Integrating comprehensive surgical, intensive, and emergency care systems into the Pan American Health Organization’s health agenda
Bibliographic record
Abstract
by the PAHO Executive Committee. This strategy builds on the 2015 World Health Assembly (WHA) Resolution 68.15, which recognized surgery as essential to universal health coverage, and the 2023 WHA Resolution 76.2, which called for standardized emergency preparedness and response. With 365 million Latin Americans lacking access to essential surgical services, the need for a regional action plan is urgent. Ecuador, the first country in Latin America to develop a national surgical, obstetric, and anesthesia plan (NSOAP), highlighted the need for integrated surgical care to address health disparities in the region. While PAHO's formal integration is commendable, its success will rely on sustained political engagement, financial commitment, and robust monitoring. This article outlines the foundations for this strategy, the mechanisms required for successful implementation, and the role of PAHO and its Member States in strengthening surgical systems as a public health priority. By focusing on vulnerable groups and leveraging collaboration, this initiative can reduce health inequities across the Americas, reinforcing universal health coverage and access to safe, timely, and affordable surgical care.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".