Health Impacts of Citywide and Localized Power Outages in New York City
Bibliographic record
Abstract
Background: Previous studies investigated potential health effects of large-scale power outages, including the massive power failure that affected the northeastern United States and Ontario, Canada, in August 2003, and outages associated with major storms. However, information on localized outages is limited. Objective: The study sought to examine potential health impacts of citywide and localized outages in New York City (NYC). Methods: Along with the citywide 2003 outage, localized outages in July 1999 and July 2006 were identified. We additionally investigated localized, warm- and cold-weather outages that occurred in any of 66 NYC electric-grid networks during 2002–2014 using New York State Public Service Commission data. Mortality and hospitalizations were geocoded and linked to the networks. Associations were estimated using Poisson time-series regression, including examining distributed lags and adjusting for temperature and temporal trends. Network-specific estimates were pooled by season. Results: Respiratory disease hospitalizations were associated with the 2006 localized outage [cumulative relative risk [CRR] over 0–1 lag day, lag01=2.26 (95% confidence interval [CI]: 1.08, 4.74)] and the 2003 citywide outage, but not with other localized, warm-weather outages. Renal disease hospitalizations were associated with the 2003 citywide outage, and with localized, warm-weather outages, pooled across networks [RR at lag3=1.16 (95% CI: 1.00, 1.34)], but not the 2006 localized outage. All-cause mortality was positively associated with the 1999, 2003, and 2006 outages (significant for the 2003 outage only), but not with other localized, warm-weather outages. Localized, cold-weather outages were associated with all-cause mortality [lag01 CRR=1.06 (95% CI: 1.01, 1.12)] and cardiovascular disease hospitalizations [lag01 CRR=1.14 (95% CI: 1.03, 1.26)], and fewer respiratory disease hospitalizations [lag03 CRR=0.77 (95% CI: 0.61, 0.97)]. Conclusions: Localized outages may affect health. This information can inform preparedness efforts and underscores the public health importance of ensuring electric grid resiliency to climate change. https://doi.org/10.1289/EHP2154
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".