Prevention of chronic diseases: reorienting primary health systems in India
Bibliographic record
Abstract
Individuals should be entitled to a "fair innings", and the primary role of health systems should be the prevention of premature mortality. In India, 66 percent of all deaths are premature. The burden of premature mortality has shifted from child (0-5 years) to adult (30-69 years) level over the years - there are three times more deaths happening at the latter vis-à-vis the former level. Nevertheless, primary health systems continue to focus almost exclusively on child mortality. They need to make a health system transition and get engaged in the prevention of risk factors, morbidity and mortality related to chronic diseases - the biggest determinant of adult mortality - together with their original focus on child mortality. This paper analyzes some of the major challenges in terms of governance, manpower and financing that such a transition will be faced with, and offers a number of actionable policy recommendations. It does so based on desk and field research in four Indian states - Uttar Pradesh, Rajasthan, Kerala and Tamil Nadu (two health-backward and two health-advanced) - and four countries - Japan, Canada, United States and Sri Lanka (with varying probability of premature mortality due to non-communicable diseases) - involving semi-structured interviews with close to 200 stakeholders from policy, industry, international organizations, civil society and the academia. A reorientation of national and state health policies, systems and resources (financial, human and infrastructural) is urgently required to begin addressing the massive burden of premature mortality due to chronic diseases in India - the highest in the world - and prevent human and economic costs associated with them. State governments will have to embrace their legal responsibility of being the primary agents for the survival and health of their population. Their role is also the most critical because prevention of chronic diseases requires a sustained, long-term engagement, which neither the Centre nor international organizations could commit to. There will, however, be macro roles - visionary, regulatory, financial, technical, etc. - that the Centre will have to play towards this end.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".