Seroprevalence of Japanese Encephalitis Virus and Risk Factors Associated with Seropositivity in Pigs in Four Mountain Districts in Nepal*
Bibliographic record
Abstract
Japanese encephalitis was recently reported from individuals in the mountain districts of Nepal without travel history to Japanese encephalitis virus (JEV) endemic areas. We performed a cross-sectional study to estimate the seroprevalence of JEV in pigs and subsequently conducted a survey of farmers to identify risk factors associated with seropositivity. In July and August, 2010, 454 pig serum samples were collected and tested by competitive ELISA. Data from a 35-question survey of 109 pig owners were analysed using multivariate logistic regression. Seventy-six (16.7, 95% CI 13.6-20.4) pigs tested positive for anti-JEV antibodies, none of which had been vaccinated against JEV or sourced from JEV endemic areas. Risk factors associated with JEV seropositivity were 'summer abortion', 'wells as a water source', 'urban location', 'reported presence of mosquitoes' and 'lower elevation'. Our results suggest that JEV is likely circulating in the mountain districts of Nepal, and that locally acquired JEV should be considered a risk for residents and travellers in these areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".