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Background Mortality estimates at the subnational level are of urgent need in India for the formulation of policies and programmes at the district level. This is the first-ever study which used survey data for the estimation of life expectancy at birth ( ) for the 640 districts from NFHS-4 (2015-16) and 707 districts from NFHS-5 (2019-21) for the total, male and female population in India. Methods This study calculated annual age-specific mortality rates from NFHS-4 and NFHS-5 for India and all 36 states for the total, male and female population. This paper constructed the abridged life tables and estimated life expectancy at birth and further estimated the model parameters for all 36 states. This study linked state-specific parameters to the respective districts for the estimation of life expectancy at birth for 640 districts from NFHS-4 and 707 districts from NFHS-5 for the total, male and female population in India. Results Findings at the state level showed that there were similarities between the estimated and calculated in most of the states. The results of this article observed that the highest varies in the ranges of 70 to 90 years among the districts of the southern region. falls below 70 years among most of the central and eastern region districts. In the northern region districts lies in the range of 70 years to 75 years. The estimates of life expectancy at birth shows the noticeable variations at the state and district levels for the person, male, and female populations from the NFHS (2015-16) and NFHS (2019-21). In the absence of age-specific mortality data at the district level in India, this study used the indirect estimation method of relating state-specific model parameters with the IMR of their respective districts and estimated across the 640 districts from NFHS-4 (2015-16) and 707 districts from NFHS-5 (2019-21). The findings of this study have similarities with the state-level estimations of from both data sources of SRS and NFHS and found the highest in the southern region and the lowest in the eastern and central region districts. Conclusions In the lack of estimates at the district level in India, this study could be beneficial in providing timely life expectancy estimates from the survey data. The findings clearly shows variations in the district level . The districts from the southern region show the highest and districts from the central and eastern region has lower . Females have higher as compared to the male population in most of the districts in India.

Background Quantifying excess deaths and their impact on life expectancy at birth (e 0 ) provide a more comprehensive understanding of the burden of coronavirus disease of 2019 (COVID-19) on mortality. The study aims to comprehend the repercussions of the burden of COVID-19 disease on the life expectancy at birth and inequality in age at death in India. Methods The mortality schedule of COVID-19 disease in the pandemic year 2020 was considered one of the causes of death in the category of other infectious diseases in addition to other 21 causes of death in the non-pandemic year 2019 in the Global Burden of Disease (GBD) data. The measures e 0 and Gini coefficient at age zero (G 0 ) and then sex differences in e 0 and G 0 over time were analysed by assessing the age-specific contributions based on the application of decomposition analyses in the entire period of 2010–2020. Results The e 0 for men and women decline from 69.5 and 72.0 years in 2019 to 67.5 and 69.8 years, respectively, in 2020. The e 0  shows a drop of approximately 2.0 years in 2020 when compared to 2019. The sex differences in e 0 and G 0 are negatively skewed towards men. The trends in e 0 and G 0 value reveal that its value in 2020 is comparable to that in the early 2010s. The age group of 35–79 years showed a remarkable negative contribution to Δe 0 and ΔG 0 . By causes of death, the COVID-19 disease has contributed − 1.5 and − 9.5%, respectively, whereas cardiovascular diseases contributed the largest value of was 44.6 and 45.9%, respectively, to sex differences in e 0 and G 0 in 2020. The outcomes reveal a significant impact of excess deaths caused by the COVID-19 disease on mortality patterns. Conclusions The COVID-19 pandemic has negative repercussions on e 0 and G 0 in the pandemic year 2020. It has severely affected the distribution of age at death in India, resulting in widening the sex differences in e 0 and G 0 . The COVID-19 disease demonstrates its potential to cancel the gains of six to eight years in e 0 and five years in G 0 and has slowed the mortality transition in India.

