Knowledge and Attitudes of Health Care Providers and the Population about Rabies in Sokone Health District, Senegal
Bibliographic record
Abstract
Rabies is still a deadly disease, but it is 100% preventable through vaccination. In 2016, Senegal notified 1214 cases of dog bites. In the same year, the district of Sokone recorded 50 cases of dog bites, of which 31.2% of the cases were notified in the region of Fatick. The objective of this study is to assess the level of knowledge, attitudes and practices of communities and healthcare providers when faced with a case of exposure to rabies in Sokone health district. This quantitative estimation study is of a descriptive cross-sectional type, which took place during the third quarter of 2017. It targeted the community and health care providers in the Sokone health district. Three-stage cluster sampling was carried out in the community. The recruitment of healthcare providers has been comprehensive. A questionnaire was administered to the community in the form of individual interviews and another questionnaire was sent to health care providers in the form of self-administration. Knowledge, attitude and practice rating grids were developed for the two categories of interviewees. Data entry and analysis was done with Epi Info 3.5.3 software and R 3.3.1. Out of 813 community members surveyed, 6.8% had already been bitten by an animal. A good level of knowledge about rabies was found in 22.4% of the community members. The attitude to a bite was correct for 94.1%. Of the 38 healthcare providers surveyed, only 5.6% had a good understanding of rabies. No provider knew the indications for rabies vaccination and the post-exposure vaccination schedule. In the Sokone health district, communities knew little about rabies. Healthcare providers who are supposed to inform and supervise them in the fight against rabies know less about it. Strengthening the skills of healthcare staff in dealing with bites exposing them to rabies is of urgency in the Sokone health district.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".