Learn more: PMC Disclaimer | PMC Copyright Notice
Interventions to improve water quality for preventing diarrhoea
Kelly T Alexander, David Sinclair, Sophie Boisson, Rachel Peletz, Howard H Chang, Fiona Majorin, Sandy Cairncross, and Cochrane Infectious Diseases GroupAbstract
Background
Diarrhoea is a major cause of death and disease, especially among young children in low‐income countries. In these settings, many infectious agents associated with diarrhoea are spread through water contaminated with faeces.
In remote and low‐income settings, source‐based water quality improvement includes providing protected groundwater (springs, wells, and bore holes), or harvested rainwater as an alternative to surface sources (rivers and lakes). Point‐of‐use water quality improvement interventions include boiling, chlorination, flocculation, filtration, or solar disinfection, mainly conducted at home.
Objectives
To assess the effectiveness of interventions to improve water quality for preventing diarrhoea.
Search methods
We searched the Cochrane Infectious Diseases Group Specialized Register (11 November 2014), CENTRAL (the Cochrane Library, 7 November 2014), MEDLINE (1966 to 10 November 2014), EMBASE (1974 to 10 November 2014), and LILACS (1982 to 7 November 2014). We also handsearched relevant conference proceedings, contacted researchers and organizations working in the field, and checked references from identified studies through 11 November 2014.
Selection criteria
Randomized controlled trials (RCTs), quasi‐RCTs, and controlled before‐and‐after studies (CBA) comparing interventions aimed at improving the microbiological quality of drinking water with no intervention in children and adults.
Data collection and analysis
Two review authors independently assessed trial quality and extracted data. We used meta‐analyses to estimate pooled measures of effect, where appropriate, and investigated potential sources of heterogeneity using subgroup analyses. We assessed the quality of evidence using the GRADE approach.
Main results
Forty‐five cluster‐RCTs, two quasi‐RCTs, and eight CBA studies, including over 84,000 participants, met the inclusion criteria. Most included studies were conducted in low‐ or middle‐income countries (LMICs) (50 studies) with unimproved water sources (30 studies) and unimproved or unclear sanitation (34 studies). The primary outcome in most studies was self‐reported diarrhoea, which is at high risk of bias due to the lack of blinding in over 80% of the included studies.
Source‐based water quality improvements
There is currently insufficient evidence to know if source‐based improvements such as protected wells, communal tap stands, or chlorination/filtration of community sources consistently reduce diarrhoea (one cluster‐RCT, five CBA studies, very low quality evidence). We found no studies evaluating reliable piped‐in water supplies delivered to households.
Point‐of‐use water quality interventions
On average, distributing water disinfection products for use at the household level may reduce diarrhoea by around one quarter (Home chlorination products: RR 0.77, 95% CI 0.65 to 0.91; 14 trials, 30,746 participants, low quality evidence; flocculation and disinfection sachets: RR 0.69, 95% CI 0.58 to 0.82, four trials, 11,788 participants, moderate quality evidence). However, there was substantial heterogeneity in the size of the effect estimates between individual studies.
Point‐of‐use filtration systems probably reduce diarrhoea by around a half (RR 0.48, 95% CI 0.38 to 0.59, 18 trials, 15,582 participants, moderate quality evidence). Important reductions in diarrhoea episodes were shown with ceramic filters, biosand systems and LifeStraw® filters; (Ceramic: RR 0.39, 95% CI 0.28 to 0.53; eight trials, 5763 participants, moderate quality evidence; Biosand: RR 0.47, 95% CI 0.39 to 0.57; four trials, 5504 participants, moderate quality evidence; LifeStraw®: RR 0.69, 95% CI 0.51 to 0.93; three trials, 3259 participants, low quality evidence). Plumbed in filters have only been evaluated in high‐income settings (RR 0.81, 95% CI 0.71 to 0.94, three trials, 1056 participants, fixed effects model).
In low‐income settings, solar water disinfection (SODIS) by distribution of plastic bottles with instructions to leave filled bottles in direct sunlight for at least six hours before drinking probably reduces diarrhoea by around a third (RR 0.62, 95% CI 0.42 to 0.94; four trials, 3460 participants, moderate quality evidence).
