A Research Agenda for Helminth Diseases of Humans: The Problem of Helminthiases
Bibliographic record
Abstract
A disproportionate burden of helminthiases in human populations occurs in marginalised, low-income, and resource-constrained regions of the world, with over 1 billion people in developing areas of sub-Saharan Africa, Asia, and the Americas infected with one or more helminth species. The morbidity caused by such infections imposes a substantial burden of disease, contributing to a vicious circle of infection, poverty, decreased productivity, and inadequate socioeconomic development. Furthermore, helminth infection accentuates the morbidity of malaria and HIV/AIDS, and impairs vaccine efficacy. Polyparasitism is the norm in these populations, and infections tend to be persistent. Hence, there is a great need to reduce morbidity caused by helminth infections. However, major deficiencies exist in diagnostics and interventions, including vector control, drugs, and vaccines. Overcoming these deficiencies is hampered by major gaps in knowledge of helminth biology and transmission dynamics, platforms from which to help develop such tools. The Disease Reference Group on Helminths Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to review helminthiases research and identify research priorities and gaps. In this review, we provide an overview of the forces driving the persistence of helminthiases as a public health problem despite the many control initiatives that have been put in place; identify the main obstacles that impede progress towards their control and elimination; and discuss recent advances, opportunities, and challenges for the understanding of the biology, epidemiology, and control of these infections. The helminth infections that will be discussed include: onchocerciasis, lymphatic filariasis, soil-transmitted helminthiases, schistosomiasis, food-borne trematodiases, and taeniasis/cysticercosis.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.017 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".