Implementation Fidelity of the National Malaria Control Program in Burkina Faso
Bibliographic record
Abstract
BACKGROUND: Every year 40,000 people die of malaria in Burkina Faso. In 2010, the Burkinabè authorities implemented a national malaria control program that provides for the distribution of mosquito nets and the home-based treatment of children with fever by community health workers. The objective of this study was to measure the implementation fidelity of this program. METHODS: We conducted a case study in two comparable districts (Kaya and Zorgho). Data were collected one year after the program's implementation through field observations (10 weeks), documentary analysis, and individual interviews with stakeholders (n = 48) working at different levels of the program. The analysis framework looked at the fidelity of (i) the intervention's content, (ii) its coverage, and (iii) its schedule. RESULTS: The program's implementation was relatively faithful to what was originally planned and was comparable in the two districts. It encountered certain obstacles in terms of the provision of supplies. Coverage fidelity was better in Kaya than in Zorgho, where many community health workers (CHW) experienced problems with the restocking of artemisinin-based combination therapy and with remuneration for periods of training. In both districts, the community was rarely involved in the process of selecting CHWs. The components affected by scheduling all experienced successive implementation delays that pushed nets distribution and the initial provision of artemisinin-based combination therapies to the CHWs past the 2010 malaria season. CONCLUSIONS: The activities intended by the program were mostly implemented with good fidelity. However, the implementation was plagued by delays that probably postponed the expected beneficial effects.
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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 | 0.028 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".