Evaluation of solid biomedical waste management practices in six health facilities in southern Benin
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
Introduction: Health care generates biomedical waste that present risks to humans and the environment if poorly managed. The objective of this study was to assess the management practices of solid biomedical waste in southern Benin. Methods: This was a descriptive cross-sectional study conducted in six health facilities. The study included 12 administrative agents selected by reasoned choice and 431 health care agents selected by convenience. The data were collected by questionnaire, interview, and observation. They concerned variables related to the production, the practice of managing, knowledge of the impact of solid biomedical waste on the environment and health, training and protection of personnel. Data analysis was done with R 4.5.0 software. Quantitative variables were described by median and interquartile range. Proportions were compared with the chi-square test or that of Fisher at the threshold of 0.05. Results: The health facilities did not have solid biomedical waste management database. Sorting was not systematic in 59.5 %. Final storage locations did not meet standards. Almost one in four health workers (24.4 %) were injured by biomedical waste. Overall, 45.8 % of the staff had been trained at least once on biomedical waste management. 61 % of the staff surveyed were vaccinated, hepatitis B (41.3 %), tetanus (32.9 %). Conclusion: In view of the results, it is necessary to ensure the on ongoing awareness and training of medical staff in the sorting and packaging of biomedical waste and to set up an efficient and sustainable solid biomedical waste management system with effective monitoring mechanisms.
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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 | 0.014 | 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 | 0.000 | 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