Mass Treatment of Parasitic Disease: Implications for the Development and Spread of Anthelmintic Resistance
Bibliographic record
Abstract
There has been a dramatic increase in the use of mass drug administration to reduce the morbidity associated with helminth infections of humans, raising the likelihood that anthelmintic resistance may become a public health concern of the future. After highlighting the scope and magnitude of the chemotherapy-based helminth control programs presently in place, this chapter emphasizes the mechanisms of action of the main anthelmintic drugs in use and how resistance may develop. To date, the most established population-based mass drug administration campaigns have been against the filarial parasites which cause human on chocerciasis and lymphatic filariasis. The molecular and parasitological evidence suggesting the presence of drug resistance in human filarial parasites is reviewed and factors influencing the spread of drug resistant parasites are discussed, taking examples from veterinary helminths and the use of mathematical models. In particular, the public health impact of the development of resistance by soil-transmitted helminths, such as hookworm, is a real concern. Implications of the development of anthelmintic resistance are discussed in relation to existing control programs, emphasizing how their monitoring and evaluation is essential to prevent it becoming a major public health concern of the future.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".