Evidence map›Paper›PMID 40835482›Full record

ArticleBMJ global health2025

Proof-of-concept evaluation at Cox's Bazar of the Safe Water Optimization Tool: water quality modelling for safe water supply in humanitarian emergencies.

Syed Imran Ali, Michael De Santi, Matt Arnold, Usman T Khan, Tarra L Penney, Syed Saad Ali, Jean-François Fesselet, James Orbinski

Abstract read
In one paragraph

Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Syed Imran AliDahdaleh Institute for Global Health Research, York University, Toronto, Ontario, Canada siali@yorku.ca.ORCID 0000-0001-6056-4746
Michael De SantiDahdaleh Institute for Global Health Research, York University, Toronto, Ontario, Canada.
Matt ArnoldDahdaleh Institute for Global Health Research, York University, Toronto, Ontario, Canada.
Usman T KhanDahdaleh Institute for Global Health Research, York University, Toronto, Ontario, Canada.ORCID 0009-0005-2760-2030
Tarra L PenneyDahdaleh Institute for Global Health Research, York University, Toronto, Ontario, Canada.
Syed Saad AliDahdaleh Institute for Global Health Research, York University, Toronto, Ontario, Canada.
Jean-François FesseletPublic Health Department, Médecins Sans Frontières, Amsterdam, The Netherlands.
James OrbinskiDahdaleh Institute for Global Health Research, York University, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWaterborne diseases are leading concerns in emergencies. Humanitarian guidelines stipulate universal water chlorination targets, but these fail to reliably protect water as postdistribution chlorine decay can leave water vulnerable to pathogenic recontamination. The Safe Water Optimization Tool (SWOT) models chlorine decay to generate context-specific chlorination targets that ensure water remains protected up to point-of-consumption. The SWOT has not been tested in an active humanitarian response, so we conducted a proof-of-concept evaluation at a Cox's Bazar refugee settlement to validate its modelling and assess its efficacy and effectiveness.

methodsWe trained the SWOT using data collected from July to September 2019 and evaluated using data from October to December 2019 (n=2221). We validated the SWOT's modelling by comparing performance using training and testing data sets. We assessed efficacy using binary logistic regression comparing household free residual chlorine (FRC) when the SWOT target was delivered at tapstands versus the status quo target, and effectiveness using interrupted time series analysis of the proportion of households with protective FRC before and after SWOT implementation.

resultsThe SWOT generated a context-specific FRC target of 0.85-1.05 mg/L for 15-hours protection. Validation of the SWOT's process-based model showed R

conclusionThe SWOT can generate context-specific chlorination targets that protect water against pathogenic recontamination. Improving feedback between monitoring and treatment would help system operators unlock the SWOT's full water safety potential.

Indexed as

Waterborne DiseasesWater QualityWater SupplyChlorineEmergenciesHalogenationHumansProof of Concept StudyWater PurificationChlorineControl strategiesEnvironmental healthInfections, diseases, disorders, injuriesIntervention studyMathematical modelling

Identifiers

PMID40835482
PMCPMC12374622

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.