Knowledge, attitude and practice (KAP) survey of canine rabies in Khyber Pakhtunkhwa and Punjab Province of Pakistan
Bibliographic record
Abstract
Background This study aimed to assess the extent of knowledge and understanding of rabies disease in rural and urban communities of Pakistan. It also identified malpractices after suspected dog bite that might pose a risk for humans contracting rabies. Methods A cross-sectional study was conducted (n = 1466) on people having different age groups and educational levels in four different geographic regions of Punjab and Khyber Pakhtunkhwa provinces in Pakistan. Knowledge, attitude, and practices of people were assessed using a structured questionnaire. We used a bivariate and multivariate analysis to study the association between rabies related mortalities in near or extended family members and different risk behaviors. Results Our results demonstrate that the majority of the juvenile population (less than 18 years of age) were not aware of the clinical signs of rabies in animals. 75% of the total respondents were not vaccinated against rabies, 60% did not seek a doctor’s advice after a suspected animal bite, and 55% had inadequate health care facilities for rabies patients in local hospitals. Respondents that had pets at home had not vaccinated (38%; p < 0.05; odds ratio 1.58) themselves against rabies due to lack of knowledge and awareness of pre-exposure prophylaxis for rabies (51%; p < 0.05; odds ratio 1.25). They also tend to not visit doctor after suspected bite (52%; p < 0.05; odds ratio 1.97), which may had resulted in more deaths (65%; p < 0.05; odds ratio 1.73) of someone in their near or extended family due to rabies. Conclusions Lack of knowledge about the nature of rabies disease and prophylaxis has contributed to increase of rabies related deaths. Inadequate health care facilities and poor attitude of not seeking medical attention after suspected dog bite are the major reasons of rabies related deaths. These findings could help in devising a targeted management strategy and awareness program to control and reduce the incidence of human rabies related deaths in Pakistan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".