Community response to artemisinin-based combination therapy for childhood malaria: a case study from Dar es Salaam, Tanzania
Bibliographic record
Abstract
BACKGROUND: New malaria treatment guidelines in Tanzania have led to the large-scale deployment of artemether-lumefantrine (Coartem), popularly known as ALu or dawa mseto. Very little is known about how people in malaria endemic areas interpret policy makers' decision to replace existing anti-malarials, such as sulphadoxine-pyrimethamine (SP) with "new" treatment regimens, such as ALu or other formulations of ACT. This study was conducted to examine community level understandings and interpretations of ALu's efficacy and side-effects. The paper specifically examines the perceived efficacy of ALu as articulated by the mothers of young children diagnosed with malaria and prescribed ALu. METHODS: Participant observation, six focus group discussions in two large villages, followed by interviews with a random sample of 110 mothers of children less than five years of age, who were diagnosed with malaria and prescribed ALu. Additionally, observations were conducted in two village dispensaries involving interactions between mothers/caretakers and health care providers. RESULTS: While more than two-thirds of the mothers had an overall negative disposition toward SP, 97.5% of them spoke favourably about ALu, emphasizing it's ability to help their children to rapidly recover from malaria, without undesirable side-effects. 62.5% of the mothers reported that they were spending less money dealing with malaria than previously when their child was treated with SP. 88% of the mothers had waited for 48 hours or more after the onset of fever before taking their child to the dispensary. Mothers' knowledge and reporting of ALu's dosage was, in many cases, inconsistent with the recommended dosage schedule for children. CONCLUSION: Deployment of ALu has significantly changed community level perceptions of anti-malarial treatment. However, mothers continue to delay seeking care before accessing ALu, limiting the impact of highly subsidized rollout of the drug. Implementation of ACT-based treatment guidelines must be complemented with educational campaigns to insure that mothers seek prompt help for their children within 24 hours of the onset of fever. Improved communication between health care providers and mothers of sick children can facilitate better adherence to ALu's recommended dosage. Community level interpretations of anti-malarials are multifaceted; integrating knowledge of local beliefs and practices surrounding consumption of anti-malarials into programmatic goals can help to significantly improve malaria control interventions.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 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".