Integrated opisthorchiasis control through the EcoHealth/one health approach: 15 years of success and experiences with the Lawa model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Opisthorchis viverrini infection remains a major health problem in Northeast Thailand and the Mekong region impacting over 12 million and causing bile duct cancer. Using an EcoHealth/One Health approach at Lawa Lake in Thailand, our integrated control program achieved a substantial reduction in liver fluke prevalence from 60 % to <5 % over 15 years. Key interventions included chemotherapy, collaboratively designed health education, ecosystem modification, and community participation. Infections in intermediate hosts, Bithynia snails and Cyprinoid fish, are now undetectable. Improved community knowledge resulted in healthier practices. The “Lawa Model”, a recognized model for liver fluke control, is now a training hub being scaled up in Thailand and the Mekong region. This program demonstrates how One Health strategies can address complex health and ecological challenges and aligns with WHO recommendations. The success of the Lawa Model demonstrates the efficacy of integrated One Health interventions against endemic parasitic diseases.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it