<i>Toxoplasma gondii</i> in Retail Beef, Lamb, and Pork in Canada: Prevalence, Quantification, and Risk Factors from a Public Health Perspective
Bibliographic record
Abstract
Toxoplasmosis is a zoonosis of public health concern worldwide. Toxoplasma gondii can be transmitted to humans through the consumption of raw or undercooked meat, but little is known about the risk associated with various meat commodities consumed by Canadians. We set out to estimate the prevalence and risk factors of T. gondii -positive status of retail meat in Canada using a combination of ELISA and quantitative polymerase chain reaction, and found a prevalence of 0.3% in pork ( n = 360), 0.6% ( n = 329) in beef, and between 4.3% and 11.1% in lamb ( n = 298), depending on province. Most of (75%) positive lamb samples (100 g each) contained more than 4000 parasites, relative to the standard curve. Lamb had a higher risk ( p < 0.001) of being T. gondii positive compared to beef and pork. Using multivariable logistic regression, T. gondii positivity in lamb samples was associated ( p < 0.001) with “country of origin” and “meat cut,” but no association was detected regarding store location, store category (independent, chain or butcher), or store volume. Ground lamb was identified as a risk factor compared to any other cuts. Overall, 26.4% of New Zealand imported lamb was positive to T. gondii compared to 4.0% of Canadian meat and 4.1% of Australian meat; only the difference between New Zealand and Australia was statistically significant in the multivariable model ( p < 0.001). However, considering the conditions under which it is transported, frozen New Zealand (and Australian) lamb should not present a risk to Canadian public health. These results provide critical information for performing T. gondii quantitative risk assessments in food and for orienting acquired and congenital toxoplasmosis prevention strategies by targeting potential transmission sources.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".