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Abstract
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Point-of-use (POU) drinking water treatment plays a crucial role in overcoming the health burden associated with waterborne diarrheal disease in low and middle-income regions. This study focuses on the long run impacts of three POU water treatments – boiling on a cook stove, ceramic filtration, and membrane filtration– in two districts of Uganda. We analyse the sustained use of the cook stove and the filters, and the impact on microbiological water quality at POU, diarrhoeal disease and household savings in the course of 18 months. A total of 600 households are involved in this randomised controlled trial. 450 households receive one of the three treatments and training on its adequate usage. 150 households are assigned to the control group. Data collection involves household surveys and water sample analysis during a baseline and four follow-ups. Focus group discussions at baseline and at end line gather an in-depth understanding of the results.
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After
Point-of-use (POU) drinking water treatment plays a crucial role in overcoming the health burden associated with waterborne diarrheal disease in low and middle-income regions. This study focuses on the impacts of three POU water treatments, boiling on a rocket stove, ceramic filtration, and membrane filtration, in two districts of rural Western Uganda in the course of 18 months. On the one hand, we measure the effectiveness of the intervention on microbiological water quality and health. We compare the water treatment systems from a user perspective, on the other hand, including affordability, effective demand, labor burden and user acceptance. A total of 600 households are involved in this randomized controlled trial. 450 households receive one of the three treatments and training on its adequate usage. 150 households are assigned to the control group. Data collection involves household surveys, health diaries and water sample analysis during a baseline and four follow-ups.
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Last Published
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November 27, 2023 09:35 AM
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September 12, 2024 07:28 AM
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Intervention (Public)
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The intervention consists of the random distribution of three different water treatment methods over the selected treatment population and training in its correct use. The treatments are an improved cook stove to boil water, ceramic filtration and membrane filtration. Each drinking water filter is accompanied by a leaflet with instructions on the use and maintenance needs. The drinking water filters and cook stoves are distributed to the dwellings of the selected households by members of HEWASA and Kiima foods, with the help of local guides of the Village Health Teams (VHTs). Members of HEWASA provide individual training at the dwelling of the responsible household members in use and maintenance of the assigned water treatment method.
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After
The intervention consists of the random distribution of three different water treatment methods over the selected treatment population and training in its correct use. The treatments are a rocket stove to boil water, ceramic filtration and membrane filtration. Each drinking water filter is accompanied by a leaflet with instructions on the use and maintenance needs. The drinking water filters and cook stoves are distributed to the dwellings of the selected households by members of HEWASA and Kiima foods, with the help of local guides of the Village Health Teams (VHTs). Members of HEWASA provide small group training in each village for the responsible household members in use and maintenance of the assigned water treatment method.
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Primary Outcomes (End Points)
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Before
1. Drinking water quality
2. Diarrhoeal disease
3. Uptake
4. Household savings
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1. Drinking water quality
2. Health
3. User acceptance
4. Affordability
5. Labor burden
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Primary Outcomes (Explanation)
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1. The participating households will be asked to identify the main drinking water container in the dwelling and a water sample will be taken from the designated water container. To assess the microbiological improvements in drinking water quality, household water samples will be analysed in the lab on the presence of total thermotolerant coliforms (TTC), and in particular the bacterium E.coli. The assessment will be performed using the membrane filtration technique on membrane lauryl sulphate medium. The unit of measurement is Colony Forming Units (CFU). A second aspect of water analysis is turbidity, i.e. a measure for the presence of particles in the drinking water. The unit of analysis is Nephelometric Turbidity Units (NTU). The values of TTC, E.coli and turbidity will both be reported in levels (CFU/NTU).
2. Diarrheal disease will be measured by recording cases among children below five years of age. A diarrhea case is defined according to the WHO-definition as “three or more loose stools passed within 24 hours, or more frequently than is normal for the individual''. The primary outcomes of diarrheal disease will focus both on incidence and longitudinal prevalence. The method is therefore twofold. First, the female household head will be surveyed on diarrhea cases in the previous seven days among children under five years of age at each follow-up wave. Second, each household will be provided with a diary to indicate whether a child experienced diarrhea on a daily basis. These diaries will be collected by the VHTs every two weeks before or after religious meetings. The outcome of interest ‘diarrhea’ will be obscure to the target population, as the relevant symptom diarrhea will be added to a list of other symptoms such as fever and cough both for the survey and the diary method (see also Performance and expectancy biases, p.14). The incidence outcomes will be reported binary by addressing whether a child had diarrhea in the previous seven days. The longitudinal prevalence will be reported as a continuous variable indicating the number of days with diarrhea between the survey waves and over the full 18-month period.
3. At each household visit the enumerators observe whether the water storage container or filter contains treated drinking water, a possible objective indicator of filter use (Rosa et al., 2014). Furthermore, the self-reported use of the cook stove and the drinking water filter will be surveyed. The respondent responsible for the cook stove or the filter will be asked when water treatment was last applied. If the treatment method is no longer being used or has broken down (irreversibly clogged, damaged etc.), the time it went out of service will be recorded. The objective and subjective use of the filter will both be expressed binary, respectively based on the presence of (treated) water and the reported use in the previous day (or today).