In subgroup analyses, larger effects were seen in trials with higher adherence, and trials that provided a safe storage container. In most cases, the reduction in diarrhoea shown in the studies was evident in settings with improved and unimproved water sources and sanitation.
Authors' conclusions
Interventions that address the microbial contamination of water at the point‐of‐use may be important interim measures to improve drinking water quality until homes can be reached with safe, reliable, piped‐in water connections. The average estimates of effect for each individual point‐of‐use intervention generally show important effects. Comparisons between these estimates do not provide evidence of superiority of one intervention over another, as such comparisons are confounded by the study setting, design, and population.
Further studies assessing the effects of household connections and chlorination at the point of delivery will help improve our knowledge base. As evidence suggests effectiveness improves with adherence, studies assessing programmatic approaches to optimising coverage and long‐term utilization of these interventions among vulnerable populations could also help strategies to improve health outcomes.
16 April 2019
Update pending
Studies awaiting assessment
The CIDG is currently examining a new search conducted in April 2019 for potentially relevant studies. These studies have not yet been incorporated into this Cochrane Review.
Plain language summary
Interventions to improve water quality and prevent diarrhoea
This Cochrane Review summarizes trials evaluating different interventions to improve water quality and prevent diarrhoea. After searching for relevant trials up to 11 November 2014, we included 55 studies enrolling over 84,000 participants. Most included studies were conducted in low‐ or middle‐income countries (LMICs) (50 studies), with unimproved water sources (30 studies), and unimproved or unclear sanitation (34 studies).
What causes diarrhoea and what water quality interventions might prevent diarrhoea?
Diarrhoea is a major cause of death and disease, especially among young children in low‐income countries where the most common causes are faecally contaminated water and food, or poor hygiene practices.
In remote and low‐income settings, source‐based water quality improvement may include providing protected groundwater (springs, wells, and bore holes) or harvested rainwater as an alternative to surface sources (rivers and lakes). Alternatively water may be treated at the point‐of‐use in people's homes by boiling, chlorination, flocculation, filtration, or solar disinfection. These point‐of‐use interventions have the potential to overcome both contaminated sources and recontamination of safe water in the home.
What the research says
There is currently insufficient evidence to know if source‐based improvements in water supplies, such as protected wells and communal tap stands or treatment of communal supplies, consistently reduce diarrhoea in low‐income settings (very low quality evidence). We found no trials evaluating reliable piped‐in water supplies to people's homes.
On average, distributing disinfection products for use in the home may reduce diarrhoea by around one quarter in the case of chlorine products (low quality evidence), and around a third in the case of flocculation and disinfection sachets (moderate quality evidence).
Water filtration at home probably reduces diarrhoea by around a half (moderate quality evidence), and effects were consistently seen with ceramic filters (moderate quality evidence), biosand systems (moderate quality evidence) and LifeStraw® filters (low quality evidence). Plumbed‐in filtration has only been evaluated in high‐income settings (low quality evidence).
In low‐income settings, distributing plastic bottles with instructions to leave filled bottles in direct sunlight for at least six hours before drinking probably reduces diarrhoea by around a third (moderate quality evidence).
Research assessing the effects of household connections and chlorination at the point of delivery will help improve our knowledge base. Evidence indicates the more people use the various interventions for improving water quality, the larger the effects, so research into practical approaches to increase coverage and help assure long term use of them in poor groups will help improve impact.
Summary of findings
Background
Description of the condition
Diarrhoeal disease is the third leading cause of mortality in low‐income countries, causing an estimated 1.4 million deaths in 2012 (WHO 2014;GBD 2015). Young children are especially vulnerable, with diarrhoea accounting for more than a quarter of all deaths in children aged under five years in Africa and Southeast Asia (Murray 2012; Lanata 2013; Walker 2013).
