Guidelines for Mountain Rescue During the COVID-19 Pandemic: Official Guidelines of the International Commission for Alpine Rescue
Bibliographic record
Abstract
Roy, Steven, Inigo Soteras, Alison Sheets, Richard Price, Kazue Oshiro, Simon Rauch, Don McPhalen, Maria Antonia Nerin, Giacomo Strapazzon, Myron Allen, Alistair Read, and Peter Paal. Guidelines for mountain rescue during the COVID-19 pandemic: official guidelines of the International Commission for Alpine Rescue. High Alt Med Biol . 22: 128–141, 2021. Background: In mountain rescue, uncertainty exists on the best practice to prevent coronavirus disease 2019 (COVID-19) transmission. The aim of this work was to provide a state-of-the-art overview of the challenges caused by the COVID-19 pandemic in mountain rescue. Methods: Original articles or reviews, published until December 27, 2020 in Cochrane COVID-19 Study Register, EMBASE, PubMed, and Google Scholar were included. Articles were limited to English, French, German, or Spanish with the article topic COVID-19 or other epidemics, addressing transmission, transport, rescue, or cardiopulmonary resuscitation. Results: The literature search yielded 6,190 articles. A total of 952 were duplicates and 5,238 were unique results. After exclusion of duplicates and studies that were not relevant to this work, 249 articles were considered for this work. Finally, 72 articles and other sources were included. Conclusions: Recommendations are provided for protection of the rescuer (including screening, personal protective equipment [PPE], and vaccination), protection of the patient (including general masking if low risk, specific PPE if high risk), equipment hygiene (including disinfection after every mission), use of single-use products, training and medical measures under COVID-19 precautions, and psychological wellbeing of rescuers during the COVID-19 pandemic. Adapted COVID-19 precautions for low-and-medium-income countries are also discussed.
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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 | 0.039 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".