Community-based dengue control intervention in Ouagadougou: intervention theory and implementation fidelity
Bibliographic record
Abstract
While malaria control is the primary health focus in Burkina Faso, the recent dengue epidemic calls for new interventions. This paper examines the implementation fidelity of an innovative intervention to control dengue in the capital Ouagadougou. First we describe the content of the intervention and its theory. We then assess the fidelity of the implementation. This step is essential as preparation for subsequent evaluation of the intervention’s effectiveness. Observations ( n = 62), analysis of documents related to the intervention ( n = 8), and semi-structured interviews with stakeholders ( n = 18) were conducted. The collected data were organized and analyzed using QDA Miner. The theory of the intervention, grounded in reported good practices of community-based interventions, was developed and discussed with key stakeholders. The theory of the intervention included four components: mobilization and organization, operational planning, community action, and monitoring/evaluation. The interactions among these components were intended to improve people’s knowledge about dengue and enhance the community’s capacity for vector control, which in turn would reduce the burden of the disease. The majority of the planned activities were conducted according to the intervention’s original theory. Adaptations pertained to implementation and monitoring of activities. Despite certain difficulties, some of which were foreseeable and others not, this experience showed the feasibility of developing community-based interventions for vector-borne diseases in Africa.
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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 | 0.034 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| 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".