Fish sharing as a risk factor for Opisthorchis viverrini infection: evidence from two villages in north-eastern Thailand
Bibliographic record
Abstract
BACKGROUND: Foodborne trematodiasis (FBT) is a significant global health problem, with the liver flukes Opisthorchis viverrini, O. felineus, and Clonorchis sinensis contributing to half of the global burden of FBT. North-eastern Thailand where O. viverrini is endemic and un-cooked fish dishes remain an integral part of the food culture has the highest reported incidence of opisthorchiasis, including associated cholangiocarcinoma. Both food sharing and eating practices are potentially important factors in FTB, suggesting an important role for the social ecology of disease transmission in these rural communities. METHODS: Two rural Thai-Lao villages that were part of a 12-village project in Northeastern Thailand were selected for detailed investigation of O. viverrini infection risk associated with sharing of raw fish dishes among households. The project included screening individuals for infection and cholangiocarcinoma, a household questionnaire, and offering treatment options for positive individuals. Social network mapping was used to construct raw fish dish-sharing networks and create a proxy variable capturing variability in the degree of food sharing (DFS), measured as the number of different households with which each household shared fish dishes. Measures of associations between DFS, O. viverrini infection, the frequency of raw fish consumption, and the number of raw fish dishes consumed were generated using binary logistic regression, proportional odds ordinal logistic regression, and Poisson regression. RESULTS: The results showed that the probability that a household has members infected with O. viverrini increased by ~7% (P < 0.01) for each additional household included in its network. Moreover, the frequency and number of types of raw fish dishes consumed increased significantly as the DFS increased. Of the two villages, that with the highest infection prevalence (48% versus 34.6%) had significantly higher social connectivity overall (P < 0.001). CONCLUSIONS: Our findings suggest that the social ecology of human settlements may be key to understanding the transmission dynamics of some FBT. In the case of O. viverrini in Thai-Lao communities, for which food sharing is a traditional practice supporting social cohesion, food sharing network mapping should be incorporated into community-based interventions. These should encourage fish dish preparation methods that minimize infection risk by targeting households with high DFS values.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".