Emergency and essential surgical healthcare services during COVID-19 in low- and middle-income countries: A perspective
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
The COVID-19 pandemic resulted in significant changes in health care systems worldwide, with low- and middle-income countries (LMIC) sustaining important repercussions. Specifically, alongside cancellation and postponements of non-essential surgical services, emergency and essential surgical care delivery may become affected due to the shift of human and material resources towards fighting the pandemic. For surgeries that do get carried through, new difficulties arise in protecting surgical personnel from contracting SARS-CoV-2. This scarcity in LMIC surgical ecosystems may result in higher morbidity and mortality, in addition to the COVID-19 toll. This paper aims to explore the potential consequences of COVID-19 on the emergency and essential surgical care in LMICs, to offer recommendations to mitigate damages and to reflect on preparedness for future crises. Reducing the devastating consequences of the COVID-19 pandemic on LMIC emergency and essential surgical services can be achieved through empowering communities with accurate information and knowledge on prevention, optimizing surgical material resources, providing quality training of health care personnel to treat SARS-CoV-2, and ensuring adequate personal protection equipment for workers on the frontline. While LMIC health systems are under larger strain, the experience from previous outbreaks may aid in order to innovate and adapt to the current pandemic. Protecting LMIC surgical ecosystems will be a pivotal process in ensuring that previous health system strengthening efforts are preserved, comprehensive care for populations worldwide are ensured, and to allow for future developments beyond the pandemic.
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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 | 0.001 |
| 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 | 0.000 | 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