EPIDEMIOLOGY OF MALARIA IN A HYPOENDEMIC BRAZILIAN AMAZON MIGRANT POPULATION: A COHORT STUDY
Bibliographic record
Abstract
The present study describes aspects of the epidemiology of malaria in a migrant population living in a hypoendemic area in Brazil using an open cohort study design. Rural settlement residents in Leonislândia, Peixoto de Azevedo, Mato Grosso, Brazil were followed from September 1996 to April 1997. At baseline, an interview and malaria diagnoses were carried out and spleen size was measured. Incident cases were detected through follow-up visits and laboratory records. Cox regression was used to assess risk factors for time to malaria onset. Eighty percent (n = 414) of the study population (n = 521) contributed follow-up data. Overall, malaria prevalence during any study visit ranged from 0.3% to 5.4% and the malaria incidence rate (IR) was 4.49 (95% confidence interval = 3.66, 5.46) per 100 person-months. The IR of Plasmodium vivax malaria was approximately four times higher than the IR for P. falciparum malaria during follow-up. Among individuals who had had malaria during his or her lifetime, 14.03% reported hospitalization (median duration = 3 days) and 70.1% reported days of work lost (median duration = 4 days for P. falciparum malaria and 3 days for P. vivax malaria) related to the last malaria episode. No important risk factor was associated with the malaria IR. The fact that neither work-related factors nor age was associated with the risk of malaria indicates that indoor/peri-domiciliary transmission by the local vector is more important or as important as workplace-related transmission.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".