Lives saved and hospitalizations averted by COVID-19 vaccination in New York City
Bibliographic record
Abstract
Abstract Despite the emergence of highly transmissible variants, the number of cases in NYC has fallen from over 5,500 average daily cases in January, 2020 to less than 350 average daily cases in July, 2021. The impact of vaccination in saving lives and averting hospitalizations in NYC has not been formally investigated yet. We used an age-stratified agent-based model calibrated to COVID-19 transmission and vaccination in NYC to evaluate the impact of the vaccination campaign in suppressing the COVID-19 burden. We found that the vaccination campaign has prevented over 250,000 COVID-19 cases, 44,000 hospitalizations and 8,300 deaths from COVID-19 infection since the start of vaccination through July 1, 2021. Notably, the swift vaccine rollout suppressed another wave of COVID-19 that would have led to sustained increase in cases, hospitalizations and deaths during spring triggered by highly transmissible variants. As the Delta variant sweeps across the city, the findings of this study underscore the urgent need to accelerate vaccination and close the vaccine coverage gaps across the city.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".