Safety and Efficacy of Incorporating Actellic® 300 CS into Soil Wall Plaster for Control of Malaria Vectors in Rural Northeastern Uganda
Bibliographic record
Abstract
Indoor residual spraying (IRS) and the use of insecticide-treated bednets for malaria vector control have contributed substantially to a reduction in malaria disease burden. However, these control tools have important shortcomings including being donor-dependent, expensive, and often failing because of insufficient uptake. We assessed the safety and efficacy of a user-friendly, locally tailored malaria vector control approach dubbed “Hut Decoration for Malaria Control” (HD4MC) based on the incorporation of a WHO-approved insecticide, Actellic® 300 CS, into a customary hut decoration practice in rural Uganda where millions of the most vulnerable and malaria-prone populations live in mud-walled huts. Three hundred sixty households were randomly assigned to either the HD4MC (120 households), IRS (120 households) or control group without any wall treatment (120 households). Entomological indices were assessed using pyrethrum spray catching, CDC light traps and human landing catches. The Actellic® 300 CS toxicity on acetylcholinesterase activity among applicators of HD4MC was evaluated using the Test-mate (Model 400) erythrocyte acetylcholinesterase (AChE) test V.2, whereas toxicity in household occupants was monitored clinically. The Actellic® 300 CS level in house dust was analyzed using reversed-phase high-performance liquid chromatography (RP-HPLC). Entomological indices were compared between the three study arms at 1.5, 3 and 6 months post-intervention. HD4MC- and IRS-treated huts had a significantly reduced malaria vector density and feeding rate compared to control huts. There was no significant reduction in acetylcholinesterase activity at 1.5 and 24 h post exposure. Actellic® 300 CS exposure did not result in any serious adverse events among the household occupants. In conclusion, HD4MC was safe and had comparable efficacy to canonical IRS.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".