Exposure to <i>Toxoplasma gondii</i> Through Consumption of Raw or Undercooked Meat: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Toxoplasma gondii is a globally distributed protozoan that mainly causes health issues in the fetuses of pregnant women who have never been exposed to this parasite and patients with deficient immune systems. Except in these vulnerable populations, the primary infection generally goes unnoticed in most healthy individuals. Apart from transplant/transfusion, congenital transmission, direct contact with infected cats or their feces, and environmental contamination (i.e., oocysts in food, water, and soil) pathways, humans can acquire the parasite through consumption of animal tissues infected by T. gondii. This meta-analysis estimated the risk of acquiring T. gondii by consuming raw or undercooked meat, regardless of which animal species are eaten. Using a random-effect model, crude and adjusted pooled measures of association (risk and odds ratio) were estimated according to study design (cohort, case–control, and cross-sectional studies). The meta-analysis included measures of heterogeneity as well as quality rating scales for each study design. Our results suggest that individuals who eat raw or undercooked meat have, respectively, 1.2–1.3 times the risk and 1.7–3.0 times the odds of T. gondii infection compared to those who thoroughly cook meat, regardless of the animal species they consume. These results align with the current understanding that adequately cooking meat inactivates the parasite and decreases the risk of transmission. Seroprevalence ranged from 1.3% to 88.6%, while the proportion of individuals eating raw or undercooked meat fluctuated from 0.7% to 98.3% across the studies in the meta-analysis. These numbers reflect various preferences with regard to eating meat (i.e., eating tartar, sausages, or salamis) as well as individual, cultural and religious food habits, and personal awareness.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".