Background Measuring life expectancy and life disparity can assist in comprehending how the COVID-19 pandemic has affected the mortality estimates in the Indian population. The present study aims to study the life expectancy and life disparity at birth at the national and subnational levels before and during the COVID-19 pandemic using the NFHS and SRS data. Methods The measures Life expectancy at birth ( e 0 ) and Life disparity at birth ( e 0 † ) were computed for the non-pandemic and pandemic years from NFHS (2015–16), SRS (2015) and NFHS (2019–21), SRS (2020) respectively at the national and Subnational level in India. Using NFHS data for the 36 states and SRS data for the 22 states, the study calculates e 0 and e 0 † by total, male and female population. Results The e 0 for male and female decline from 64.3 years and 69.2 years in 2015–16 to 62.9 years and 68.9 years in 2019–21. The e 0 shows a drop of approximately 1.4 years for males and 0.3 years for females in the pandemic year 2019–21 when compared to the non-pandemic year 2015–16. At the subnational level e 0 shows a decline for 22 states in person, 23 states in males and 21 states in females in the pandemic year 2019–21 as compared to the non-pandemic years 2015–16. The e 0 † shows a increase for 21 states in person, 24 states in females and 17 states in males in the pandemic year than non-pandemic year. The findings shows a significant losses in e 0 and gains in e 0 † for males than females in the pandemic year as compared to the non-pandemic year at the subnational level in India. Conclusions COVID-19 pandemic has decreased e 0 and increased e 0 † in the pandemic year 2019–21 at the national and subnational level in India. COVID-19 had a significant impact on the age pattern of mortality for many states and male, female population and delayed the mortality transition in India.

India contributes a major share of global unintended births. It is established that contraception plays a significant role in preventing unintended pregnancies, maternal mortality and induced abortion. In this study, to analyze the effectiveness of our family welfare program, we tried to give district-level estimates of number of births averted due to contraception. The study successfully identified the districts that were not performing well at the front of utilization of various family planning methods for birth control. To achieve objectives of National Population Policy (2000), poor-performing districts must be monitored like the government keeps monitoring of Aspirational districts.

Background Under-five mortality is a matter of serious concern for child health as well as the social development of any country. The paper aimed to find the accuracy of machine learning models in predicting under-five mortality and identify the most significant factors associated with under-five mortality. Method The data was taken from the National Family Health Survey (NFHS-IV) of Uttar Pradesh. First, we used multivariate logistic regression due to its capability for predicting the important factors, then we used machine learning techniques such as decision tree, random forest, Naïve Bayes, K- nearest neighbor (KNN), logistic regression, support vector machine (SVM), neural network, and ridge classifier. Each model’s accuracy was checked by a confusion matrix, accuracy, precision, recall, F1 score, Cohen’s Kappa, and area under the receiver operating characteristics curve (AUROC). Information gain rank was used to find the important factors for under-five mortality. Data analysis was performed using, STATA-16.0, Python 3.3, and IBM SPSS Statistics for Windows, Version 27.0 software. Result By applying the machine learning models, results showed that the neural network model was the best predictive model for under-five mortality when compared with other predictive models, with model accuracy of (95.29% to 95.96%), recall (71.51% to 81.03%), precision (36.64% to 51.83%), F1 score (50.46% to 62.68%), Cohen’s Kappa value (0.48 to 0.60), AUROC range (93.51% to 96.22%) and precision-recall curve range (99.52% to 99.73%). The neural network was the most efficient model, but logistic regression also shows well for predicting under-five mortality with accuracy (94% to 95%)., AUROC range (93.4% to 94.8%), and precision-recall curve (99.5% to 99.6%). The number of living children, survival time, wealth index, child size at birth, birth in the last five years, the total number of children ever born, mother’s education level, and birth order were identified as important factors influencing under-five mortality. Conclusion The neural network model was a better predictive model compared to other machine learning models in predicting under-five mortality, but logistic regression analysis also shows good results. These models may be helpful for the analysis of high-dimensional data for health research.

