Impact of Face Washing and Environmental Improvement on Reduction of Active Trachoma in Vietnam—A Public Health Intervention Study
Bibliographic record
Abstract
PURPOSE: A public health intervention study in Vietnam was conducted between 2002 and 2005 to assess the impact of improved water and sanitation facilities and increased awareness about active trachoma in the community. METHODS: In My Thon village (MT), all four components of the SAFE strategy were implemented. In Xom Ngoai village (XN), only the S & A components of the trachoma control strategy were implemented. The villagers improved water and sanitation facilities in MT. Women's Union and school authorities assisted in increasing awareness in the community. Ophthalmologists examined the residents for trachoma. The decline in active trachoma and other water-related diseases was determined by pre- and post-intervention assessments. The impact of the differential F & E strategy on two villages was evaluated. RESULTS: The active trachoma prevalence in MT (SAFE) and XN (SA) at baseline was 13.3% and 10.2%, respectively. In two years, the masons constructed or improved 281 double-vault and three septic tank latrines, 241 bathrooms, 273 dug wells and 252 water tanks in MT. The prevalence in MT (SAFE) & XN (SA) after two years was 1.4% and 6.7%, respectively. The additional decline of active trachoma due to the differential F & E strategy among children under the age of 15 was 6.8%. The F & E strategy was responsible for 58.7% of the decline at all ages and 37.4% in children under the age of 15. Knowledge of the prevention of trachoma had improved in two years. However, the attitude towards and practice of trachoma control were not different in the two villages. CONCLUSIONS: 'F' & 'E' implementation made a significant contribution to the reduction of active trachoma. Community participation and collaborative efforts of partners are crucial. The indicators used to monitor F & E strategies are interrelated and therefore should be evaluated together.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".