Syed Imran Ali, Michael De Santi, Matt Arnold, Usman T Khan, Tarra L Penney, Syed Saad Ali, Jean-François Fesselet, James Orbinski
{"title":"考克斯巴扎尔安全水优化工具的概念验证评估:人道主义紧急情况下安全供水的水质建模。","authors":"Syed Imran Ali, Michael De Santi, Matt Arnold, Usman T Khan, Tarra L Penney, Syed Saad Ali, Jean-François Fesselet, James Orbinski","doi":"10.1136/bmjgh-2024-018631","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Waterborne 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.</p><p><strong>Methods: </strong>We 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.</p><p><strong>Results: </strong>The 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<sup>2</sup> decreased from 0.50 to 0.23 between training and testing data sets, indicating periodic retraining is required. The SWOT's machine-learning model predicted a 1%-9% probability of household FRC<0.2 mg/L at 15 hours, close to the observed 12% and in line with the observed 7% risk during baseline and endline, respectively. Households that collected water meeting the SWOT target were more likely to have sufficient protection after 15 hours compared with the status quo target (90% vs 35%, p<0.01), demonstrating the SWOT's efficacy. The SWOT target was not fully implemented at tapstands, so we did not observe change in household FRC during endline.</p><p><strong>Conclusion: </strong>The 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.</p>","PeriodicalId":9137,"journal":{"name":"BMJ Global Health","volume":"10 8","pages":""},"PeriodicalIF":6.1000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374622/pdf/","citationCount":"0","resultStr":"{\"title\":\"Proof-of-concept evaluation at Cox's Bazar of the Safe Water Optimization Tool: water quality modelling for safe water supply in humanitarian emergencies.\",\"authors\":\"Syed Imran Ali, Michael De Santi, Matt Arnold, Usman T Khan, Tarra L Penney, Syed Saad Ali, Jean-François Fesselet, James Orbinski\",\"doi\":\"10.1136/bmjgh-2024-018631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Waterborne 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.</p><p><strong>Methods: </strong>We 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.</p><p><strong>Results: </strong>The 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<sup>2</sup> decreased from 0.50 to 0.23 between training and testing data sets, indicating periodic retraining is required. The SWOT's machine-learning model predicted a 1%-9% probability of household FRC<0.2 mg/L at 15 hours, close to the observed 12% and in line with the observed 7% risk during baseline and endline, respectively. Households that collected water meeting the SWOT target were more likely to have sufficient protection after 15 hours compared with the status quo target (90% vs 35%, p<0.01), demonstrating the SWOT's efficacy. The SWOT target was not fully implemented at tapstands, so we did not observe change in household FRC during endline.</p><p><strong>Conclusion: </strong>The 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.</p>\",\"PeriodicalId\":9137,\"journal\":{\"name\":\"BMJ Global Health\",\"volume\":\"10 8\",\"pages\":\"\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2025-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374622/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ Global Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjgh-2024-018631\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Global Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/bmjgh-2024-018631","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Proof-of-concept evaluation at Cox's Bazar of the Safe Water Optimization Tool: water quality modelling for safe water supply in humanitarian emergencies.
Introduction: Waterborne 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.
Methods: We 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.
Results: The 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 R2 decreased from 0.50 to 0.23 between training and testing data sets, indicating periodic retraining is required. The SWOT's machine-learning model predicted a 1%-9% probability of household FRC<0.2 mg/L at 15 hours, close to the observed 12% and in line with the observed 7% risk during baseline and endline, respectively. Households that collected water meeting the SWOT target were more likely to have sufficient protection after 15 hours compared with the status quo target (90% vs 35%, p<0.01), demonstrating the SWOT's efficacy. The SWOT target was not fully implemented at tapstands, so we did not observe change in household FRC during endline.
Conclusion: The 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.
期刊介绍:
BMJ Global Health is an online Open Access journal from BMJ that focuses on publishing high-quality peer-reviewed content pertinent to individuals engaged in global health, including policy makers, funders, researchers, clinicians, and frontline healthcare workers. The journal encompasses all facets of global health, with a special emphasis on submissions addressing underfunded areas such as non-communicable diseases (NCDs). It welcomes research across all study phases and designs, from study protocols to phase I trials to meta-analyses, including small or specialized studies. The journal also encourages opinionated discussions on controversial topics.