COVID-19 and emergency department attendances in Irish public hospitals
Bibliographic record
Abstract
On 29 February 2020 the first confirmed case of COVID-19 was announced in the Republic of Ireland.In subsequent weeks, progressively more restrictive control measures were introduced in an attempt to 'flatten the curve' and specifically to relieve pressure on emergency and critical care services.Using the most up to date data available on emergency department (ED) attendances in acute public hospitals, this analysis examines the impact on the numbers and types of attendances since the onset of COVID-19.Our analysis shows that there were on average 45.4 per cent fewer ED attendances per day in the week ending 29 March compared to the week ending 1 March.In addition, the reduction in ED attendances appears to be more prevalent in younger age groups.We also show that the proportion of ED attendances across triage categories, used to assess urgency of treatment, remained stable with no substantive changes in the overall proportion of very urgent/immediate attendances.Public information campaigns must encourage people to contact GPs and attend EDs if they require emergency care, and healthcare facilities must ensure that it is safe to do so. 1.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".