Eliminating morbidity caused by neglected tropical diseases by 2030
Bibliographic record
Abstract
The objective of this manuscript is to provide selective examples of the work of the Pan American Health Organization/World Health Organization (PAHO/WHO) Collaborating Centre for Research and Training in Parasite Epidemiology and Control which contribute to the WHO goal of eliminating neglected tropical diseases by 2030. This PAHO/WHO CC specifically aligns its activities with the Sustainable Development Goals and with the goals outlined in the WHO Road Map for Neglected Tropical Diseases 2021-2030. Its role is to contribute to advancing global action on NTDs, primarily through policy development and knowledge translation. Three important projects have recently been completed: 1. Finalizing the Monitoring and Evaluation Framework for the NTD Road Map (published May 2021; this PAHO/WHO CC was a member of the working group); 2. Developing new guidelines for the preventive chemotherapy of Taenia solium taeniasis (published September 2021; this PAHO/WHO CC was co-Chair; and 3. Formulating a policy brief on deworming for adolescent girls and women of reproductive age (published January 2022; this PAHO/WHO CC is co-lead). These projects are the result of the integration of expertise and experience from multiple partners, including from PAHO and WHO (where both organizations provided key leadership), this PAHO/WHO CC, government ministries, civil society organizations and universities, among others. In conclusion, this PAHO/WHO CC contributes timely guidance to country-led evidence-informed public health policy, to cost-effective program implementation and to the identification of priority research topics – all focused, ultimately, on eliminating NTD-attributable morbidity by 2030.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.016 |
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".