MétaCan
Menu
Back to cohort

Knowledge and Practices of Pig Farmers Regarding Japanese Encephalitis in Kathmandu, Nepal

2012· article· en· W1935271708 on OpenAlexafffund
Santosh Dhakal, Craig Stephen, Analía Ale, D. D. Joshi

Bibliographic record

VenueZoonoses and Public Health · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of CalgaryVancouver Coastal Health
FundersInternational Development Research CentreWorld Bank Group
KeywordsJapanese encephalitisSocioeconomicsGeographyEncephalitisVeterinary medicineEnvironmental healthMedicineVirologyVirusSociology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.114
GPT teacher head0.348
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueZoonoses and Public HealthSame topicAnimal Disease Management and EpidemiologyFrench-language works237,207