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Background Lymphatic filariasis (LF) is a mosquito-borne disease caused by filarial worms. The WHO has targeted LF elimination by 2030. Mathematical models can help evaluate and guide elimination strategies. Methods We developed a new compartmental model—COmpartmental Modelling of Elimination strategies and Transmission of Lymphatic Filariasis (COMET-LF)—to assess the impact of mass drug administration (MDA) on LF elimination. Our model incorporates efficacy data from clinical trials and generates estimates of disease (lymphoedema and hydrocele) prevalence. The model is calibrated to publicly available microfilaria (Mf) and disease prevalence data (2008-2013), and validated using programmatic data (2018-2019) from ten endemic districts of Bihar, India. Results COMET-LF simulation projected that at 85% coverage with a two- or three-drug regimen, six rounds of MDA should be sufficient to achieve elimination for baseline Mf prevalence up to 10%, consistent with the existing models - EPIFIL and LYMFASIM. The impact of MDA on disease burden, generated using COMET-LF, suggest that the disease prevalence reduces over much longer timescales - 20 years for a reduction of 8%-11.5% following 5 rounds of MDA. To investigate the role of migration, we implemented COMET-LF within a meta-population model. We found that high Mf prevalence in the spatial neighbourhood can require up to 3 additional rounds for the two-drug regimen. Migration between non-endemic and adjacent endemic regions (>5% Mf) may lead to a significant risk of resurgence. Conclusion Our COMET-LF model can capture LF transmission dynamics and estimate the number of MDA rounds required to reach elimination. MDA coverage, baseline Mf prevalences and human migration are the determinants of the required rounds of MDA. Our model can be easily tailored to specific blocks and districts to guide programmatic intervention for LF elimination and disease management.

IntroductionIndia’s progress in reducing maternal and neonatal mortality since the 1990s was faster than the regional average. We systematically analysed how national health policies, services for maternal and newborn health, and socioeconomic contextual changes, drove these mortality reductions.MethodsThe study’s mixed-methods design integrated quantitative trend analyses of mortality, intervention coverage and equity since the 1990s, using the sample registration system and national surveys, with interpretive understandings from policy documents and 13 key informant interviews.ResultsIndia’s maternal mortality ratio (MMR) declined from 412 to 103 maternal deaths per 100 000 live births between 1997–1998 and 2017–2019. The neonatal mortality rate (NMR) declined from 46 to 22 per 1000 live births between 1997 and 2019. The average annual rate of mortality reduction increased over time. During this period, coverage of any antenatal care (57%–94%), quality antenatal care (37%–85%) and institutional delivery (34%–90%) increased, as did caesarean section rates among the poorest tertile (2%–9%); these coverage gains occurred primarily in the government (public) sector. The fastest rates for increasing coverage occurred during 2005–2012.The 2005–2012 National Rural Health Mission (which became the National Health Mission in 2012) catalysed bureaucratic innovations, additional resources, pro-poor commitments and accountability. These efforts occurred alongside smaller family sizes and improvements in macroeconomic growth, mobile and road networks, women’s empowerment, and nutrition. These together reduced high-risk births and improved healthcare access, particularly among the poor.ConclusionRapid reduction in NMR and MMR in India was accompanied by increased coverage of maternal and newborn health interventions. Government programmes strengthened public sector services, thereby expanding the reach of these interventions. Simultaneously, socioeconomic and demographic shifts led to fewer high-risk births. The study’s integrated methodology is relevant for generating comprehensive knowledge to advance universal health coverage.

BackgroundIndia’s progress in reducing maternal and newborn mortality since the 1990s has been exemplary across diverse contexts. This paper examines progress in two state clusters: higher mortality states (HMS) with lower per capita income and lower mortality states (LMS) with higher per capita income.MethodsWe characterised state clusters’ progress in five characteristics of a mortality transition model (mortality levels, causes, health intervention coverage/equity, fertility and socioeconomic development) and examined health policy and systems changes. We conducted quantitative trend analyses, and qualitative document review, interviews and discussions with national and state experts.ResultsBoth clusters reduced maternal and neonatal mortality by over two-thirds and half respectively during 2000–2018. Neonatal deaths declined in HMS most on days 3–27, and in LMS on days 0–2. From 2005 to 2018, HMS improved coverage of antenatal care with contents (ANCq), institutional delivery and postnatal care (PNC) by over three-fold. In LMS, ANCq, institutional delivery and PNC rose by 1.4-fold. C-sections among the poorest increased from 1.5% to 7.1% in HMS and 5.6% to 19.4% in LMS.Fewer high-risk births (to mothers <18 or 36+ years, birth interval <2 years, birth order 3+) contributed 15% and 6% to neonatal mortality decline in HMS and LMS, respectively. Socioeconomic development improved in both clusters between 2005 and 2021; HMS saw more rapid increases than LMS in women’s literacy (1.5-fold), household electricity (by 2-fold), improved sanitation (3.2-fold) and telephone access (6-fold).India’s National (Rural) Health Mission’s financial and administrative flexibility allowed states to tailor health system reforms. HMS expanded public health resources and financial schemes, while LMS further improved care at hospitals and among the poorest.ConclusionTwo state clusters in India progressed in different mortality transitions, with efforts to maximise coverage at increasingly advanced levels of healthcare, alongside socioeconomic improvements. The transition model characterises progress and guides further advances in maternal and newborn survival.

Background : With epidemiological transition, stroke has emerged as a public health priority in rural India. However, population-level information on secondary prevention of stroke from rural areas of India and other low- and middle-income countries remains exceedingly rare. Methods : In a cross-sectional community-based survey, trained surveyors screened a well-defined population of 74,095 individuals living in 64 villages in Gadchiroli district of India for symptoms of stroke. A trained physician evaluated screen positive patients, diagnosed stroke, measured blood pressure and collected information on prior diagnosis of risk factors and current use of medications using a structured questionnaire. Results : A total of 265 stroke survivors were identified. Prior diagnosis of hypertension was made in 57.4%, diabetes in 9.8%, hyperlipidaemia in 0.4%, ischaemic heart disease in 1.5%. and atrial fibrillation in 1.1%. Blood pressure was uncontrolled (>140/90) in 46% of stroke survivors. Among men 71.2% used tobacco and 30% used alcohol, while among women 38.2% used tobacco and none used alcohol. Only 40.8% of stroke survivors were receiving antihypertensive medications, while 10.6% were on antiplatelet agents and 4.9% were on statins. In a multivariate analysis, age <50 years (OR 0.2, 95% CI 0.1-0.5), male sex (OR 0.2, 95% CI 0.2-0.8) and lower economic status (no assets vs four assets; OR 0.3, 95% CI 0.1-0.9) were associated with lower odds of receiving medications for secondary prevention of stroke. Conclusions : There were significant gaps in secondary prevention of stroke in rural Gadchiroli. Healthcare programmes for secondary prevention of stroke in rural areas will have to ensure that blood pressure is adequately controlled, alcohol and tobacco cessation is promoted and special attention is paid to those who are younger, men and economically weaker.