A Spatial Analysis of Individual- and Neighborhood-Level Determinants of Malaria Incidence in Adults, Ontario, Canada
Bibliographic record
Abstract
Malaria, once endemic in Canada, is now restricted to imported cases.Imported malaria in Canada has not been examined recently in the context of increased international mobility, which may infl uence incidence of imported and autochthonous cases.Surveillance of imported cases can highlight high-risk populations and help target prevention and control measures.To identify geographic and individual determinants of malaria incidence in Ontario, Canada, we conducted a descriptive spatial analysis.We then compared characteristics of case-patients and controls.Case-patients were signifi cantly more likely to be male and live in low-income neighborhoods that had a higher proportion of residents who had emigrated from malariaendemic regions.This method's usefulness in clarifying the local patterns of imported malaria in Ontario shows its potential to help identify areas and populations at highest risk for imported and emerging infectious disease.M alaria is a parasitic, vector-borne disease that causes ≈1 million deaths each year and substantial global public health costs (1,2).The disease was previously endemic in North America, with transmission in most of the United States and parts of southern Canada (3).The malaria parasite, Plasmodium spp., was introduced into North America during the 16th-17th centuries through the arrival of European colonists and African slaves (3).Malaria was eliminated in North America by the 1950s through several different interventions, including vector control by A Spatial Analysis of Individualand Neighborhood-Level Determinants of Malaria Incidence in Adults, Ontario, Canada
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".