Implementation challenges of an integrated One Health surveillance system in humanitarian settings: A qualitative study in Palestine
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
OBJECTIVES: Several factors have changed interactions between people, animals, plants, and the environment - renewing the relevance of the One Health surveillance system in the fight against zoonotic diseases such as COVID-19. Therefore, this study aimed to explore barriers to implementing an integrated One Health surveillance system in Palestine. METHODS: This qualitative study was conducted from April 2020 until August 2020. Data were collected using semi-structured interview guides. Seven key stakeholders were interviewed during data collection. A thematic analysis was performed. RESULTS: Four overarching themes emerged explaining barriers to integrated implementation of the One Health surveillance system. They are lack of policy coherence, limited financial resources, poor governance and leadership, and lack of One Health training programmes. CONCLUSION: Improved understanding of the transmission and effective control (including One Health approach) of zoonotic disease and better governance and leadership are critical in the diseases that threaten public health, such as the COVID-19.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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