Cost-effectiveness of larviciding for urban malaria control in Tanzania
Bibliographic record
Abstract
BACKGROUND: Larviciding for malaria control can contribute to an Integrated Vector Management (IVM) approach. This intervention is currently supported in settings where breeding habitats are 'few, fixed, and findable', such as urban areas of sub-Saharan Africa, but the knowledge base regarding the cost-effectiveness of larviciding is non-existent. METHODS: Programme costs and effectiveness data were collected from the Dar es Salaam Urban Malaria Control Programme in Tanzania. Cost-effectiveness ratios (CER) were estimated from the provider and societal perspectives for standard indicators using different malaria transmission scenarios. RESULTS: CER for microbial larviciding were highly dependent on the assumed baseline malaria incidence rates. Using the societal perspective, net CER were estimated (in 2012 US dollars) at $43 (95% uncertainty intervals [UI]: $15-181) per disability-adjusted life year averted (DALY) when malaria incidence was 902 infections per 1,000 individuals, increasing to $545 (95% UI: $337-1,558) per DALY at an incidence of 122 per 1,000. Larviciding was shown to be cost-effective in Tanzania for incidences as low as 40 infections per 1,000 people per year. CONCLUSION: This is believed to be the first study to estimate the cost-effectiveness of larviciding for urban malaria control in sub-Saharan Africa. The results support the use of larviciding as a cost-effective intervention in urban areas and managers of national malaria control programme should consider this intervention as part of an IVM approach.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".