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Record W3108379942 · doi:10.1371/journal.pntd.0008623

Population genomic evidence that human and animal infections in Africa come from the same populations of Dracunculus medinensis

2020· article· en· W3108379942 on OpenAlexaff
Caroline Durrant, Elizabeth A. Thiele, Nancy Holroyd, Stephen R. Doyle, Guillaume Sallé, Alan Tracey, Geetha Sankaranarayanan, Magda E. Lotkowska, Hayley M. Bennett, Thomas Huckvale, Zahra Abdellah, Ouakou Tchindebet, Mesfin Wossen, Makoy Samuel Yibi Logora, Cheick Oumar Coulibaly, Adam Weiss, Albrecht I. Schulte‐Hostedde, Jeremy M. Foster, Christopher A. Cleveland, Michael J. Yabsley, Ernesto Ruiz‐Tiben, Matthew Berriman, Mark L. Eberhard, James A. Cotton

Bibliographic record

VenuePLoS neglected tropical diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicParasitic Diseases Research and Treatment
Canadian institutionsLaurentian University
FundersBiotechnology and Biological Sciences Research CouncilCenters for Disease Control and PreventionWellcome TrustCarter CenterWellcome
KeywordsBiologyPopulationTransmission (telecommunications)Vector (molecular biology)ZoologyVeterinary medicineEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Guinea worm-Dracunculus medinensis-was historically one of the major parasites of humans and has been known since antiquity. Now, Guinea worm is on the brink of eradication, as efforts to interrupt transmission have reduced the annual burden of disease from millions of infections per year in the 1980s to only 54 human cases reported globally in 2019. Despite the enormous success of eradication efforts to date, one complication has arisen. Over the last few years, hundreds of dogs have been found infected with this previously apparently anthroponotic parasite, almost all in Chad. Moreover, the relative numbers of infections in humans and dogs suggests that dogs are currently the principal reservoir on infection and key to maintaining transmission in that country. PRINCIPAL FINDINGS: In an effort to shed light on this peculiar epidemiology of Guinea worm in Chad, we have sequenced and compared the genomes of worms from dog, human and other animal infections. Confirming previous work with other molecular markers, we show that all of these worms are D. medinensis, and that the same population of worms are causing both infections, can confirm the suspected transmission between host species and detect signs of a population bottleneck due to the eradication efforts. The diversity of worms in Chad appears to exclude the possibility that there were no, or very few, worms present in the country during a 10-year absence of reported cases. CONCLUSIONS: This work reinforces the importance of adequate surveillance of both human and dog populations in the Guinea worm eradication campaign and suggests that control programs aiming to interrupt disease transmission should stay aware of the possible emergence of unusual epidemiology as pathogens approach elimination.

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)0.001
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 score0.018
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.114
GPT teacher head0.336
Teacher spread0.222 · 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 designObservational
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

Citations37
Published2020
Admission routes1
Has abstractyes

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