Background Depression among the elderly is well-documented and associated with socio-economic factors, physical and mental health conditions. Few studies have focused on older adults’ physical limitations and depressive symptoms. However, very little is known about marital status’ role in such associations, especially in India. The present study examines the association between physical limitations and self-reported depressive symptoms and moderating role of marital status in such association separately for men and women. Methods The present study used data from the Longitudinal Ageing Study in India (LASI) wave 1, 2017–2018, a nationally and state representative longitudinal large-scale survey of ageing and health. For the present research, a total sample of 20,806 older adults aged 60+ years was selected after excluding missing values. Along with descriptive statistics, binary logistic regression analysis and interaction effect of marital status were applied to examine the association between physical limitations (functional limitations and mobility difficulty) with the depressive symptoms separately for men and women. Results About 58, 50, and 45% elderly reported having depressive symptoms and had difficulty in 2+ ADLs, 2+ IADLs, and 2+ mobility difficulties, respectively. By the marital status, the prevalence of depressive symptoms was higher among currently unmarried than currently married, irrespective of type and number of physical limitations. The unadjusted, marital and multivariate-adjusted association suggested that elderly with more than two ADLs, IADLs, and mobility difficulty had higher odds of depressive symptoms. The gender stratified interaction effect of marital status and physical limitations on depressive symptoms indicated that currently unmarried elderly, particularly unmarried older women with 2+ ADLs (OR = 2.85; CI 95% = 1.88–3.09), 2+ IADLs (OR = 2.01; CI 95% = 1.74–2.31) and 2+ mobility difficulty (OR = 2.20; CI 95% = 1.86–2.60) had higher odds of depressive symptoms. However, such association was only valid for unmarried men having mobility difficulty. Conclusion The study highlights that the elderly with physical limitations such as ADLs, IADLs, and mobility difficulty require attention and care. Although married elderly are less likely to have depressive symptoms even with all the mentioned physical limitations, unmarried women are more vulnerable to have depressive symptoms with physical limitations.

Immuno-modulators in combination with antileishmanial drug miltefosine is a better therapeutic approach for treatment of Visceral Leishmaniasis (VL) as it not only reduces the dose of miltefosine but also shortens the treatment regimen. However, immunological mechanisms behind the perceived benefits of this combination therapy have not been investigated in detail. In the present study, we hypothesized that potential use of drugs that target the host in addition to the parasite might represent an alternative strategy for combination therapy. We investigated immune responses generated in Leishmania donovani infected animals (hamsters and mice) treated with combination of CpG-ODN-2006 and miltefosine at short dose regimen. Infected animals were administered CpG-ODN-2006 (0.4 mg/kg, single dose), as free and liposomal form, either alone or in combination with miltefosine for 5 consecutive days and parasite clearance was evaluated at day 4 and 7 post treatment. Animals that received liposomal CpG-ODN-2006 (lipo-CpG-ODN-2006) and sub-curative miltefosine (5 mg/kg) showed the best inhibition of parasite multiplication (∼97%) which was associated with a biased Th1 immune response in. Moreover, compared to all the other treated groups, we observed increased mRNA expression levels of pro-inflammatory cytokines (IFN-γ, TNF-α and IL-12) and significantly suppressed levels of Th2 cytokines (IL-10 and TGF-β) on day 4 post treatment in animals that underwent combination therapy with lipo-CpG-ODN-2006 and sub-curative miltefosine. Additionally, same therapy also induced heightened iNOS mRNA levels and NO generation, increased IgG2 antibody level and strong T-cell response in these hamsters compared with all the other treated groups. Collectively, our results suggest that combination of lipo-CpG-ODN-2006 and sub-curative miltefosine generates protective T-cell response in an animal model of visceral leishmaniasis which is characterized by strong Th1 biased immune response thereby underlining our hypothesis that combination therapy, at short dose regimen can be used as a novel way of treating visceral leishmaniasis.

