In the footsteps of Albert Calmette: an ecological study of TB, leprosy and potential exposure to wild-type <i>Mycobacterium bovis</i>
Bibliographic record
Abstract
BACKGROUND: One hundred years ago, Albert Calmette developed an avirulent strain of Mycobacterium bovis, but there is no evidence that his BCG strain was more immunogenic than wild-type M. bovis. Geographic variations in BCG efficacy remain ill-understood. We hypothesized that exposure to M. bovis through unpasteurized milk might protect against Mycobacterium tuberculosis and Mycobacterium leprae. METHODS: After excluding high-income countries (with universal milk pasteurization) and microstates, an ecological study comprising 113 countries was conducted. National data were obtained from United Nations agencies and international organizations about milk production per capita (1980-1999) as a proxy for exposure to wild-type M. bovis, TB (2000-2019) and leprosy (2005-2019) incidence, HIV prevalence (2000-2019), human development index (2010), global hunger index (2010), neonatal BCG coverage (1980-1999), urbanization (2000) and temperature (1990-2020). Multiple linear regression analyses were performed using log-transformed variables. RESULTS: For TB, the association differed by region. An inverse association with milk production was seen in regions outside, but not within, sub-Saharan Africa, after adjustment for confounders. The incidence of leprosy was inversely associated with milk production when combining all countries, but the association was stronger in sub-Saharan Africa. CONCLUSIONS: Exposure to wild-type M. bovis through unpasteurized milk may provide cross-protection against M. tuberculosis and M. leprae and contribute to geographic disparities in BCG efficacy. This needs to be confirmed by individual-level studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".