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Record W1598392550 · doi:10.1159/000298760

Mass Treatment of Parasitic Disease: Implications for the Development and Spread of Anthelmintic Resistance

2010· book-chapter· en· W1598392550 on OpenAlexaff
Thomas S. Churcher, Ray M. Kaplan, Bernadette F. Ardelli, Jan M. Schwenkenbecher, Marı́a-Gloria Basáñez, Patrick J. Lammie

Bibliographic record

VenueIssues in infectious diseases · 2010
Typebook-chapter
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsBrandon University
Fundersnot available
KeywordsLymphatic filariasisMass drug administrationAnthelminticDrug resistancePublic healthEnvironmental healthHelminthsResistance (ecology)HelminthiasisFilariasisImmunologyPopulationBiologyMedicineVeterinary medicineEcologyMicrobiologyPathology

Abstract

fetched live from OpenAlex

There has been a dramatic increase in the use of mass drug administration to reduce the morbidity associated with helminth infections of humans, raising the likelihood that anthelmintic resistance may become a public health concern of the future. After highlighting the scope and magnitude of the chemotherapy-based helminth control programs presently in place, this chapter emphasizes the mechanisms of action of the main anthelmintic drugs in use and how resistance may develop. To date, the most established population-based mass drug administration campaigns have been against the filarial parasites which cause human on chocerciasis and lymphatic filariasis. The molecular and parasitological evidence suggesting the presence of drug resistance in human filarial parasites is reviewed and factors influencing the spread of drug resistant parasites are discussed, taking examples from veterinary helminths and the use of mathematical models. In particular, the public health impact of the development of resistance by soil-transmitted helminths, such as hookworm, is a real concern. Implications of the development of anthelmintic resistance are discussed in relation to existing control programs, emphasizing how their monitoring and evaluation is essential to prevent it becoming a major public health concern of the future.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.728
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.037
GPT teacher head0.338
Teacher spread0.301 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2010
Admission routes1
Has abstractyes

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