Assessing the 1918/19 Pandemic Influenza and Respiratory Tuberculosis Interaction in Malta: Operationalizing a Syndemic During a Crisis Event
Bibliographic record
Abstract
Studies have indicated that there was a disease interaction of pandemic influenza with respiratory tuberculosis (TB) in Malta, which could explain the heightened mortality recorded in young adults. We revisit the 1918/19 influenza and TB syndemic potential on the island of Malta. Borrowing from crisis studies that explore the harvesting effect, we used the method of assessing changes in pre-pandemic, pandemic, fallow, and post-pandemic mortality/life expectancy to reveal the syndemic experience. Pre-pandemic (1914–1917) life expectancy at birth was significantly higher, at 37.91 years, than during the pandemic (1918), when life expectancy dropped to 33.26 years (Z = 10.56, p < 0.0001). Post-pandemic (1919) life expectancy rose to 43.49 years, which was an even longer life expectancy than pre-pandemic (Z = 17.61, p < 0.0001). There were significant changes in TB mortality death rates during the four periods in those of reproductive age. Augmenting our framework for studies of syndemics involving short-term events, we proposed the identification of contributing, driving, and limiting factors. Underlying living conditions contributed to the syndemic. The exacerbation of housing conditions, the economy associated with the First World War, and meteorological measures—temperature, relative humidity, and rainfall—were driving factors. The early implementation of mitigation strategies, such as restrictions on mass gatherings, were limiting factors of the syndemic.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".