Examining geographic variation in the prevalence of household drainage types across India in 2019-2021
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The proportion of Indian households with access to a toilet has grown considerably over the past decade. Many of these toilets rely on on-site containment, either in the form of a septic tank or soak pit. If the waste from these containers is not removed using some type of mechanized method, it can overflow into drains before flowing into treatment facilities or being discharged into water bodies. Therefore, drains are a critical part of the sanitation chain. What remains unknown, however, is what types of drains are available to households in India. Understanding this is critical given that people are at a greater risk of ingesting contaminated water and making dermal contact with pathogens if waste flows in open drains. For the first time, India’s National Family Health Survey from 2019–2021 contains data on the type of drainage available to households. Thus, the purpose of this paper is to estimate the prevalence of households relying on no drainage, open drainage, drains to soak pits, and closed drainage. We also estimate these prevalence values for each of India’s 720 districts and by urban/rural communities to understand the geographic clustering of drainage types throughout India. Overall, we found that the most common drainage type was open drains (37.5% | 95% CI: 37.3–37.6), followed by closed drains (33.9% | 95% CI: 33.7–34.0). The household prevalence of open drainage was above 42% in more than half of India’s 720 districts. Similarly, the household prevalence of closed drainage was below 24% in more than half of India’s 720 districts. We also found that open drains were more common in rural communities, while closed drains were more common in urban communities. We also found a socioeconomic gradient in terms of drainage types, with those lower on the socioeconomic spectrum more likely to have open drains or no drainage. Our results underscore the need to both geographically and socioeconomically target interventions that ensure households have access to adequate drainage. Doing so is vital to remove contamination from the environment as a means of preventing morbidity.
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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 it