Broadening the vaccine metaphor: The adequate balanced food (ABF) vaccine against tuberculosis (Acid-fast bacilli/AFB) and more
Bibliographic record
Abstract
Nutrition is essential to survival, health, and protection from disease across the lifespan. In the 1970s, an adequate diet was described as the most effective vaccine available for respiratory, diarrheal, and other common infections, as nutritional supplementation reduced these in the setting of undernutrition. Recently, the RATIONS (Reducing Activation of Tuberculosis through Improvement Of Nutritional Status) trial showed the efficacy of nutritional supplementation in reducing TB incidence in households by up to 50%, and an editorial used the metaphor of food as a vaccine for tuberculosis. This essay provides a historical overview of nutrition and TB prevention, with reports of reduced TB incidence from nutritional supplementation in World War II prisoner-of-war camps. This essay discusses additional evidence supporting McKeown's proposition that the historical decline of TB in countries like the UK was related to improvements in nutrition. Undernutrition is the leading risk for tuberculosis incidence globally, the underlying cause of 45% of 4.9 million deaths in children under five years annually. Undernutrition in early life is a risk factor for many non-communicable diseases, and its effect on cognition and growth perpetuates both undernutrition and poverty intergenerationally. The essay broadens the vaccine metaphor to describe adequate balanced food (ABF) as a vaccine for TB and many public health problems, with a unique product profile. It concludes with a reminder that nutrition acts by optimizing immune function - the most powerful system/vaccine we have for TB prevention; draws attention to emerging threats to food security like climate change and conflicts, and proposes that the answer to the prevention of TB may lie in better population health rather than only a war on the bacillus.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".