Quantitative microbial risk assessment (QMRA) of the work of manual pit emptiers, commonly known as <i>bayakous</i>
Bibliographic record
Abstract
ABSTRACT In Haiti, manual pit emptiers, known as bayakous, face significant health risks. They work by descending naked into latrine pits, exposing themselves to pathogens and contributing to environmental contamination. This study employs the quantitative microbial risk assessment (QMRA) method to evaluate the microbial risks associated with this practice, considering nine prevalent pathogens in Haiti. Three ingestion scenarios were developed: hand-to-mouth contact, ingestion while immersed in excreta, and a combination of both. A sensitivity analysis assessed the impact of input data on study outcomes. The results indicate a high probability of infection and illness during pit emptying operations annually for all scenarios and pathogens. Recommendations include adopting personal protective equipment (PPE) and using a manual Gulper waste pump to eliminate the need to descend directly into the pits, thereby reducing the risk of injury from sharp objects. The study proposes the establishment of intermediate disposal points approximately 5 km from collection sites to deter illegal dumping. National regulations and professionalization of the bayakou profession are suggested, along with awareness campaigns to promote PPE and Gulper pump usage. Addressing these issues is crucial for safeguarding the health of bayakou and public health in Haiti.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".