Enhancing the design, conduct and evaluation of public health emergency preparedness exercises: a rapid review
Bibliographic record
Abstract
BACKGROUND: Emergency preparedness exercises are essential in building a resilient public health system that can support increasingly frequent and complex public health risks. This rapid review describes evidence-informed practices or principles that can enhance all-hazards emergency preparedness exercises, with a specific focus on the public health agency context. METHODS: Four databases were systematically searched, including MEDLINE, Embase, Global Health, and CINAHL (January 2013-June 2024) and complemented with a grey literature search. Studies were included if published in English, from a member country of the Organisation for Economic Co-operation and Development, relevant to the public health agency context, and reported outcomes that aligned with our primary research question. Included articles were assessed for quality based on study design. The analysis involved a descriptive summary and thematic analysis. RESULTS: The review identified fifteen studies that reported insights on optimizing exercise design and delivery, with most studies reporting on tabletop exercise evaluation results. We identified ten sub-themes on how to strengthen exercises with a focus on how scenarios are developed, how participants are selected and organized during an exercise, thoughtful selection and training of exercise facilitators, selecting evaluation methods that closely align with the purpose of the exercise, and the importance of embedding activities that will encourage pathways to improvement. CONCLUSIONS: Findings from this review can be utilized in practice to enhance the design of emergency preparedness exercises. There are several gaps that should inform future work, including the need for additional studies focused on exercises conducted within the public health agency context, as well as more rigorous research to strengthen knowledge regarding evidence-informed practices in this area. There is a need for more guidance on triggers for conducting exercises, additional research on innovative technologies and approaches to enhance participant engagement, and guidance on incorporating evidence-based frameworks and indicators to improve exercise design and evaluation.
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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 | 0.040 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".