The bacterial, viral, and protozoan pathogens causing diarrhoeal disease are primarily transmitted via the faecal‐oral route, through the consumption of faecally contaminated food and water (Byers 2001). Among the most important of these are rotavirus, Cryptosporidium sp.,Escherichia coli,Salmonella sp.,Shigella sp.,Campylobacter jejuni,Vibrio cholerae, norovirus, Giardia lamblia, and Entamoeba histolytica (Leclerc 2002; Kotloff 2013), though the relative importance of these varies among settings, seasons, and population groups.
An estimated 1.1 billion people worldwide rely on water supplies that are at high risk of faecal contamination (Bain 2014). Moreover, nearly half the world's population lack household water connections (WHO/UNICEF 2015), and are at increased risk of unsafe water due to contamination during collection, storage, and use in the home (Wright 2004).
Description of the intervention
Interventions to improve the microbiological quality of water can be grouped into four main categories:
- Physical removal of pathogens (for example, filtration, adsorption, or sedimentation).
- Chemical treatment to kill or deactivate pathogens (most commonly with chlorine).
- Disinfection by heat (for example, boiling or pasturization) or ultraviolet (UV) radiation (for example, solar disinfection, or artificial UV lamps).
- Combination of these approaches (for example, filtration or flocculation combined with disinfection).
In higher‐income countries, and in many urban settings worldwide, drinking water is treated centrally at the source of supply and distributed to consumers through a network of pipes and household taps. Alternatively, water may be treated at any point in the distribution network, or at the 'point‐of‐use' (POU) in people's homes, schools, or workplaces.
In remote and low‐income settings, source‐based water quality improvement may include providing protected groundwater (springs, wells, and bore holes) or harvested rainwater as an alternative to surface sources (rivers and lakes). These improvements frequently also improve both the quantity and access to water by increasing the volume or frequency of water delivery or reducing the time spent in collecting water. This may result in significant benefits not only in health but also in economic and social welfare (Hutton 2013; Stelmach 2015).
Potential and widely used POU interventions for remote or low‐income settings include boiling, filtration, chlorination, flocculation, and solar disinfection. These interventions have the potential to overcome both contaminated sources and recontamination of safe water in the home (Wright 2004). A review commissioned by the World Health Organization (WHO) identified a wide variety of options for household‐based water treatment and assessed the available evidence on their microbiological effectiveness, health impact, acceptability, affordability, sustainability, and scalability (Sobsey 2002).
How the intervention might work
Health authorities generally accept that microbiologically safe water plays an important role in preventing outbreaks of waterborne diseases (Reynolds 2008). Moreover, there is evidence that chlorination and filtration of municipal water supplies contributed to substantial health gains in the late 19th and early 20th century (Cutler 2005).
However, much of the epidemiological evidence for increased health benefits following improvements in the quality of drinking water has been equivocal, particularly in low‐income settings (Clasen 2006; Waddington 2009; Cairncross 2010).
This may be due to the variety of alternative transmission pathways, such as ingestion of contaminated food, person‐to‐person contact, or direct contact with infected faeces. In addition, interventions which only target the home may fail if unsafe water is consumed at work or school. Consequently, effective programmes may require combined interventions to address not only water quality, but also water quantity and access, the proper disposal of human faeces (sanitation), and the promotion of hand washing and hygiene practices within communities.
The effectiveness of individual water quality interventions may also vary between settings due to the varied prevalence of the organisms causing diarrhoea. For instance, ceramic filters are only marginally protective against viral illness, while chlorination may provide little protection against Cryptosporidium.
Why it is important to do this review
This is an update of a Cochrane Review that was first completed in 2006 (Clasen 2006). The review concluded that, in general, interventions to improve microbiological quality of drinking water are effective in preventing diarrhoea, and that interventions at the household level were more effective than those at the source.
New studies have been recently published, and other unpublished studies have been made available to us. In this Cochrane Review update, we have reapplied the inclusion criteria, repeated data extraction, added new studies, and used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess the quality of the evidence. We were also able to apply statistical methods to unify the measures of effect and to apply additional criteria for subgrouping based on study design, setting, and length of follow‐up.
