Coverage of seasonal malaria chemoprevention in children aged 3 to 59 months in Burkina Faso: a nationwide cross-sectional study
Bibliographic record
Abstract
The objective of this study was to investigate seasonal malaria chemoprevention (SMC) coverage during the 2018 campaign and to identify factors associated with full coverage (receiving three doses of SMC four times during a campaign) of children aged 3 to 59 months. This was a cross-sectional study conducted in nine regions of Burkina Faso. In each region, we purposely selected districts based on the epidemiological profile and randomly selected villages within each district. The World Health Organization (WHO) Expanded Programme on Immunization (EPI) method was used in the household selection process. A generalized linear mixed model (GLMM) was used to account for the hierarchical structure of the design and to identify factors associated with full SMC coverage. Our results showed that community distributors (CDs) visited more than 98% of the selected households, and 95.9% of the children received three doses of SMC in the last round in October 2018. Furthermore, 84.8% of children were fully covered after having received all three doses of SMC during four campaigns by the end of 2018. The age of the children and the occupation of the respondent were factors significantly associated with complete SMC coverage. Full coverage of SMC among children aged 3 to 59 months remained below the expected coverage by the Burkina Faso Ministry of Health. It will be up to the Ministry of Health to strengthen the system for monitoring SMC activities.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".