Association between biological sex and insecticide-treated net use among household members in ethnic minority and internally displaced populations in eastern Myanmar
Bibliographic record
Abstract
Malaria prevalence in Myanmar is highest among remote and ethnic minority populations living near forest fringes along the country's international borders. Insecticide-treated nets (ITNs) are a key intervention used to prevent malaria transmission, but insufficient ITN availability and low use can hinder effectiveness. This study assessed age and sex disparities in ITN possession, access, and use among household members of ethnic minority and internally displaced populations in eastern Myanmar. Cross-sectional data from the 2013 Eastern Burma Retrospective Mortality Survey were used to describe prevalence of ITN possession, access, and use. The association between a household member's biological sex and their ITN use was assessed using multilevel log binomial regression. Age and household ITN supply were tested as potential effect modifiers. Of 37927 household members, 89.8% (95% CI: 89.5, 90.1) of people lived in households with at least one ITN. Approximately half belonged to households with sufficient ITN supply and used an ITN. Pregnant women and children under five had the highest proportion of ITN use regardless of sufficient household ITN status. Female adults aged 15 to 49 years old (Risk ratio or RR: 1.4, 95% CI: 1.29, 1.52) were more likely to use ITNs. This relationship did not differ by sufficient household ITN status. The findings suggest that among ethnic minority populations in areas where ITN use is indicated, many households do not have adequate ITN supply, and many individuals are not using ITNs. Children under five and pregnant women appear to be prioritized for ITN use and overall, women are slightly more likely to use ITNs than men. This study's findings can support efforts ensuring that all household members belonging to ethnic minority and displaced populations in Eastern Myanmar benefit from sufficient ITN access and use for malaria prevention.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".