4. To address financial savings due to water filtration or energy efficient boiling, all respondents will be surveyed on the household expenses for charcoal, firewood or other fuels used for the treatment of drinking water or cooking in the previous seven days. Since households could receive charcoal, firewood or other fuels from relatives, they will also be questioned on the amount of each consumed in the previous seven days. Additionally, 40 households receiving the cook stove will be closely monitored during one week at each follow-up to weigh the exact amount of wood fuel used for boiling. The total monetary value will be both expressed in the local currency Ugandan Shilling and converted to US Dollar. If a household collects firewood for free from the surrounding bushes, the time spent to collect firewood in the previous seven days will be estimated by multiplying the number of roundtrips with the average timespan needed to collect firewood. The time saved will be expressed in hours.
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After
1. The participating households will be asked to identify the main drinking water storage container in the dwelling and a water sample will be taken from the designated water container. To assess the microbiological improvements in drinking water quality, household water samples will be analyzed in the lab on the presence of total thermotolerant coliforms (TTC), and in particular the bacterium E.coli. The assessment will be performed using the membrane filtration technique on membrane lauryl sulphate medium. The unit of measurement is Colony Forming Units (CFU). A second aspect of water analysis is turbidity, i.e. a measure for the presence of particles in the drinking water. The unit of analysis is Nephelometric Turbidity Units (NTU). The values of TTC, E.coli and turbidity will both be reported in levels (CFU/NTU). All microbiological data will be log transformed.
2. Health will be measured by surveying the female household head on medical care seeking and medical costs in the last month. Furthermore, for each household member the incidence of illness in the last seven days will be recorded.
Diarrhea prevalence in young children will be closely monitored by self-recording cases daily among children below five years of age in a health diary. A diarrhea case is defined according to the WHO-definition as “three or more loose stools passed within 24 hours, or more frequently than is normal for the individual''. The diaries also include the symptoms of vomiting and fever.
3. Apart from water quality and health benefits, the products are evaluated from a user-perspective. At each household visit the enumerators observes the presence and functionality of the product, surveys on frequency of usage and untreated water consumption and observes whether the filter contains treated drinking water and the cook stove is used. Furthermore, the user is asked to rate the product on easiness, safety, robustness, effectiveness and speed.
4. To address potential energy savings due to water filtration or energy efficient boiling, all respondents will be surveyed on the household expenses for charcoal, firewood or other fuels used in the previous seven days. Furthermore, a willingness to pay questionnaire is conducted to elicit users' product value under real market circumstances.
5. The labor burden is estimated by surveying the main operating household member on the time spend for treating drinking water. We measure, the volume of drinking water fetched and treated, as well as the time spend on and the frequency of each task involved in the process. This allows to compute a total time per volume of water. Furthermore, the respondents are questioned on the main operators of the product to detect gender biases in labor burden.
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Experimental Design (Public)
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Experimental evidence to answer the four research questions will be obtained by a four-arm randomized controlled trial over an 18-month period. The trial will include three treatment groups that each receive either a cook stove for energy efficient boiling, the ceramic filter or a membrane filter, and one control group that continues business as usual. The RCT design allows to identify and compare the long run causal impacts of the three treatments on uptake, microbiological water quality, diarrheal disease among young children and household time and money savings. Data will be obtained by a baseline survey and four follow-up surveys, accompanied by drinking water quality analysis at point of source and point of use. The treatment will be phased-in i.e., all households in the control group will receive a water filter at the end of the experiment.
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Experimental evidence to answer the four research questions will be obtained by a four-arm randomized controlled trial over an 18-month period. The trial will include three treatment groups that each receive either a cook stove for energy efficient boiling, the ceramic filter or a membrane filter, and one control group that continues business as usual. The RCT design allows to identify and compare the long run causal impacts of the three treatments on the outcomes listed above. Data will be obtained by a baseline survey and four follow-up surveys, accompanied by drinking water quality analysis at point of source and point of use. The treatment will be phased-in i.e., all households in the control group will receive a water filter at the end of the experiment.
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Power calculation: Minimum Detectable Effect Size for Main Outcomes
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The following power calculations are calculated based on the means and variances at baseline in the data.
600 households evenly divided over four treatment arms account for a minimal detectable effect size of 53 CFUs reduction in E.coli, 61 CFUs reduction in TTC and 13 NTUs reductions in turbidity. The standardized minimal detectable effect size is 0.36.
Variables Mean SD MDE MDE standardized MDE as percentage of the mean
E.coli 61.237202 146.89854 52.698715 .35874227 .86056703
TTC 105.51195 170.16864 61.04668 .35874227 .57857603
Turbidity 13.035959 36.064888 12.938 .35874227 .99248546
900 children under five evenly divided over four treatment arms account for a minimal detectable effect size of 0.13 in diarrheal disease incidence in the past seven days. The standardized minimal detectable effect size is 0.32.
