Knowledge, Treatment-Seeking, and Socioeconomic Impact of Malaria on the Essequibo Coast of Guyana
Bibliographic record
Abstract
The study was conducted to provide insight into malaria control efforts in Guyana, and to identify areas to emphasize in future educational campaigns. To do this, a community-based survey of knowledge, treatment-seeking patterns, and socio-economic impact of malaria was conducted at four outdoor markets in Region 2 Guyana. One hundred and eight individuals between the ages of 16 and 65 who had a malaria infection in the previous twelve months were interviewed. Within the study population, 94% identified mosquitoes as being the source of malaria infection. More than 70% of respondents identified fever, headache and chills as symptoms of malaria. Sixty percent of individuals incorrectly believed that women could not be treated with antimalarials when pregnant or they risked spontaneous abortion or congenital defects. Most individuals (76%) used bed nets although very few nets were chemically treated. Mean delay in presentation to a health clinic was 6.3 days. Use of the official health care sector was high (96%) and relatively few individuals (15%) self-treated with antimalarials. Compliance with antimalarial regimens was also found to be relatively good (92%). Cost of treatment was significantly higher among those who used private clinics (US$ 13.74) than those who used public clinics (US$ 0.96) (p < 0.001). The good level of knowledge of malaria may be due to the relatively high literacy rate and level of education in Guyana. The fact that public clinics in Guyana provide treatment and antimalarials at no cost may explain the relatively high use of the official health sector, low levels of self-treatment, and good compliance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".