Will a lack of fabric durability be their downfall? Impact of textile durability on the efficacy of three types of dual-active-ingredient long-lasting insecticidal nets: a secondary analysis on malaria prevalence and incidence from a cluster-randomized trial in north-west Tanzania
Bibliographic record
Abstract
Abstract Background The Dual-Active Ingredient long-lasting insecticidal nets (Dual-AI LLIN) have been developed to counteract the reduced efficacy of pyrethroid (PY)-only nets due to widespread pyrethroid insecticide resistance in malaria vector mosquitoes. They constitute half of the nets distributed in sub-Saharan Africa between 2022 and 2024. However, their effectiveness once they develop holes is unclear, particularly in pyrethroid-resistant settings. This study evaluates the textile integrity of three dual- AI LLINs compared to standard PY LLN, over 3 years of use in a community in Tanzania and the associated impact on malaria prevalence and incidence. Methods A secondary analysis of data from a randomized controlled trial (RCT) in North-western Tanzania was conducted to evaluate the effectiveness of α-cypermethrin only; pyriproxyfen and α-cypermethrin (PPF-PY); chlorfenapyr and α-cypermethrin (chlorfenapyr-PY); and the synergist piperonyl butoxide and permethrin (PBO-PY) LLINs on malaria infection prevalence and case incidence. The association between the net textile condition and 1/malaria prevalence over 3 years of use between 2019 and 2022, and 2/malaria case incidence in a cohort of children over 2 years of follow-up was assessed between 2019 and 2021. Results There was no significant association between damaged (OR 0.98, 95% CI 0.71–1.37, p-value = 0.655) and too-torn (OR 1.07, 95% CI 0.77–1.47, p-value = 0.694) compared to intact nets on malaria prevalence for all net types. However, there were reduced rates of malaria case incidence in children sleeping under a net in good condition compared to too-torn nets (incidence rate ratio (IRR) 0.76 [95% CI 0.63–0.92], p = 0.005). Malaria incidence was also consistently lower in too-torn PBO-PY LLIN (IRR = 0.37 [95% CI 0.19–0.72], p = 0.003) and chlorfenapyr-PY LLIN (IRR = 0.45 [95% CI 0.33–0.97], p = 0.053) compared to an intact PY-only LLIN during the first year of follow up. In year 2, the incidence was only significantly lower in intact chlorfenapyr-PY LLIN (IRR = 0.49 [95% CI 0.29–0.81], p = 0.006) compared to intact PY LLIN. Conclusion The study confirmed that sleeping under a chlorfenapyr-PY LLIN or PBO-PY LLIN offered superior protection to pyrethroid-only nets even when torn. Preventing the development of holes is essential as they impact the level of protection offered against malaria infection. Trial registration: ClinicalTrials.gov, number (NCT03554616)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".