Association among ecological and behavioural attributes, dengue vector and disease control: a cross-sectional study of the city of Dhaka, Bangladesh
Bibliographic record
Abstract
BACKGROUND: This study examines vector density, the prevailing knowledge, awareness, attitudes and practice (KAAP) of community members regarding dengue disease and their willingness to pay (WTP) for vector control in Dhaka, Bangladesh. METHODS: A population-based, cross-sectional study design was followed: (i) an entomological survey was carried out in 727 randomly selected households in 12 wards, representing four urban ecological zones and (ii) a survey of 330 household heads was conducted to study their KAAP. The χ2 test and multinomial logistic regression (MLR) were applied to investigate factors associated with WTP and other variables. RESULTS: The Stegomyia indices significantly vary among the urban zones, revealing that the paved and built areas with concentrated public/commercial services have the highest mosquito density. Most respondents (93.9%) knew about dengue and its severity (90.3%); however, many of them were unaware (79.3%) about the types of mosquitoes causing dengue. MLR modelling reveals that average spending per month for mosquito control, household income and knowledge about the effects of land use and seasonality on dengue were significantly associated with the WTP for controlling the dengue vector. CONCLUSIONS: Concerted efforts should be made to increase awareness about dengue transmission and develop community-based sustainable dengue vector control programmes involving both the public and private sectors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".