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      Do Sanitation Improvements Reduce Fecal Contamination of Water, Hands, Food, Soil, and Flies? Evidence from a Cluster-Randomized Controlled Trial in Rural Bangladesh

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          Abstract

          Sanitation improvements have had limited effectiveness in reducing the spread of fecal pathogens into the environment. We conducted environmental measurements within a randomized controlled trial in Bangladesh that implemented individual and combined water treatment, sanitation, handwashing (WSH) and nutrition interventions (WASH Benefits, NCT01590095). Following approximately 4 months of intervention, we enrolled households in the trial’s control, sanitation and combined WSH arms to assess whether sanitation improvements, alone and coupled with water treatment and handwashing, reduce fecal contamination in the domestic environment. We quantified fecal indicator bacteria in samples of drinking and ambient waters, child hands, food given to young children, courtyard soil and flies. In the WSH arm, Escherichia coli prevalence in stored drinking water was reduced by 62% (prevalence ratio = 0.38 (0.32, 0.44)) and E. coli concentration by 1-log (Δlog 10 = −0.88 (−1.01, −0.75)). The interventions did not reduce E. coli along other sampled pathways. Ambient contamination remained high among intervention households. Potential reasons include noncommunity-level sanitation coverage, child open defecation, animal fecal sources, or naturalized E. coli in the environment. Future studies should explore potential threshold effects of different levels of community sanitation coverage on environmental contamination.

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          Super learner.

          When trying to learn a model for the prediction of an outcome given a set of covariates, a statistician has many estimation procedures in their toolbox. A few examples of these candidate learners are: least squares, least angle regression, random forests, and spline regression. Previous articles (van der Laan and Dudoit (2003); van der Laan et al. (2006); Sinisi et al. (2007)) theoretically validated the use of cross validation to select an optimal learner among many candidate learners. Motivated by this use of cross validation, we propose a new prediction method for creating a weighted combination of many candidate learners to build the super learner. This article proposes a fast algorithm for constructing a super learner in prediction which uses V-fold cross-validation to select weights to combine an initial set of candidate learners. In addition, this paper contains a practical demonstration of the adaptivity of this so called super learner to various true data generating distributions. This approach for construction of a super learner generalizes to any parameter which can be defined as a minimizer of a loss function.
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            Treating water with chlorine at point-of-use to improve water quality and reduce child diarrhea in developing countries: a systematic review and meta-analysis.

            We conducted a systematic review of all studies that measured diarrheal health impacts in children and the impact on water quality of point-of-use chlorine drinking water treatment. Twenty-one relevant studies were identified from > 856 screened abstracts. Data were extracted and combined using meta-analysis to provide summary estimates of the intervention effect. The intervention reduced the risk of child diarrhea (pooled relative risk: 0.71, 0.58-0.87) and it reduced the risk of stored water contamination with Escherichia coli (pooled relative risk: 0.20, 0.13-0.30). A major finding from this review is that nearly all trials on this topic have been short (median length was 30 weeks). Although not statistically significant, we observed an attenuation of the intervention's reduction of child diarrhea in longer trials. Future studies with multi-year follow-up are required to assess the long-term acceptability and sustainability of health impacts shown by the shorter trials identified in this review.
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              Less than obvious - statistical treatment of data below the detection limit

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                Author and article information

                Journal
                Environ Sci Technol
                Environ. Sci. Technol
                es
                esthag
                Environmental Science & Technology
                American Chemical Society
                0013-936X
                1520-5851
                26 September 2018
                06 November 2018
                : 52
                : 21
                : 12089-12097
                Affiliations
                []Department of Forestry and Environmental Resources, North Carolina State University , Raleigh, North Carolina 27695, United States
                []School of Public Health, University of California , Berkeley, California 94720, United States
                [§ ]Civil and Environmental Engineering, Tufts University , Medford, Massachusetts 02153, United States
                []Civil and Environmental Engineering, Stanford University , Stanford, California 94305, United States
                []Infectious Disease Division, International Centre for Diarrhoeal Disease Research , Bangladesh, Dhaka, 1212, Bangladesh
                [# ]Water Global Practice, World Bank , Washington, D.C. 20433, United States
                []Water Global Practice, World Bank , Dhaka, 1207, Bangladesh
                []University at Buffalo , Buffalo, New York 14214, United States
                []Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States
                []Infectious Diseases & Geographic Medicine, Stanford University , Stanford, California 94305, United States
                Author notes
                Article
                10.1021/acs.est.8b02988
                6222553
                30256095
                bf4dc35a-455d-43d1-9283-506ac0b7f8ca
                Copyright © 2018 American Chemical Society

                This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.

                History
                : 02 June 2018
                : 26 September 2018
                : 12 September 2018
                Categories
                Article
                Custom metadata
                es8b02988
                es-2018-02988q

                General environmental science
                General environmental science

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