A Rapid Review of Pandemic Studies in Paramedicine
Bibliographic record
Abstract
Introduction The spread of COVID-19 has challenged the paramedic community's ability to provide health care, maintain personal safety, and implement evidence informed decisions and programs. The study objective was to examine the published literature related to paramedicine and pandemics. Methods A rapid review of research derived from an existing broad database of literature generated between 2006 and 2019 was used. We conducted a targeted secondary search of this database to identify studies of pandemics in paramedicine contexts and included three levels of screening. We used content analysis to identify broad themes and subthemes, and provide summaries and descriptions of each. Results From 54,638 citations, our search identified 24 citations representing eight countries. The most common method of enquiry was cross-sectional survey (n=10). Five broad themes (and 15 subthemes) were identified: general planning and preparedness (impact to paramedic service operations, roles and responsibilities, communication centre preparedness, paramedic service preparedness, training); workforce (availability of personal protective equipment, safety of family, perception of risk, trust in the organisation); ethics (duty, resource allocation); (triage (needless exposure to infection, transmission of disease); and vaccination (vaccination information, organisational readiness). Conclusion The evidence base describes the importance of pandemic planning and preparedness for emergency medical services and integrating these activities into broader public health and healthcare system plans. Although this rapid review provides a foundation to support response plans and research, it is considered ‘just in time’ for the evolving pandemic, and further work understanding research in paramedicine and pandemics is recommended.
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.
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 | 0.029 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.052 | 0.046 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".