Human Babesiosis Caused by Babesia duncani Has Widespread Distribution across Canada
Bibliographic record
Abstract
Human babesiosis caused by Babesia duncani is an emerging infectious disease in Canada. This malaria-like illness is brought about by a protozoan parasite infecting red blood cells. Currently, controversy surrounds which tick species are vectors of B. duncani. Since the availability of a serological or molecular test in Canada for B. duncani has been limited, we conducted a seven-year surveillance study (2011–2017) to ascertain the occurrence and geographic distribution of B. duncani infection country-wide. Surveillance case data for human B. duncani infections were collected by contacting physicians and naturopathic physicians in the United States and Canada who specialize in tick-borne diseases. During the seven-year period, 1119 cases were identified. The presence of B. duncani infections was widespread across Canada, with the highest occurrence in the Pacific coast region. Patients with human babesiosis may be asymptomatic, but as this parasitemia progresses, symptoms range from mild to fatal. Donors of blood, plasma, living tissues, and organs may unknowingly be infected with this piroplasm and are contributing to the spread of this zoonosis. Our data show that greater awareness of human babesiosis is needed in Canada, and the imminent threat to the security of the Canadian blood supply warrants further investigation. Based on our epidemiological findings, human babesiosis should be a nationally notifiable disease in Canada. Whenever a patient has a tick bite, health practitioners must watch for B. duncani infections, and include human babesiosis in their differential diagnosis.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".