“Where we put little fish in the water there are no mosquitoes:” a cross-sectional study on biological control of the Aedes aegypti vector in 90 coastal-region communities of Guerrero, Mexico
Bibliographic record
Abstract
BACKGROUND: In the Mexican state of Guerrero, some households place fish in water storage containers to prevent the development of mosquito larvae. Studies have shown that larvivorous fish reduce larva count in household water containers, but there is a lack of evidence about whether the use of fish is associated with a reduction in dengue virus infection. We used data from the follow up survey of the Camino Verde cluster randomised controlled trial of community mobilisation to reduce dengue risk to study this association. METHODS: The survey in 2012, among 90 clusters in the three coastal regions of Guerrero State, included a questionnaire to 10,864 households about socio-demographic factors and self-reported cases of dengue illness in the previous year. Paired saliva samples provided serological evidence of recent dengue infection among 4856 children aged 3-9 years. An entomological survey in the same households looked for larvae and pupae of Aedes aegypti and recorded presence of fish and temephos in water containers. We examined associations with the two outcomes of recent dengue infection and reported dengue illness in bivariate analysis and then multivariate analysis using generalized linear mixed modelling. RESULTS: Some 17% (1730/10,111) of households had fish in their water containers. The presence of fish was associated with lower levels of recent dengue virus infection in children aged 3-9 years (OR 0.64; 95% CI 0.45-0.91), as was living in a rural area (OR 0.57; 95% CI 0.45-0.71), and being aged 3-5 years (OR 0.65; 95% CI 0.51-0.83). Factors associated with lower likelihood of self-reported dengue illness were: the presence of fish (OR 0.79; 95% CI 0.64-0.97), and living in a rural area (OR 0.74; 95% CI 0.65-0.84). Factors associated with higher likelihood of self-reported dengue illness were: higher education level of the household head (OR 1.28; 95% CI 1.07-1.52), living in a household with five people or less (OR 1.33; 95% CI 1.16-1.52) and household use of insecticide anti-mosquito products (OR 1.68; 95% CI 1.47-1.92). CONCLUSIONS: Our study suggests that fish in water containers may reduce the risk of dengue virus infection and dengue illness. This could be a useful part of interventions to control the Aedes aegypti vector.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".