Objectives
To assess the effectiveness of interventions to improve water quality for preventing diarrhoea.
Methods
Criteria for considering studies for this review
Types of studies
Cluster‐randomized controlled trials (cluster‐RCTs), quasi‐randomized controlled trials (quasi‐RCTs) and controlled before‐and‐after studies (CBAs).
Types of participants
Children and adults.
Types of interventions
Intervention
Any intervention aimed at improving the microbiological quality of drinking water.
We included interventions that combined improvements in water quality with hygiene or health promotion, but excluded studies that combined water quality interventions with other water, sanitation, and hygiene (WASH) interventions, such as improvements in water quantity or sanitation. We also excluded studies where the water quality intervention was implemented away from the home, such as at schools, clinics, markets, or workplaces.
Control
No intervention, or a dummy intervention.
Types of outcome measures
Primary
- Diarrhoea episodes among individuals, whether or not confirmed by microbiological examination.
The WHO's definition of diarrhoea is three or more loose or fluid stools (that take the shape of the container) in a 24‐hour period (WHO 1993). We defined diarrhoea and an episode in accordance with the case definitions used in each trial. In the 'Summary of findings' tables, we have converted the results to episodes per year from a baseline of three episodes/child year in 2010 (Fischer Walker 2012).
Secondary
- Death.
- Adverse events.
We excluded studies that had no clinical outcomes; for example, studies that only report on microbiological pathogens in the stool.
Search methods for identification of studies
We attempted to identify all relevant studies regardless of language or publication status (published, unpublished, in press, and in progress).
Electronic searches
We searched the following databases using the search terms and strategy described in Appendix 1: Cochrane Infectious Diseases Group Specialized Register (11 November 2014); Cochrane Central Register of Controlled Trials (CENTRAL), published in the Cochrane Library (7 November, 2014); MEDLINE (1966 to 10 November 2014); EMBASE (1974 to 10 November 2014); and LILACS (1982 to 7 November 2014).
Searching other resources
Conference proceedings
We searched the conference proceedings of the following organizations for relevant abstracts: International Water Association (IWA) (1990 to 11 November 2014); and Water, Engineering and Development Centre, Loughborough University, UK (WEDC) (1973 to 11 November 2014).
Researchers and organizations
We contacted individual researchers working in the field and the following organizations for unpublished and ongoing studies: Water, Sanitation and Health Programme of the WHO; World Bank Water and Sanitation Program; UNICEF Water, Sanitation and Hygiene; and IRC International Water and Sanitation Centre; Foodborne and Diarrhoeal Diseases Branch, Division of Bacterial and Mycotic Diseases, Centers for Disease Control and Prevention (CDC); US Agency for International Development (USAID), including its Environmental Health Project (EHP); and the UK Department for International Development (DFID).
Reference lists
We checked the reference lists of all studies identified by the above methods.
Data collection and analysis
Selection of studies
Two review authors (RP and SB) independently reviewed the titles and abstracts located in the searches and selected all potentially relevant studies. After obtaining the full‐text articles, they independently determined whether they met the inclusion criteria. Where they were unable to agree, they consulted a third review author (TFC) and arrived at a consensus. We have listed the potentially relevant studies that were ultimately excluded together with the reasons for exclusion in the 'Characteristics of excluded studies' section.
Data extraction and management
Two review authors (RP and SB) used a pre‐piloted form to extract and record the data described in Appendix 2. One review author entered the extracted data into Review Manager (RevMan) (KA).
Assessment of risk of bias in included studies
Two review authors (KA and FM) independently assessed the risk of bias of the included studies and resolved differences of opinion through discussion.
For cluster‐RCTs we used the Cochrane 'Risk of bias' assessment tool (Higgins 2011). We followed the guidance to assess whether adequate steps were taken to reduce the risk of bias across five domains: sequence generation; allocation concealment; blinding of participants and personnel; blinding of outcome assessors; and incomplete outcome data.
