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Record W2112817270 · doi:10.1093/cid/ciu467

Reaching the London Declaration on Neglected Tropical Diseases Goals for Onchocerciasis: An Economic Evaluation of Increasing the Frequency of Ivermectin Treatment in Africa

2014· article· en· W2112817270 on OpenAlex
Hugo C. Turner, Martin Walker, Thomas S. Churcher, Mike Y. Osei‐Atweneboana, Nana‐Kwadwo Biritwum, Adrian Hopkins, Roger K. Prichard, Marı́a-Gloria Basáñez

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Infectious Diseases · 2014
Typearticle
Languageen
FieldMedicine
TopicParasitic Diseases Research and Treatment
Canadian institutionsMcGill University
FundersMedical Research CouncilWellcome Trust
KeywordsOnchocerciasisIvermectinContext (archaeology)MedicineNeglected tropical diseasesEnvironmental healthDisease EradicationCost–benefit analysisCost effectivenessTransmission (telecommunications)Public healthDiseaseRisk analysis (engineering)BiologyVeterinary medicineImmunologyComputer scienceNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Recently, there has been a shift in onchocerciasis control policy, changing from prevention of morbidity toward elimination of infection. Switching from annual to biannual ivermectin distribution may accelerate progress toward the elimination goals. However, the settings where this strategy would be cost effective in Africa have not been described. METHODS: An onchocerciasis transmission framework (EpiOncho) was coupled to a disease model in order to explore the impact on disability-adjusted life years averted, program cost, and program duration of biannual ivermectin treatment in different epidemiological and programmatic scenarios in African savannah. RESULTS: While biannual treatment yields only small additional health gains, its benefit is pronounced in the context of the elimination goals, shortening the time frames for and increasing the feasibility of reaching the proposed operational thresholds for stopping treatment. In settings with high precontrol endemicity (and/or poor coverage and compliance), it may not be possible to reach such thresholds even within 50 years of annual ivermectin, requiring adoption of biannual treatment. Our projections highlight the crucial role played by coverage and compliance in achieving the elimination goals. CONCLUSIONS: Biannual ivermectin treatment improves the chances of reaching the 2020/2025 elimination goals, potentially generating programmatic cost savings in settings with high precontrol endemicity. However, its benefit and cost are highly sensitive to levels of systematic noncompliance and, in many settings, it will lead to an increase in costs. Furthermore, it may not always be feasible to implement biannual treatment, particularly in hard-to-reach populations. This highlights the continued need for a macrofilaricide.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.112
GPT teacher head0.429
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it