National survey data for zoonotic schistosomiasis in the Philippines grossly underestimates the true burden of disease within endemic zones: implications for future control
Bibliographic record
Abstract
Zoonotic schistosomiasis has a long endemic history in the Philippines. Human mass drug administration has been the cornerstone of schistosomiasis control in the country for the past three decades. Recent publications utilizing retrospective national survey data have indicated that the national human prevalence of the disease is <1%, hence the disease is now close to elimination. However, the evidence for such a claim is weak, given that less than a third of the human population is currently being treated annually within endemic zones and only a third of those treated actually swallow the tablets. For those who consume the drug at the single oral dose of 40mg/kg, the estimated cure rate is 52% based on a recent meta-analysis. Thus, approximately 5% of the endemic human population is in reality receiving the appropriate treatment. To compound this public health problem, most of the bovines in the endemic communities are concurrently infected but are not treated under the current national control programme. Given this evidence, it is believed that the human prevalence of schistosomiasis within endemic regions has been grossly underestimated. Inherent flaws in the reporting of national schistosomiasis prevalence data are reported here, and the problems of utilizing national retrospective data in making geographic information system (GIS) risk maps and advising policy makers of the outcomes are highlighted.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".