For sequence generation and allocation concealment, we reported the methods used. For blinding, we described who was blinded and the blinding method. For incomplete outcome data, we reported the percentage and proportion of participants lost to follow‐up. For selective outcome reporting, any discrepancies between the methods used and the results were stated in terms of the outcomes measured or the outcomes reported. For other biases, we described any other trial features that could have affected the trial result (for example, if the trial was stopped early).
We categorized our 'Risk of bias' judgements as 'low', 'high', or 'unclear'. Where risk of bias was unclear, we attempted to contact the study authors for clarification and we resolved any differences of opinion through discussion. We classified the inclusion of randomized participants in the analysis as 'low risk' if 90% or more of all participants randomized to the study were included in the analysis.
For quasi‐RCTs and CBA studies, we used two additional criteria:
- Comparability of baseline characteristics: we classified studies as 'low risk' if there were no substantial differences between groups with respect to water quality, diarrhoeal morbidity, age, socioeconomic status, access to water, hygiene practices, and sanitation facilities.
- Contemporaneous data collection: we classified studies as 'low risk' if data were collected at similar points in time, 'unclear' if the relative timing was not reported or not clear from trial, or 'high risk' if data were not collected at similar points in time.
Measures of treatment effect
Two review authors independently extracted and, where necessary, calculated the measure of effect of the intervention on diarrhoea. We extracted the measure of effect as reported by the authors of each study, whether it be risk ratios (RRs), rate ratios, odds ratios (ORs), longitudinal prevalence ratios, or means ratios. In using these various measures of effect, we noted the design effect in treating all such measures of effect as equivalent for common outcomes such as diarrhoea and the debate about methodologies for converting such measures of effect into a single measure (Zhang 1998; McNutt 2003).
For purposes of analysis, we transformed ORs into RRs using the assumed control risk and the formula prescribed in Higgins 2011 (Section 12.5.4.4).
Unit of analysis issues
A number of the included studies had multiple intervention arms (for example, treating water with bleach or with a flocculant and disinfectant) and compared two or more intervention groups against a single control group. In some analyses, we included multiple comparisons from the same study, which double counts the control group participants and yields results in the meta‐analysis that are artificially precise. Unfortunately, because of the way data was presented in included studies, it was not possible to correct for this error by dividing the control group participants between multiple groups.
Dealing with missing data
When data was missing or incomplete we attempted to contact the study authors.
Assessment of heterogeneity
We assessed the statistical heterogeneity between trials by visually examining the forest plots for overlapping confidence intervals (CIs), applying the Chi² test with a 10% level of statistical significance, and using the I² statistic with a value of 50% to denote moderate levels of heterogeneity.
Assessment of reporting biases
When there were sufficient studies, we assessed the possibility of publication bias by constructing funnel plots and looking for asymmetry.
Data synthesis
We entered the estimates of effect using the generic inverse variance method on the log scale (Higgins 2006), and analysed the data using Review Manager (RevMan).
We stratified our primary analysis by intervention type, and study design (cluster‐RCT, quasi‐RCT, or CBA). When appropriate we used meta‐analyses to derive pooled estimates of effect using a random‐effects model because of the substantial heterogeneity in study settings, interventions, and outcome measures.
We summarized the evidence using 'Summary of findings' tables that we created using the GRADE Guideline Development Tool (GRADEpro GDT). The quality of evidence was rated using the GRADE approach, which consists of five factors that are used to assess the quality of the evidence: study limitations (risk of bias), inconsistency, indirectness, imprecision, and publication bias (Guyatt 2008).
Subgroup analysis and investigation of heterogeneity
We investigated the potential causes of heterogeneity by conducting the following subgroup analyses: age (all ages versus children under five years old); adherence with intervention (< 50%, 50% to 85%, > 85%); water source; water access; water quantity; sanitation conditions; country income level; and length of follow‐up.
In the subgroup analyses based on water source, we followed terminology used by the WHO/UNICEF Joint Monitoring Programme (JMP) on Water and Sanitation (WHO/UNICEF 2015), using 'unimproved' to extend to unprotected wells or springs, vendor‐ or tanker‐provided water or bottled water, and 'improved' to extend to household connections, public standpipes, boreholes, protected dug wells or springs, or rainwater collection; we categorized studies as 'unclear' with respect to water supply if they contained insufficient information.
