The 1918 influenza pandemic did not accelerate tuberculosis mortality decline in early‐20th century Newfoundland: Investigating historical and social explanations
Bibliographic record
Abstract
OBJECTIVES: The selective mortality hypothesis of tuberculosis after the 1918 influenza pandemic, laid out by Noymer and colleagues, suggests that acute exposure or pre-existing infection with tuberculosis (TB) increased the probability of pneumonia and influenza (P&I) mortality during the 1918 influenza pandemic, leading to a hastened decline of TB mortality in post-pandemic years. This study describes cultural determinants of the post-pandemic TB mortality patterns in Newfoundland and evaluates whether there is support for this observation. MATERIALS AND METHODS: Death records and historical documents from the Provincial Archives of Newfoundland and Labrador were used to calculate age-standardized island-wide and sex-based TB mortality, as well as region-level TB mortality, for 1900-1939. The Joinpoint Regression Program (version 4.8.0.1) was used to estimate statistically significant changes in mortality rates. RESULTS: Island-wide, females had consistently higher TB mortality for the duration of the study period and a significant shift to lower TB mortality beginning in 1928. There was no similar predicted significant decline for males. On the regional level, no models predicted a significant decline after the 1918 influenza pandemic, except for the West, where significant decline was predicted in the late-1930s. DISCUSSION: Although there was no significant decline in TB mortality observed immediately post-pandemic, as has been shown for other Western nations, the female post-pandemic pattern suggests a decline much later. The general lack of significant decrease in TB mortality rate is likely due to Newfoundland's poor nutrition and lack of centralized healthcare rather than a biological interaction between P&I and TB.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".