Trend of COVID-19 spreads and status of household handwashing practice and its determinants in Bangladesh – situation analysis using national representative data
Bibliographic record
Abstract
The objective of the study was to assess the prevalence and factors associated with household (HH) handwashing practice in Bangladesh and draw a trend of COVID-19 spreads and compare that with the countrywide HH handwashing practice. The study is based on the two national representative publicly available datasets (MICS 2019, and confirmed cases of COVID-19). Of 61,209 (weighted) HH, the overall prevalence of HH handwashing was found 56.3%, and the prevalence was significantly varied across the socio-economic status of the HH. Map comparison suggested that the gradual increasing trend of COVID-19 cases in areas where HH handwashing practice is low. The northern part of Bangladesh had the highest handwashing practice, whereas it had less effected by COVID-19 cases. However, central Bangladesh had the hardest hit by COVID-19 cases, and it had around 50% handwashing practice coverage. Large-scale observational study is necessary to establish the causality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".