Variables Mean SD MDE MDE standardized MDE as percentage of the mean
Diarrhea incidence .23825504 .42625439 .13466863 .31593487 .56522894
The estimated effect sizes are rather conservative as they already account for 5% non-compliance in the treatment group and 10% attrition. Moreover, these calculations do not apply to the pooled estimator over the four follow up rounds. The pooled estimator will have higher power stemming from the multiple rounds of post-treatment data collection, as suggested by McKenzie (2012).
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We estimate the minimal detectable effect sizes (MDEs) at each follow-up for
microbiological water quality and health outcomes in children under five years. We
design an experiment with 80% power and 5% significance level and rely on the
standard deviations of the outcome variables in the baseline data. The MDEs are
conservative since they account for 10% attrition and 5% non-compliance.
In the first scenario, we find MDEs of 51% and 49% for E.coli and TTC, which are very likely given the 99% efficacy of the household water treatment methods. We are able to detect a reduction of 44% of E.coli and 43% in TTC in the pooled scenario. There is a 40% reduction in turbidity detectable in the first scenario and 39% In the second scenario. Considering child health in the first scenario, we are able to detect reductions of 69%, 39% and 89% in respectively diarrhea, fever and vomiting in the last seven days. The number of days ill should decrease by 43% in order to be detected. Given that household water treatment is believed to reduce diarrhea by a half, these MDEs are on the high end. We are more likely to detect an effect when pooling the treatment arms. The MDEs as percentage of the mean are then estimated at 46% for diarrhea incidence, 26% for fever, 59% for vomiting and 29% for number of days ill. Remark that we can as well pool the observations over time given the panel structure of the final dataset. Pooling the observation over time increases the sample size and reduces the MDEs for the given significance level and power.
aseline parameters One treatment arm vs control Pooled treatment arms vs control
Variables Mean SD MDE MDE std. MDE % MDE MDE std. MDE %
Ecoli (10logCF U/100mL) .85866147 .86257356 .3094416 .35874227 50.959103 .25265801 .29291183 44.108986
TTC (10logCF U/100mL) 1.4163516 .8232103 .29532033 .35874227 49.33831 .24112804 .29291183 42.605278
Turbidity (10logN T U/100mL) .60001236 .61352879 .2200987 .35874227 39.757736 .17970984 .29291183 33.886497
900 children under five evenly divided over four treatment arms account for a minimal detectable effect size of 0.13 in diarrheal disease incidence in the past seven days. The standardized minimal detectable effect size is 0.32.
Baseline parameters One treatment arm vs control Pooled treatment arms vs control
Variables Mean SD ICC MDE MDE std. MDE % MDE MDE std. MDE %
Diarrhea .23825504 .42625439 .32675844 .16493471 .38693962 .69226116 .10995647 .25795975 .46150744
Fever .49328858 .50023478 .25861463 .1907052 .38123137 .38659966 .1271368 .25415424 .25773311
Vomiting .16442953 .37087238 .40639234 .1459403 .39350545 .8875553 .09729353 .26233697 .59170353
Days ill 2.2940516 2.5927639 .28176934 .99349666 .3831805 .4330751 .6623311 .25545368 .28871673
The estimated effect sizes are rather conservative as they already account for 5% non-compliance in the treatment group and 10% attrition. Moreover, these calculations do not apply to the pooled estimator over the four follow up rounds. The pooled estimator will have higher power stemming from the multiple rounds of post-treatment data collection, as suggested by McKenzie (2012).
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Additional Keyword(s)
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Rct; point-of-use drinking water treatment; filtration; diarrhea, household savings; Uganda
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RCT, point-of-use drinking water treatment, filtration, boiling, diarrhea, user-centered, Uganda
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Keyword(s)
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Behavior, Environment And Energy, Health
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Behavior, Environment And Energy, Gender, Health
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Secondary Outcomes (End Points)
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1. Drinking water quality
2. Diarrheal disease
3. Uptake
4. Household savings
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Secondary Outcomes (Explanation)
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1. Apart from the primary outcomes TTC, E.coli and turbidity for drinking water quality at home, secondary outcomes are considered. First, households will be asked about their primary water source. These choices could change due to seasonal availability of water, but also because of the intervention. For instance, receiving a water filter could induce households to fetch water at more turbid sources closer to the home. We survey whether there is a qualitative change in the nature of the source (well, borehole etc.). Next, we analyze a water sample of each indicated source on the same characteristics as outlined above to determine potential changes in source water quality over the course of the intervention.
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3. As a secondary outcome, the respondent will be asked whether a household member drank unfiltered or non-boiled water in the previous day. If this is the case, the respondent will be asked whether another method was used or whether the water was left untreated. Reasons addressed by the responsible household member will be recorded. This measure of adherence to treated water also will be reported binary, and separately for children below five, children above five and adults. All reasons addressed for not drinking treated water will be listed and thematically ordered.
4. As secondary outcomes, the indirect savings in resources and time due to lower health care expenses and less absent days at school or work because of diarrhea will be recorded. The respondent will be surveyed about medical expenditures and the absence from usual activities of children and adults due to diarrhea in the previous seven days. The first will be reported in monetary terms as outlined above, while the latter will be reported in number of days.
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