Background Financing for NCDs is encumbered by out-of-pocket expenditure (OOPE) assuming catastrophic proportions. Therefore, it is imperative to investigate the extent of catastrophic health expenditure (CHE) on NCDs, which are burgeoning in India. Thus, our paper aims to examine the extent of CHE and impoverishment in India, in conjunction with socio-economic determinants impacting the CHE. Methods We used cross-sectional data from nationwide healthcare surveys conducted in 2014 and 2017–18. OOPE on both outpatient and inpatient treatment was coalesced to estimate CHE on NCDs. Incidence of CHE was defined as proportion of households with OOPE exceeding 10% of household expenditure. Intensity of catastrophe was ascertained by the measure of Overshoot and Mean Positive Overshoot Indices. Further, impoverishing effects of OOPE were assessed by computing Poverty Headcount Ratio and Poverty Gap Index using India’s official poverty line. Concomitantly, we estimated the inequality in incidence and intensity of catastrophic payments using Concentration Indices. Additionally, we delineated the factors associated with catastrophic expenditure using Multinomial Logistic Regression. Results Results indicated enormous incidence of CHE with around two-third households with NCDs facing CHE. Incidence of CHE was concentrated amongst poor that further extended from 2014(CI = − 0.027) to 2017–18(CI = − 0.065). Intensity of CHE was colossal as households spent 42.8 and 34.9% beyond threshold in 2014 and 2017-18 respectively with poor enduring greater overshoot vis-à-vis rich (CI = − 0.18 in 2014 and CI = − 0.23 in 2017–18). Significant immiserating impact of NCDs was unraveled as one-twelfth in 2014 and one-eighth households in 2017–18 with NCD burden were pushed to poverty with poverty deepening effect to the magnitude of 27.7 and 30.1% among those already below poverty on account of NCDs in 2014 and 2017–18 respectively. Further, large inter-state heterogeneities in extent of CHE and impoverishment were found and multivariate analysis indicated absence of insurance cover, visiting private providers, residing in rural areas and belonging to poorest expenditure quintile were associated with increased likelihood of incurring CHE. Conclusion Substantial proportion of households face CHE and subsequent impoverishment due to NCD related expenses. Concerted efforts are required to augment the financial risk protection to the households, especially in regions with higher burden of NCDs.

Background Long distances to facilities, topographical constraints, inadequate service capacity of institutions and insufficient/ rudimentary road & transportation network culminate into unprecedented barriers to access. These barriers gets exacerbated in presence of external factors like conflict and political disruptions. Thus, this study was conducted in rural, remote and fragile region in India measuring geographical accessibility and modelling spatial coverage of public healthcare network.

Background Due to uncertainties encompassing the transmission dynamics of COVID-19, mathematical models informing the trajectory of disease are being proposed throughout the world. Current pandemic is also characterized by surge in hospitalizations which has overwhelmed even the most resilient health systems. Therefore, it is imperative to assess health system preparedness in tandem with need projections for comprehensive outlook. Objective We attempted this study to forecast the need for hospital resources for one year period and correspondingly assessed capacity and tipping points of Indian health system to absorb surges in need due to COVID-19. Methods We employed age-structured deterministic SEIR model and modified it to allow for testing and isolation capacity to forecast the need under varying scenarios. Projections for documented cases were made for varying degree of containment and mitigation strategies. Correspondingly, data on health resources was collated from various government records. Further, we computed daily turnover of each of these resources which was then adjusted for proportion of cases requiring mild, severe and critical care to arrive at maximum number of COVID-19 cases manageable by health care system of India. Findings Our results revealed pervasive deficits in the capacity of public health system to absorb surge in need during peak of epidemic. Also, model suggests that continuing strict lockdown measures in India after mid-May 2020 would have been ineffective in suppressing total infections significantly. Augmenting testing to 1,500,000 tests per day during projected peak (mid-September) under social-distancing measures and current test to positive rate of 9.7% would lead to more documented cases (60, 000, 000 to 90, 000, 000) culminating to surge in demand for hospital resources. A minimum allocation of 13x, 70x and 37x times more beds for mild cases, ICU beds and mechanical ventilators respectively would be required to commensurate with need under that scenario. However, if testing capacity is limited to 9,000,000 tests per day (current situation as of 19th August 2020) under continued social-distancing measures, documented cases would plummet significantly, still requiring 5x, 31x and 16x times the current allocated resources (beds for mild cases, ICU beds and mechanical ventilators respectively) to meet unmet need for COVID-19 treatment in India.

The article hinged upon exploring the patterns and determinants of healthcare utilization and financing amongst particularly vulnerable tribal groups (PVTG's) in Nilgiri district of Tamil Nadu. Three PVTG's viz Paniyas (P), Kattunayakans (KN) and Bettakurumbas (BK) are explored in the study. These groups have some quint essential features impacting the healthcare seeking behaviour e.g. Paniyas were subject to historical repression after they were brought over from Kerala as agricultural labourers culminating into their seclusion and accentuated patient provider wedge. Kattunayackans have their behaviour embedded in using magico-religious beliefs and indigenous medicines. Bettakurumbas are the other forest dwellers residing in Nilgiris biosphere reserve and contemporaneously seek institutional care. Mixed method approach (amalgamation of quantitative and qualitative) was adopted and the households were selected through two stage stratified random sampling. The health seeking behaviour was captured by running a Logit model and Blinder Oaxaca decomposition analysis was conducted to decompose the health gap amongst the tribal groups.

Background Health outcomes in India are characterized by pervasive inequities due to deeply entrenched socio-economic gradients amongst the population. Therefore, it is imperative to investigate these systematic disparities in health, however, evidence of inequities does not commensurate with its policy objectives in India. Thus, our paper aims to examine the magnitude of and trends in horizontal inequities in self-reported morbidity and untreated morbidity in India over the period of 2004 to 2017–18. Methods The study used cross-sectional data from nationwide healthcare surveys conducted in 2004, 2014 and 2017–18 encompassing sample size of 3,85,055; 3,35,499 and 5,57,887 individuals respectively. Erreygers concentration indices were employed to discern the magnitude and trend in horizontal inequities in self-reported morbidity and untreated morbidity. Need standardized concentration indices were further used to unravel the inter-regional and intra-regional income related inequities in outcomes of interest. Additionally, regression based decomposition approach was applied to ascertain the contributions of both legitimate and illegitimate factors in the measured inequalities. Results Estimates were indicative of profound inequities in self-reported morbidity as inequity indices were positive and significant for all study years, connoting better-off reporting more morbidity, given their needs. These inequities however, declined marginally from 2004(HI: 0.049, p< 0.01) to 2017–18(HI: 0.045, P< 0.01). Untreated morbidity exhibited pro-poor inequities with negative concentration indices. Albeit, significant reduction in horizontal inequity was found from 2004(HI= − 0.103, p< 0.01) to 2017–18(HI = − 0.048, p< 0.01) in treatment seeking over the years. The largest contribution of inequality for both outcomes stemmed from illegitimate variables in all the study years. Our findings also elucidated inter-state heterogeneities in inequities with high-income states like Andhra Pradesh, Kerala and West Bengal evincing inequities greater than all India estimates and Northeastern states divulged equity in reporting morbidity. Inequities in untreated morbidity converged for most states except in Punjab, Chhattisgarh and Himachal Pradesh where widening of inequities were observed from 2004 to 2017–18. Conclusions Pro-rich and pro-poor inequities in reported and untreated morbidities respectively persisted from 2004 to 2017–18 despite reforms in Indian healthcare. Magnitude of these inequities declined marginally over the years. Health policy in India should strive for targeted interventions closing inequity gap.