Rapid review of the impacts of climate change on the health system workforce and implications for action
Bibliographic record
Abstract
Introduction: The cascading impacts of climate change have significant implications for public health and healthcare delivery globally. This review explores how climate change impacts the health system workforce (both public health and healthcare service delivery), and what adaptation strategies are being deployed to mitigate against extreme climate events. Methods: The review draws from English language peer-reviewed articles published between 2003 and 2023, that forefront experiences and adaptations to climate change events as they relate to the health system workforce. Out of 1662 articles, upon completing title and abstract review, two reviewers completed full-text review of 130 articles, removing 92 for not meeting inclusion criteria, resulting in 38 articles. Articles were analyzed in relation to the World Health Organization Climate Resilient Health Systems Framework. Results: Emergent themes highlight occupational health impacts such as physical hazards, burn out and psychosocial impacts. Adaptive strategies to address these impacts include bolstering transformative leadership praxis, psychosocial support provision, emergency preparedness and planning, and scaling up climate-related emergency preparedness through the development of climate change core competencies and multi-sectoral collaboration strategies. Conclusions: Our review illustrates the limitations and opportunities of current adaptive strategies being utilized to support the healthcare workforce around the world, highlights the need for immediate emissions reductions that will reduce future hazards, and provides recommendations for how these findings can be applied to better prepare the health workforce for a range of climate futures.
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How this classification was reachedexpand
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".