Long-Term Efficacy of Insecticidal Wall Painting for Controlling Visceral Leishmaniasis Vectors in Bangladesh
Bibliographic record
Abstract
The success of the visceral leishmaniasis (VL) elimination program largely depends on cost-effective vector control measures. Our goal was to investigate the longevity of the efficacy of insecticidal wall painting (IWP), a new vector control tool, compared with a routine indoor residual spraying (IRS) program for reducing the VL vector density in Bangladesh. This study is the extension of our recent IWP study for VL vector management in Bangladesh, which was undertaken in seven highly VL endemic villages of the Mymensingh district with a 12-month follow-up. In this 24-months follow-up study, we collected sand flies additionally at 15, 18, 21, and 24 months since the interventions from the IWP and control (where the program did routine IRS) clusters to examine the longevity of the efficacy of IWP on sand fly density reduction and mortality. The difference-in-differences regression models were used to estimate the effect of IWP on sand fly reduction against Program IRS. The IWP showed excellent performance in reducing sand fly density and increasing sand fly mortality compared with Program IRS. The effect of IWP for controlling sand flies was statistically significant for up to at least 24 months. The mean female Phlebotomus argentipes density reduction ranged from -56% to -83%, and the P. argentipes sand fly mortality ranged from 81% to 99.5% during the 24-month follow-up period. Considering the duration of the efficacy of IWP for controlling VL vectors, Bangladesh National Kala-azar Elimination Program may consider IWP as the best alternative to IRS for the subsequent phases of the program.
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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 | 0.001 |
| 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 | 0.000 |
| 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".