Trends in emergency department visits related to acute alcohol consumption before and during the COVID-19 pandemic in the United States, 2018–2020
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Excessive drinking accounts for more than 95,000 deaths annually in the United States. Coronavirus disease 2019 (COVID-19) pandemic-related factors (e.g., social, economic, policy) may have affected alcohol consumption. Emergency department (ED) visits involving acute alcohol consumption (referred to as "alcohol-related") are a useful indicator for assessing changes in alcohol-related harms. Methods: The 2018-2020 National Syndromic Surveillance Program data, which include nonfatal ED visits from facilities in 49 states and Washington, DC, were analyzed. Trends in the number of alcohol-related ED visits among people ≥15 years, and weekly alcohol-related ED visit rates (per 10,000 total visits) overall, by demographic characteristics, and quarter (Q) were assessed. Quarterly rates for 2018 and 2019 were averaged to increase baseline data stability. Results: Alcohol-related visits accounted for 1.6% of 60,474,770 total visits (2018), 1.7% of 61,564,380 total visits (2019), and 1.8% of 52,174,507 total visits (2020). The number of alcohol-related ED visits generally increased during the first eight months of 2018 and 2019. However, it sharply declined at the onset of the COVID-19 pandemic in mid-March-mid-April 2020, before resuming pre-pandemic patterns. Alcohol-related ED visits per 10,000 were higher during quarters in 2020 than corresponding quarters in 2018-2019 (Q1: +7.3%, Q2: +23.8%, Q3: +9.7%, Q4: +6.5%). Conclusions: Alcohol-related ED visit rates per 10,000 total visits increased during 2020 versus 2018-2019, with the greatest relative difference in the second quarter. Fewer people sought ED care in 2020 than 2018-2019 but alcohol-related visits declined to a lesser extent than total visits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it