Hurricane Sandy (New Jersey): Mortality Rates in the Following Month and Quarter
Bibliographic record
Abstract
OBJECTIVES: To describe changes in mortality after Hurricane Sandy made landfall in New Jersey on October 29, 2012. METHODS: We used electronic death records to describe changes in all-cause and cause-specific mortality overall, in persons aged 76 years or older, and by 3 Sandy impact levels for the month and quarter following Hurricane Sandy compared with the same periods in earlier years adjusted for trends. RESULTS: All-cause mortality increased 6% (95% confidence interval [CI] = 2%, 11%) for the month, 5%, 8%, and 12% by increasing Sandy impact level; and 7% (95% CI = 5%, 10%) for the quarter, 5%, 8%, and 15% by increasing Sandy impact level. In elderly persons, all-cause mortality rates increased 10% (95% CI = 5%, 15%) and 13% (95% CI = 10%, 16%) in the month and quarter, respectively. Deaths that were cardiovascular disease-related increased by 6% in both periods, noninfectious respiratory disease-related by 24% in the quarter, infection-related by 20% in the quarter, and unintentional injury-related by 23% in the month. CONCLUSIONS: Mortality increased, heterogeneous by cause, for both periods after Hurricane Sandy, particularly in communities more severely affected and in the elderly, who may benefit from supportive services.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".