Wastewater irrigation is practiced in outskirts of several cities of India. Enhanced growth and productivity of crops possess threat of heavy metal accumulation while irrigated with wastewater. Assessment of heavy metal accumulation in soil flooded with wastewater of Mawaiya drain in Naini region of Allahabad district, using parameter of contamination factor and pollution load index (PLI). Samples of soil were taken from the fields irrigated with wastewater and analyzed for heavy metals by using Atomic Absorption Spectroscopy (AAS). The maximum accumulation of heavy metal was observed for iron in soil. Heavy metal contamination is soil was assessed by estimation of contamination factor which was observed for Cu (0.7858), Fe (296.1864), Zn (0.4304), Pb (1.1661) and Ni (1.8912). Pollution load index (PLI) used for assessment of soil contamination and observed that maximum contamination (PLI, 74.31) was in water stressed conditions of summer. Heavy metals concentration in wastewater and accumulation in soil found within WHO limits in present study which may increase if unmanaged wastewater flooding continued.

In this study, we have presented a hitherto unreported mappable lithofacies of an intercalated unit of arkose and shale of the Dhandraul Formation of the Kaimur Group exposed in Kaimur district, Bihar, India which was not reported by earlier workers in the Vindhyan basin. It is a contribution for understanding the possible provenance, source area weathering, depositional environment, and geodynamic set-up of this member. Based on field characteristics and petrography study, three lithofacies units have been identified viz. (i) coarse to medium-grained arkose, (ii) intercalated sequence of arkose and shale, and (iii) shale. Geochemically, these lithofacies predominantly occupied the field of arkose and shale except samples fall in the field of sub-arkose. These lithofacies display relatively an enrichment of SiO 2 and Al 2 O 3 and show low concentrations of MgO, CaO, Na 2 O, K 2 O, and TiO 2 . The values of ∑REE in arkose are varying from 78.74 to 128.81 ppm whereas the values of fractionation indicate (La/Sm) N (3.73–4.22), (La/Yb) N (7.33–15.59), (Gd/Yb) N (1.32–2.30), and Eu/Eu* (0.58–0.66). In shale, ∑REE ranges from 354.02 to 382.11 ppm while the fractionation contents of (La/Sm) N , (La/Yb) N , and (Gd/Yb) N , and Eu/Eu* are ranging from 3.82 to 4.82, 7.65 to 11.85, 1.38 to 1.73, and 0.56 to 0.81. On the basis of rock fragments and paleocurrent direction, the possible sources are presumed to be the Chhotanagpur Gneissic Complex and the Mahakoshal Group of rocks, which lie towards the south and southwest. In the binary and ternary plots, most of the samples of arkose and shale have mostly occupied the field of passive margin tectonic setting except one sample comes in the field of the continental island arc. Based on mineralogical and textural maturity, sedimentary structures and the overall sequence of these lithofacies from sandstone to shale member of the Dhandraul Formation show fining upward sequence which attributes the deposition in a shallow coastal fluvial-marine environment in a transgressive phase. This finding has opened a new opportunity to relook at the depositional environment of the Dhandraul Formation in other parts of the Vindhyan basin.

The Gorakhpur city experienced several high-intensity tremors because of ongoing seismic activities in the Himalayan region. Therefore, the characterization of its subsurface is crucial for a better assessment of the seismic hazards. Ambient noise measurements at 360 sites single-station and four array sites show the predominant frequency peak varies between 0.434 to 1.02 Hz from horizontal-to-vertical spectral ratio (HVSR) analysis and amplitude increasing toward the north with maximum amplification is 4.81. The structure of the shallow soft soil has been observed by frequency wavenumber (F–K) analysis. Joint inversion of the HVSR and Rayleigh wave dispersion curves reveals three layers of soft, dense and stiff soil sediments of varying thickness. The shear wave velocity (Vs) of the sediment varies between 280 to 1200 m/s from top soil to 100 m subsurface depth. The observed Vs models correspond to soil classifications ranging from soft soil to very dense soil and rock.