Cost-effectiveness of incorporating Mycobacterium indicus pranii vaccine to multidrug therapy in newly diagnosed leprosy cases for better treatment outcomes & immunoprophylaxis in contacts as leprosy control measures for National Leprosy Eradication Programme in India

BACKGROUND & OBJECTIVES: The elimination goal for leprosy as a public health problem at the national level was achieved in 2005 in India. However, the number of new cases reporting annually remained nearly the same during the last 10-15 years. Moreover, a substantial number of these new cases reported disabilities for the first time. Therefore, besides multidrug therapy (MDT), newer strategies with focus on effectively decreasing the number of new cases, optimizing the treatment of detected cases, averting disabilities and arresting the transmission of the disease are required. So the objective of this study was to assess the cost-effectiveness of Mycobacterium indicus pranii (MIP) vaccine implementation in National Leprosy Eradication Programme (NLEP) for newly diagnosed leprosy patients as well as their contacts to arrest/decrease the transmission and occurrence of new cases. METHODS: This was a model-based estimation of incremental costs, total quality-adjusted life years (QALYs) gained, new cases averted, deaths averted, incremental cost-effectiveness ratio (ICER) and budget impact of the vaccination intervention. This model included the addition of MIP treatment intervention to the newly detected leprosy patients as well as vaccination with MIP to their contacts. RESULTS: Using the societal perspective, discounted ICER was estimated to be ₹73,790 per QALY gained over a five-year time period. Probabilistic sensitivity analysis (PSA) was assessed by varying the values of input parameters. Majority (96%) of simulations fell in North East quadrant of cost-effectiveness plane, which were all below the willingness to pay threshold. INTERPRETATION & CONCLUSIONS: Introduction of MIP vaccination in the NLEP appears to be a cost-effective strategy for India. Significant health gains were reduction in the number of new leprosy cases, decreased incidence and severity of reactions during treatment, and after release from treatment, prevention of disabilities, thus reducing the cost as well as stigma of the disease

A national-level analysis of life expectancy associated with the COVID-19 pandemic in India.

BACKGROUND From a demographic perspective, the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on life expectancy is not clear. Hence, there is a need to study the number of years of life lost concerning the existing average life expectancy due to COVID-19 in India. OBJECTIVE This study aimed to estimate the impact of life expectancy due to the COVID-19 pandemic in India. METHODOLOGY We considered day-wise age-specific mortality due to COVID-19 which was extracted from the COVID-19 data repository from March 11, 2020, to June 30, 2021, in India. All-cause mortality was collected from the United Nations population estimates. An abridged life table technique was utilized for calculating life expectancies based on all-cause mortality and mortality due to COVID-19. MortPak software was used to calculate the life expectancy with and without the COVID-19 pandemic. Life expectancy at birth in different age groups was estimated with respect to with and without COVID-19. RESULTS A total of 399,459 deaths due to COVID-19 were distributed age wise, and their corresponding life expectancy was calculated. The general mortality was compared with COVID-19 mortality for the various age groups, and it was observed that mortality due to COVID-19 was significantly higher among the elderly age group [i.e., 45 to 60 years (36%) and > 60 years (51%)] when compared with < 25 years (1%) and 26-44 years (11%) (trend Chi-square 7.59; = 0.001). The life expectancy without and with COVID-19 was 69.28 years and 69.16 years, respectively. CONCLUSION Overall, it was estimated that COVID-19 has an impact on life expectancy by 0.12 years during the study period. Even though mortality due to COVID-19 was high, factors such as lockdown, vaccination, and accidents also had an influence on mortality. Thus, there is a need to assess the impact of COVID-19 on life expectancy in future

Time Elapsed from Onset of Symptoms to Antituberculosis Treatment in Children with Central Nervous System Tuberculosis in a Tertiary Hospital in South India: A Mixed‑Methods Pilot Study

A pilot study with a mixed‑methods design was conducted to estimate the time for tuberculosis (TB) treatment initiation and associated factors among children with central nervous system‑TB (CNS‑TB). A total of 38 children were enrolled for the quantitative component, and 20 in‑depth interviews were conducted. The median duration (interquartile range) from onset of symptoms to treatment initiation was 23 (11, 55) days. About 44% and 31% of the children presented with Stage II and Stage III of CNS‑TB, respectively. The major reasons for delay were symptoms not taken seriously (50%) and too many referrals (21%). About 89% of the families went into catastrophic health expenditure due to the disease. The treatment delay may be due to both patient delay and health system delay. Tailoring approaches to target the pediatric population could further improve early detection and treatment initiation of CNS‑TB

Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients

BACKGROUND: The use of Bayesian Structural Equation Model (BSEM) to evaluate the impact of TB on self-reported health related quality of life (HRQoL) of TB patients has been not studied. OBJECTIVE: To identify the factors that contribute to the HRQoL of TB patients using BSEM. METHODS: This is a latent variable modeling with Bayesian approach using secondary data. HRQoL data collected after one year from newly diagnosed 436 TB patients who were registered and successfully completed treatment at Government health facilities in Tiruvallur district, south India under the National TB Elimination Programme (NTEP) were used for this analysis. In this study, the four independent latent variables such as physical well–being (PW = PW1-7), mental well-being (MW = MW1-7), social well-being (SW = SW1-4) and habits were considered. The BSEM was constructed using Markov Chain Monte Carlo algorithm for identifying the factors that contribute to the HRQoL of TB patients who completed treatment. RESULTS: Bayesian estimates were obtained using 46,300 observations after convergence and the standardized structural regression estimate of PW, MW, SW on HRQoL were 0.377 (p<0.001), 0.543 (p<0.001) and 0.208 (p<0.001) respectively. The latent variables PW, MW and SW were significantly associated with HRQoL of TB patients. The age was found to be significantly negatively associated with HRQoL of TB patients. CONCLUSIONS: The current study demonstrated the application of BSEM in evaluating HRQoL. This methodology may be used to study precise estimates of HRQoL of TB patients in different time points

Cost of digital technologies and family-observed DOT for the 9-month injectable-containing MDR-TB regimen

Background: In 2017 WHO recommended the use of digital technologies, such as medication monitors and video observed treatment (VOT) for directly-observed treatment (DOT) of drug-susceptible TB, with no policy recommendations for multidrug-resistant TB (MDR-TB), which imposes considerably higher patient-costs. Given the COVID-related demand on health systems, the benefits of transitioning towards more patient-centred approaches are increasingly relevant. Design/Methods: A decision-tree model was developed to explore the cost-effectiveness of several DOT replacement approaches including VOT, 99DOTS and family-observed DOT. Assuming a 9-month, injectable-containing regimen (as evaluated within the STREAM trial), we constructed base-case models to reflect the standard-of-care in Ethiopia, India, and Uganda. The model used STREAM data supplemented with published studies, with sensitivity analyses conducted on key parameters. Results: Modelling suggested that standard-of-care is the most expensive strategy in India and Uganda, with considerable direct- and indirect-costs incurred by patients. In Ethiopia, implementing VOT and 99DOTS increased health-system costs by US$402 and US$17 respectively, but patient-costs remained lower than for standard-of-care. These higher health-system costs were largely caused by up-front technology expenditure, with 80% of Ethiopians not owning a smartphone. Sensitivity analyses showed costs were sensitive to both loss-to-follow-up and relapse rates. However, only the VOT strategy in Uganda exceeded standard-of-care DOT costs, by US$70 per patient, when the relapse rate was equalled to the upper-bound of the confidence interval. Modelling suggested each of VOT, 99DOTS, and family-observed DOT would halve patients’ out-of-pocket costs. Taking a patient perspective, each strategy appeared highly cost-effective across all countries, even if implemented solely in continuation phase. Conclusions: While data on the costs and efficacy of switching MDR-TB treatment management to new technologies are lacking, our modelling suggests alternative DOT support strategies can significantly reduce patient-costs. Health-system costs however are more country-specific, depending heavily on both internet availability and smartphone penetration within the population

Long-term Survival of Treated Tuberculosis Patients in Comparison to a General Population In South India: A Matched Cohort Study

Objectives: This study aimed to measure the mortality rate, potential years of life lost, and excess general mortality among individuals treated for pulmonary tuberculosis (TB) in a TB endemic country. Methods: A retrospective analysis was conducted on a population-based cohort study of 4022 TB patients and 12,243 gender-matched and age-matched controls from prevalence surveys conducted between 2000 and 2004 in the Thiruvallur district of Tamil Nadu, South India. Results: The mortality rate among TB patients was 59/1000 person-years. The excess standardized mortality ratio was 2.3 (95% CI: 1.7–3.1). The rate of potential years of life lost was 6.15/1000 (95% CI: 5.97–6.33) in the TB cohort compared to the general population of 1.52/1000 (95% CI: 1.46–1.60). Individuals aged >50 years, those underweight (<40 kg), with treatment failures, or lost to follow-up had higher mortality rates when compared with the rest of the TB cohort. The risk of death was significantly higher in the TB cohort until the end of the fourth year when compared with later years. Conclusion: Mortality in the TB cohort was 2.3 times higher than in the age-matched general population. Most deaths occurred in the first year after completing treatment. Post-treatment follow-ups and interventions for reducing comorbid conditions are necessary to prevent deaths