Population genomic evidence that human and animal infections in Africa come from the same populations of <i>Dracunculus medinensis</i>
Bibliographic record
Abstract
Abstract 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 30 human cases reported globally last year. 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 may be key in maintaining transmission in that country. Results 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 should stay aware of the possible emergence of unusual epidemiology as they approach elimination.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".