Participatory development of a target policy profile to support soil-transmitted helminth elimination
Bibliographic record
Abstract
Introduction: Soil-transmitted helminths (STH) are parasitic worms that infect nearly a quarter of the world's population, particularly those living in communities without access to adequate water, sanitation, and housing. Emerging evidence suggests that it may be possible to interrupt transmission of STH by deworming individuals of all ages via community-wide MDA (cMDA), as opposed to only treating children and other focal populations. Transitioning from a policy of STH control to STH elimination in targeted areas would require a fundamental shift in STH policy and programming. This policy change would require updated guidance to support countries as they adapt their current approaches for STH surveillance, supply chain management, community mobilization, and core programmatic activities in pursuit of STH elimination. There is an opportunity to engage with key stakeholders, such as program implementers and implementation partners, to understand what evidence they need to confidently adopt a new policy guideline and to deliver guideline adherent management at scale. Methods: We aimed to engage with STH stakeholders to develop a Target Policy Profile (TPoP), a single document that describes optimal characteristics and evidence requirements that STH stakeholders prioritized in future potential STH transmission interruption efforts. Steps in TPoP development included a scoping review and key informant interviews (KIIs), which were used to design a two-stage Delphi technique to identify and verify TPoP components. Results: The scoping review resulted in 25 articles, and 8 experts participated in KII's. Twenty respondents completed the first Delphi survey and 10 respondents completed the second. This systematic effort resulted in a net of 3 key information domains (background/context, clinical considerations, and implementation considerations) encompassing 24 evidence categories (examples include evidence regarding safety and adverse events, implementation feasibility, or evidence dissemination). For each evidence category, STH stakeholders reviewed, endorsed, or revised a range of options for how the evidence could be presented. Discussion: This information can be used by guideline committees or global policy makers prior to convening guideline advisory groups. The TPoP tool may also speed the process of stakeholder consensus building around guidelines, accelerating progress towards implementing evidence-based policy at scale.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".