Evaluation of household coverage with long-lasting insecticidal nets in central Côte d’Ivoire
Bibliographic record
Abstract
BACKGROUND: To reduce malaria burden in Côte d'Ivoire, the Ministry of Health aims for 90% of its population to possess one long-lasting insecticidal net (LLIN) for every two persons by 2025. This study evaluated LLIN coverage two years after a mass distribution in central Côte d'Ivoire. METHODS: A census was conducted in 43 villages. Data were collected on household geo-position, composition, number of sleeping units and LLINs owned. LLIN coverage was assessed using: 1/ownership; proportion of household with at least one LLIN; 2/household access; households with sufficient nets for every two persons and for every sleeping unit; and 3/population access; proportion of population with access to LLIN within households and sleeping units. RESULTS: 10,630 households (89.6% response rate) and 46,619 inhabitants were recruited. Household LLIN ownership was 63.8% (95% CI: 58.7-68.8). Household LLIN access was 37.6% (95% CI: 33.2-42.0) based on 1 LLIN per 2 persons and 37.1% (95% CI: 33.0-41.2) based on 1 net per sleeping unit. Population LLIN access based on 1 LLIN per 2 persons and 1 net per sleeping space was 53.3% (95% CI: 48.6-58.1) and 49.4% (95% CI: 45.1-53.6), respectively. Approximately 17% of households with access for every 2 persons did not have access by every sleeping unit and 9.7% of households with access by sleeping unit did not have access for every 2 persons. Households with adequate access by sleeping unit but not for every 2 persons tend to be larger with fewer sleeping units, and have children under 5 years old and female members. The largest households (>7 members) and households with at least one under-five member had the lowest access (20.8 and 27.3%, respectively). CONCLUSION: LLIN access was low in this area of intense indoor malaria transmission, 2 years after the last mass distribution campaign. Strategies are needed to improve LLINs coverage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| 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 teacher head, 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".