Hospital Waste Management at the Provincial Hospital and the Notre Dame des Apôtres Hospital of Sarh, Chad
Bibliographic record
Abstract
In order to improve environmental and individual health and make aware that poor management of biomedical waste is a vector for the spread of many diseases, a study was conducted on the management of hospital waste in two main reference health structures, the Provincial Hospital (HP) and the Hospital of Our Lady of the Apostles (HNDA) of Sarh. The general objective of this study is to contribute to the reduction of environmental pollution through the management of biomedical waste. More specifically, it is to: 1) identify the sources of the waste, 2) sort and classify the waste by their categories, 3) assess the quality of the water in the yard of each health facility involved. The study was based on surveys, documentary research and physico-chemical and bacteriological analyses of the water in the two hospitals. The results of this work made it possible to identify that the DBM management system remains inadequate and that neither of these two reference health facilities in the province had a hospital waste management plan or produced waste management activity reports. 96% of the medical and paramedical staff interviewed confirmed that biomedical waste was sorted, 32% of the medical and paramedical staff confirmed that the waste treatment program was not followed before disposal, and 16% were not informed about hospital waste management. All the support staff for hygiene and sanitation services in the two health facilities are illiterate. In terms of vaccinations, 100% of health care staff and waste managers at the hospitals are not vaccinated against hepatitis or tetanus serum (TSS). The physicochemical and bacteriological analyses of the water showed the poor quality of these different waters, with the presence of germs indicating pollution.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".