Role of container type, behavioural, and ecological factors in Aedes pupal production in Dhaka, Bangladesh: An application of zero-inflated negative binomial model
Bibliographic record
Abstract
The container-inhabiting Aedes mosquitoes are the major vectors transmitting dengue and several other arboviral diseases such as chikungunya and zika across the tropical world. Surveillance for immature Aedes, particularly pupae, is an effective tool for measuring dengue outbreak risk. While in Bangladesh, the greatest burden of dengue fever and dengue hemorrhagic fever cases has periodically been occurring since the first major outbreak in 2000, very limited research has yet been pursued to understand the dynamics of Aedes pupal production in this country. In this backdrop, this study was carried out to i) identify containers at household premises contributing to dengue vector productivity; ii) measure the extent of pupae productivity of household containers; and, iii) determine the effects of household ecological factors upon productivity of pupae in the city of Dhaka, Bangladesh. During the monsoon months of 2013, a total of 1,033 containers (674 wet and 363 dry) in 727 household premises in 12 wards of the city of Dhaka were inspected to measure container productivity and collect household ecological, and human behavioural data. The results reveal that the majority of immature mosquitoes (73.52% larvae and 84.91% pupae) developed in containers located outdoor that are used mostly for household chores. Plastic containers (57.55% of all immature mosquito-positive containers) used for household chores produce most of the immature mosquitos. The results of the zero-inflated negative binomial (ZINB) model reveal that pupae production significantly varies by container type (p-value = 0.0136) for the count regression group. However, when considering container size along with container type, container size is found significant for pupae production (p-value = 0.0041), showing that container size is confounded with the container type and the pupae production. Containers greater than 50 litres (L) are likely to produce 4.9 times more pupae than containers with <1L. Two household ecological factors are found to be significant (shade: p-value = 0.005 in the count regression group and type of water: p-value = 0.001 in the excess zero group) for pupae production. We found that containers with partial shade produce 4.6 times more pupae than without any shade, whereas in the excess zero group the expected number of observed zero pupae count is 86.5% lower in containers filled with rain water than those with tap water, tube-well water, ring well water and water from other sources. The most commonly used plastic-made containers (i.e., refrigerator trays, drums, buckets) and flower tubs/trays are the most abundant immature mosquito-positive containers. These findings would help the concerned authorities to formulate programs for changing human behaviour targeting the most productive containers for Aedes habitat management and vector control in the city of Dhaka, Bangladesh.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".