Evidence-based chlorination targets for household water safety in humanitarian settings: Recommendations from a multi-site study in refugee camps in South Sudan, Jordan, and Rwanda
Bibliographic record
Abstract
The current Sphere guideline for water chlorination in humanitarian emergencies fails to reliably ensure household water safety in refugee camps. We investigated post-distribution chlorine decay and household water safety in refugee camps in South Sudan, Jordan, and Rwanda between 2013-2015 with the goal of demonstrating an approach for generating site-specific and evidence-based chlorination targets that better ensure household water safety than the status quo Sphere guideline. In each of four field studies we conducted, we observed how water quality changed between distribution and point of consumption. We implemented a nonlinear optimization approach for the novel technical challenge of modelling post-distribution chlorine decay in order to generate estimates on what free residual chlorine (FRC) levels must be at water distribution points, in order to provide adequate FRC protection up to the point of consumption in households many hours later at each site. The site-specific FRC targets developed through this modelling approach improved the proportion of households having sufficient chlorine residual (i.e., ≥0.2 mg/L FRC) at the point of consumption in three out of four field studies (South Sudan 2013, Jordan 2014, and Rwanda 2015). These sites tended to be hotter (i.e., average mid-afternoon air temperatures >30°C) and/or had poorer water, sanitation, and hygiene (WASH) conditions, contributing to considerable chlorine decay between distribution and consumption. Our modelling approach did not work as well where chlorine decay was small in absolute terms (Jordan 2015). In such settings, which were cooler (20 to 30°C) and had better WASH conditions, we found that the upper range of the current Sphere chlorination guideline (i.e., 0.5 mg/L FRC) provided sufficient residual chlorine for ensuring household water safety up to 24 hours post-distribution. Site-specific and evidence-based chlorination targets generated from post-distribution chlorine decay modelling could help improve household water safety and public health outcomes in refugee camp settings where the current Sphere chlorination guideline does not provide adequate residual protection. Water quality monitoring in refugee/IDP camps should shift focus from distribution points to household points of consumption in order to monitor if the intended public health goal of safe water at the point of consumption is being achieved.
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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 | 0.085 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".