Summary of recommendations for the prevention of malaria by the Committee to Advise on Tropical Medicine and Travel (CATMAT)
Bibliographic record
Abstract
BACKGROUND: for Canadian health care providers who are preparing patients for travel to malaria-endemic areas and treating travellers who have returned ill. OBJECTIVE: To provide guidelines on risk assessment and prevention of malaria. METHODS: CATMAT reviewed all major sources of information on malaria prevention, as well as recent research and national and international epidemiological data, to tailor guidelines to the Canadian context. The evidence-based medicine recommendations were developed with associated rating scales for the strength and quality of the evidence. RECOMMENDATIONS: Used together and correctly, personal protective measures (PPM) and chemoprophylaxis very effectively protect against malaria infection. PPM include protecting accommodation areas from mosquitoes, wearing appropriate clothing, using bed nets pre-treated with insecticide and applying topical insect repellant (containing 20%-30% DEET or 20% icaridin) to exposed skin. Selecting the most appropriate chemoprophylaxis involves assessment of the traveller's itinerary to establish his/her malaria risk profile as well as potential drug resistance issues. Antimalarials available on prescription in Canada include chloroquine (or hydroxychloroquine), atovaquone-proguanil, doxycycline, mefloquine and primaquine.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.007 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.036 | 0.013 |
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".