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Record W4413932186 · doi:10.3390/insects16090911

A Systematic Review of Aircraft Disinsection Efficacy

2025· review· en· W4413932186 on OpenAlexafffund
Gregory D. Hawley, Michael Klowak, Syed Zain Ahmad, Candice Madakadze, Jahmar Hewitt, Aquilla Reid-John, Asal Adawi, Andrea K. Boggild

Bibliographic record

VenueInsects · 2025
Typereview
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersUniversity Health NetworkUniversity of TorontoWorld Health Organization
KeywordsBiologyComputational biology

Abstract

fetched live from OpenAlex

Disinsection of aircraft and other conveyances is recommended to prevent the international spread of disease-carrying mosquitoes. A systematic review synthesized the effectiveness of adult mosquito disinsection aboard international air, marine, and land conveyances, using literature available up to 31 May 2025. Nineteen experimental trials, nine of which included an unexposed control arm, were synthesized. The studies were generally of poor quality with high risk of bias, and adherence to WHO guidelines was 33.30% (range: 18.20-60.5%). Across comparator trials of aircraft disinsection, the odds of mosquito mortality in the treated groups compared to control groups was 163.60 (95% CI 147-182), and the relative risk of mosquito death was 14.24 (95% CI 12.99-15.63). The direction of effect was consistent across mosquito species, methods of disinsection, types of aircraft, and insecticides, though the magnitude of the effect varied widely. The only WHO-recommended insecticide tested in a controlled trial was 2% d-phenothrin, which demonstrated an odds ratio of 171.70 (95% CI 139.10-212) and a relative risk of 20.08 (95% CI 16.53-24.43) for mosquito mortality. The lack of adherence to WHO guidelines raises uncertainty about the real-world effectiveness of disinsection.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.018
GPT teacher head0.345
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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