Utilization of community health workers for malaria treatment: results from a three-year panel study in the districts of Kaya and Zorgho, Burkina Faso
Bibliographic record
Abstract
BACKGROUND: Malaria is holo-endemic in Burkina Faso and causes approximately 40,000 deaths every year. In 2010, health authorities scaled up community case management of malaria with artemisinin-based combination therapy. Previous trials and pilot project evaluations have shown that this strategy may be feasible, acceptable, and effective under controlled implementation conditions. However, little is known about its effectiveness or feasibility/acceptability under real-world conditions of implementation at national scale. METHODS: A panel study was conducted in two health districts of Burkina Faso, Kaya and Zorgho. Three rounds of surveys were conducted during the peak malaria-transmission season (in August 2011, 2012 and 2013) in a panel of 2,232 randomly selected households. All sickness episodes in children under five and associated health-seeking practices were documented. Community health worker (CHW) treatment coverage was evaluated and the determinants of consulting a CHW were analysed using multi-level logistic regression. RESULTS: In urban areas, less than 1% of sick children consulted a CHW, compared to 1%-9% in rural areas. Gaps remained between intentions and actual practices in treatment-seeking behaviour. In 2013, the most frequent reasons for not consulting the CHW were: the fact of not knowing him/her (78% in urban areas; 33% in rural areas); preferring the health centre (23% and 45%, respectively); and drug stock-outs (2% and 12%, respectively). The odds of visiting a CHW in rural areas significantly increased with the distance to the nearest health centre and if the household had been visited by a CHW during the previous three months. CONCLUSIONS: This study shows that CHWs are rarely used in Burkina Faso to treat malaria in children. Issues of implementation fidelity, a lack of adaptation to the local context and problems of acceptability/feasibility might have undermined the effectiveness of community case management of malaria. While some suggest extending this strategy in urban areas, total absence of CHW services uptake in these areas suggest that caution is required. Even in rural areas, treatment coverage by CHWs was considerably less than that reported by previous trials and pilot projects. This study confirms the necessity of evaluating public health interventions under real-world conditions of implementation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".