Multinational Impact of the 1968 Hong Kong Influenza Pandemic: Evidence for a Smoldering Pandemic
Bibliographic record
Abstract
BACKGROUND: The first pandemic season of A/H3N2 influenza virus (1968/1969) resulted in significant mortality in the United States, but it was the second pandemic season of A/H3N2 influenza virus (1969/1970) that caused the majority of deaths in England. We further explored the global pattern of mortality caused by the pandemic during this period. METHODS: We estimated the influenza-related excess mortality in 6 countries (United States, Canada, England and Wales, France, Japan, and Australia) using national vital statistics by age for 1967-1978. Geographical and temporal pandemic patterns in mortality were compared with the genetic drift of the influenza viruses by analyzing hemagglutinin and neuraminidase sequences from GenBank. RESULTS: In North America, the majority of influenza-related deaths in 1968/1969 and 1969/1970 occurred during the first pandemic season (United States, 70%; Canada, 54%). Conversely, in Europe and Asia, the pattern was reversed: 70% of deaths occurred during the second pandemic season. The second pandemic season coincided with a drift in the neuraminidase antigen. CONCLUSION: We found a consistent pattern of mortality being delayed until the second pandemic season of A/H3N2 circulation in Europe and Asia. We hypothesize that this phenomenon may be explained by higher preexisting neuraminidase immunity (from the A/H2N2 era) in Europe and Asia than in North America, combined with a subsequent drift in the neuraminidase antigen during 1969/1970.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".