Knowledge and Practices of Pig Farmers Regarding Japanese Encephalitis in Kathmandu, Nepal
Bibliographic record
Abstract
Japanese encephalitis (JE) is the single largest cause of viral encephalitis in the world and has been endemic in Nepal since the early 1980s. Since then, it has spread from its origins in lowland plains to the Kathmandu Valley as well as in hill and mountain districts. Pigs are amplifying hosts for the virus. The Nepal government has been encouraging the development of pig farming as a means of poverty alleviation. Whereas other countries have reduced JE through vaccination programmes and improvements in pig husbandry, these options are not economically possible in Nepal. The objective of this study was to examine the occupational risk of pig farmers in Nepal and to determine their level of knowledge and practice of JE prevention techniques. We surveyed 100 randomly selected pig farmers in the Kathmandu District and found that pig farmers were exposed to many JE risk factors including poverty and close proximity to pigs, rice paddy fields and water birds, which are the definitive hosts for the virus. Forty-two percent of the farmers had heard of JE, 20% associated it with mosquito bites and 7% named pigs as risk factors. Few protective measures were taken. None of the farmers were vaccinated against JE nor were any pigs, despite an ongoing human vaccination campaign. This farming community had little ownership of land and limited education. JE education programmes must consider gender differences in access to public health information as there were an equal number of male and female farmers. We provide findings that can inform future JE education programmes for this vulnerable population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".