative binomial regression analysis with 21 independent variables (identified through multicollinearity analysis, with VIF < 10) covering demography, socio-economic status, environment, and health was carried out for wave-I, wave-II, and total (wave-I and wave-II) cases and deaths. It shows wealth index, derived from household amenities datasets, has a high positive risk ratio (RR) with COVID-19 cases (RR: 3.577; 95% CI: 2.062-6.205) and deaths (RR: 2.477; 95% CI: 1.361-4.506) across the districts. Furthermore, socio-economic factors such as literacy rate, health services, other workers' rate, alcohol use in men, tobacco use in women, overweight/obese women, and rainfall have a positive RR and are significantly associated with COVID-19 cases/deaths at the district level. These positively associated variables are highly interconnected in COVID-19 hotspot districts. Among these, the wealth index, literacy rate, and health services, the key indices of socio-economic development within a state, are some of the significant indicators associated with COVID-19 epidemiology in India. The identification of district-level space-time trends and indicators associated with COVID-19 would help policymakers devise strategies and guidelines during public health emergencies.

Occurrence and seasonal disparity of emerging endocrine disrupting chemicals in a drinking water supply system and associated health risk.

Contamination of drinking water with endocrine-disrupting chemicals (EDCs) raises concerns over the security and long-term sustainability of clean water supplies as well as human exposure via daily water intake. In this study, the seasonal disparity and occurrence of six phthalates and bisphenol-A in the drinking water supply system and associated health-risk were examined. The detection frequencies of the ∑6PAEs ranged from 24 to 100% in the winter whereas; in summer it is below the detection limit up to 100%. DEHP was the most prevalent phthalate congener ranging from 1.14 to 8351.85 µg/L (winter) and 0.552 to 410.29 µg/L (summer) surpassing the permissible limit. However, BPA concentrations were found under the permissible limit. The results suggested that PAEs concentration displayed significant seasonal variations with the highest in winter and the lowest in summer. The exposure to PAEs and BPA from drinking water was assessed, indicating a possible health risk to humans with a hazard quotient (HQ) > 1 for DEHP only. The findings necessitate an immediate scrutiny of these EDCs in drinking water supply system and are critical for implementing effective technologies at the WTP scale to ensure the quality and safety of drinking water to ascertain human and environmental health.