School enrolment in Zanzibar linked to children’s age and helminth infections
Bibliographic record
Abstract
UNLABELLED: School health programmes have been identified as a cost-effective strategy to reduce morbidity due to soil-transmitted helminths in the school-age population, but the low rate of school enrollment in developing countries is a major factor limiting their success. OBJECTIVE: The present study was conducted to identify reasons for non-enrollment and to evaluate differences in the occurrence of helminth infection between enrolled and non-enrolled children in Zanzibar, United Republic of Tanzania. METHOD: A questionnaire was submitted to 520 households to obtain information about enrollment and other socio-economic indicators. In addition, one school-age child was randomly selected in each household and investigated for soil-transmitted helminth infection. RESULTS: Overall, 71% of school-age children were enrolled. Enrollment increased with age. Only 41% of children under 9 years of age were enrolled compared to 91% in children older than 12 years. Enrollment is delayed because of an insufficient number of schools. Among non-enrolled school-age children, the proportion of heavy intensity infections was twice that of enrolled school-age children. CONCLUSIONS: Most of the non-enrolled school-age children live together with enrolled siblings in the same household, thereby representing an important opportunity for effective outreach activities. The effectiveness of the school-based helminth control programme in reducing the intensity of infection was confirmed. The significant gains achieved by enrolled school-age children in this study must be viewed as an attainable goal for the important numbers of non-enrolled school-age children in endemic areas. Decision-makers must ensure that outreach activities are included in helminth control programmes targeted to school-age children.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".