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Record W2736942160 · doi:10.1177/1010539517712758

Household Exposure to Livestock and Health in the CHILILAB HDSS Cohort, Vietnam

2017· article· en· W2736942160 on OpenAlexafffund
Sinh Dang-Xuan, Lauren E. MacDonald, Janna M. Schurer, Hung Nguyen‐Viet, Phuc Pham-Duc

Bibliographic record

VenueAsia Pacific Journal of Public Health · 2017
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of Saskatchewan
FundersConsortium of International Agricultural Research CentersGlobal Affairs CanadaGovernment of Canada
KeywordsEnvironmental healthLivestockBiosecurityMedicineCohortSanitationVeterinary medicineSocioeconomicsGeography

Abstract

fetched live from OpenAlex

In Vietnam, pigs and poultry are predominantly produced by small-scale farmers, creating challenges for zoonotic disease management. The objective of this study was to characterize practices related to livestock and manure management and to measure association with 3 self-reported health symptoms (coughing, fever, and diarrhea/nausea/vomiting) in a region currently undergoing health transitions. We analyzed cross-sectional survey data collected from a subset (N = 5520) of the Chi Linh Health and Demographic Surveillance System cohort in Chi Linh district, Vietnam. Bivariate analyses indicated that female gender was a significant risk factor for all 3 health symptoms, whereas age (≥60 years), suburban living, low education level, and household wealth were risk factors for 2 symptoms. Overall, we found no indication that biogas production or exposure to livestock and manure adversely affected human health. Efforts to control zoonotic disease transmission should prioritize utilization of veterinarians, enhanced farm biosecurity, and improvements to commune drinking water/wastewater infrastructure.

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)0.013
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.671
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.080
GPT teacher head0.348
Teacher spread0.267 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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