Population-level impact of mass drug administration against schistosomiasis with anthelmintic drugs targeting juvenile schistosomes: a modelling study
Bibliographic record
Abstract
BACKGROUND: Schistosomiasis is a neglected disease caused by parasitic flatworms of the genus Schistosoma and affects more than 150 million people worldwide. Praziquantel, the drug used in public health control programmes, has minimal activity against juvenile schistosomes (within 6 weeks of infection) and imperfect cure rates. We aimed to model the population-level impact of hypothetical novel drug candidates, targeting both juvenile and adult schistosomes with various efficacies, across a range of baseline epidemiological settings. METHODS: In this modelling study, we used a stochastic, individual-based mechanistic model of Schistosoma mansoni infection and simulated mass drug administration control programmes in diverse epidemiological environments. These programmes involved the administration, over a 5-year period at 75% coverage, of praziquantel (single-dose or two-dose regimens) or hypothetical novel drugs with various assumed efficacies against adult and juvenile schistosome parasites: novel drug A, with equivalent efficacy to praziquantel against adult schistosomes plus perfect (100%) efficacy against juvenile schistosomes; novel drug B, with higher efficacy than praziquantel against adult schistosomes and no activity against juveniles; and novel drug C, with higher efficacy than praziquantel against adult schistosomes plus perfect efficacy against juveniles. The outcomes were median observed S mansoni infection prevalence and infection intensity over time in simulated populations. FINDINGS: In a simulated high-endemicity setting (baseline prevalence of S mansoni infection of 53%), modelled prevalence after a single treatment was 20·8% (uncertainty interval 15·8-23·6) for single-dose praziquantel, 17·8% (15·2-19·8) for two-dose praziquantel, 18·4% (13·4-21·4) for novel drug A, 16·0% (15·0-16·8) for novel drug B, and 13·4% (12·6-14·0) for novel drug C; at year 5, modelled prevalence was 14·6% (12·2-16·4) for single-dose praziquantel, 13·6% (11·6-14·6) for two-dose praziquantel, 11·8% (9·4-13·4) for novel drug A, 12·6% (11·6-13·4) for novel drug B, and 9·6% (9·0-10·4) for novel drug C. In a simulated low-endemicity setting (baseline prevalence 15%), modelled prevalence after a single treatment was 4·8% (3·6-5·8) for single-dose praziquantel, 4·2% (3·6-5·0) for two-dose praziquantel, 4·6% (3·2-5·4) for novel drug A, 4·0% (3·4-4·6) for novel drug B, and 3·6% (3·2-4·2) for novel drug C; at year 5, modelled prevalence was 3·0% (2·2-3·6) for single-dose praziquantel, 2·8% (2·2-3·4) for two-dose praziquantel, 2·6% (1·8-3·2) for novel drug A, 2·7% (2·2-3·2) for novel drug B, and 2·2% (1·8-2·6) for novel drug C. INTERPRETATION: This study provides policy-relevant data that could help to guide the development and selection of novel drugs for schistosomiasis. Novel anthelmintic drugs that can kill both adult and juvenile schistosomes with higher efficacy than praziquantel could have some public health gains in control programmes for schistosomiasis, especially in high-burden settings. Novel drugs with increased efficacy against adult schistosomes are likely to have an initial and larger impact on disease control, whereas targeting juveniles could moderately improve longer-term control outcomes. FUNDING: US National Institutes of Health.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".