Impact of seasonal malaria chemoprevention in children aged 3 to 59 months in the Kangaba and Kolokani health districts between 2013 and 2015.
Bibliographic record
Abstract
INTRODUCTION: Malaria is a public health problem in Mali. Seasonal chemo prevention (SCP) is of particular importance, hence its introduction by the WHO since 2012 in children aged 3 to 59 months from the start of the transmission season. This study aims to demonstrate the impact of SCP on malaria in the health districts of Kangaba and Kolokani. MATERIALS AND METHODS: Our retrospective study was carried out from 2013 to 2015 in the health districts of Kangaba and Kolokani using the databases of the NGO AMCP / ALIMA. Data from 2014 and 2015 were compared to data from 2013. RESULTS: The number of malaria cases in children under 5year in the area covered by the SCP shows a considerable decrease in Kangaba of 52% in 2014 and 49% in 2015, compared to the reference period being the year 2013. In Kolokani the decrease is 57% in 2014 and 40% in 2015 compared to the year 2013. Compared to deaths, a decrease of 50.5% was recorded in 2014 and 60.4% in 2015 compared to the year 2013, i.e. 51 and 61 fewer deaths compared to 2013, respectively, in health facilities. CONCLUSION: The SCP had made it possible to reduce significant mortality and malaria morbidity in the two health districts of Kangaba and Kolokani.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".