Accès au traitement préventif intermittent (TPI) dans une situation de gratuité : rôle du bien-être économique
Bibliographic record
Abstract
In Senegal, the free distribution of sulfadoxine pyrimethamine during antenatal care is recommended to remove the disparity in the context of intermittent preventive treatment against malaria. The objective of this study was thus to identify factors influencing access to treatment in a situation of abolition of user fees. It was a cross-sectional and analytical study. It covered a sample of 1906 women aged 15-49 years randomly selected during the national survey on malaria in Senegal. Data were collected during a personal interview. The economic well-being was measured from the characteristics of housing and durable goods. The multivariate analysis was performed using logistic regression. The average age was 27.94 ± 5.34, 64.27% resided in rural area and 71.8% had received no schooling. Among the surveyed women, 23% were in the poorest quintile, while 16.3% were in the richest. Intermittent preventive treatment was performed in 49.3%. IPt were made more in urban areas (OR 1.45 95% [1.17 to 1.72]). It increased with the level of education with an OR of 1.5 and 1.68 in primary and secondary. The completion of the IPt increased with economic welfare. The OR ranged from 1.44 to 2.95 in the second quintile to the richest. Free medication does not necessarily benefit poor people. Other accompanying measures must be developed to facilitate the distribution of drugs particularly at community level with the involvement of people.
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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 | 0.005 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".