International survey on the impact of parasitic infections: frequency of transmission and current mitigation strategies
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Globally, blood safety interventions have been successful in mitigating risk of the major transfusion-transmitted (TT) viruses. However, strategies that address risk from parasites are comparatively limited. TT parasites are often regional in nature, posing unique challenges; we sought to understand their impact on blood safety. MATERIALS AND METHODS: An electronic questionnaire was distributed to transfusion medicine leaders in 100 countries. The survey focused on specific questions pertaining to four parasitic diseases: babesiosis, Chagas, leishmaniasis and malaria. Respondents provided data on historical TT cases, local epidemiology, policies to mitigate risk and an assessment of public health perceptions for each aetiologic agent. RESULTS: Twenty-eight (28%) surveys were returned from countries in Europe (n = 13), the Americas (n = 6), Africa (n = 4), Asia (n = 3) and Oceana (n = 2). Historically, no cases of TT leishmaniasis were reported, TT babesiosis was exclusive to Canada and the USA, TT Chagas was limited to the Americas and Spain, while TT malaria was cosmopolitan. Mitigation efforts varied widely; malaria was the most frequently tested parasitic disease. The public's perception of risk for parasitic agents was low, while that of health authorities in endemic countries was higher. CONCLUSION: The global impact of parasitic infections on blood safety and related mitigation efforts varied widely by parasite epidemiology, test availability, public health priorities and socioeconomic constraints. While parasites continue to pose a risk to blood safety, the successful mitigation of viral risk has elevated the prominence of TT parasites in many locations, thereby requiring consideration of mitigation efforts.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".