We used the same definitions from the WHO/UNICEF JMP criteria to classify sanitation conditions as 'improved' (connection to a public sewer or septic system, pour‐flush latrine, simple pit latrine, ventilated improved pit latrine) or 'unimproved' (service or bucket latrines, public latrines, open latrines); where the necessary information was unclear or unreported, we categorized the sanitation facilities as 'unclear'.
To subgroup studies based on access to water source, we used the classifications defined by the Sphere Project 2011, classifying access as 'sufficient' if a consistently available source was located within 500 m, with queuing no more than 15 minutes and filling time for a 20 L container no more than three minutes, 'insufficient' if any access failed any such criteria, and 'unclear' if such criteria was unreported or unclear.
The quantity of water available to study participants was considered 'sufficient' if consisting of a minimum of 15 L per person per day. For country income level, we used the World Bank classification of country income levels (high, upper middle, lower middle, low) (World Bank Country and Lending Groups).
Sensitivity analysis
We conducted a sensitivity analysis to investigate the robustness of the results to each of the 'Risk of bias' components by including only studies that were at low risk of bias. We used this information to guide our judgements on the quality of the evidence.
In addition, we explored the impact of non‐blinding of POU interventions using a Bayesian meta‐analysis with bias correction. For this purpose, we assumed the true log relative risks from non‐blinding studies are subject to a multiplicative bias that results in the observed relative risks being inflated in magnitude. We assumed the bias is normally distributed with a mean 1.48 or 1.65 and a corresponding standard deviation (SD) of 0.17 or 0.13. These values were derived from the additive bias correction employed in Wood 2008 and Savović 2012. While we believe an attempt to adjust for non‐blinding is appropriate, we urge caution in relying on these adjusted estimates since the basis for the adjustment is from clinical (mainly drug) studies that may not be transferable to field studies of environmental interventions and because methodology for the adjustment has not been validated.
Results
Description of studies
Results of the search
The search strategy identified 1088 titles and abstracts, 1076 from the databases and 12 from the other sources (Figure 1). We screened these titles and abstracts, and obtained the full‐text articles of 161 studies for further assessment.
Included studies
Fifty‐five studies, including 84,023 participants, met the inclusion criteria (see Characteristics of included studies). Of these, six studies had two relevant intervention arms (Austin 1993; URL 1995; Luby 2004; Crump 2005; Brown 2008; Lindquist 2014), two had three arms (Luby 2006; Opryszko 2010), and one had four arms (Reller 2003), making a total of 65 discrete comparisons. Three included studies had inadequate information on disease morbidity to include in the quantitative analysis (Torun 1982 GTM; Kremer 2011 KEN; Patel 2012 KEN). We contacted the study authors for further information, but no data could be provided. Therefore we have only described these three studies and their results, but have not integrated these studies into the analysis.
Study design and length
Forty‐five studies were cluster‐RCTs, two were quasi‐RCTs, and eight were CBA studies. Most included cluster‐RCTs used households as the unit of randomization, though some used neighbourhoods, villages, or communities. Most CBA studies used villages or communities as the unit of allocation. The intervention period ranged from eight weeks to four years. The duration of the cluster‐RCTs (median seven months, range 9.5 weeks to 18 months) tended to be shorter than in the CBA studies (median 12 months, range two to 60 months). Studies of source‐based interventions were also longer (median 24 months, range eight weeks to two years) than those of POU interventions (median six months, range 9.5 weeks to 17 months).
Participants and settings
Nine studies included data only for children under five years of age, and three studies included data only on adults. The other studies enrolled and presented results for all ages of participants.
Most studies were undertaken in lower middle or low‐income countries based on World Bank criteria, but three studies were conducted in the USA (Colford 2002 USA; Colford 2005 USA; Colford 2009 USA), one in Australia (Rodrigo 2011 AUS), and one in Saudi Arabia (Mahfouz 1995 KSA). Five studies were conducted in urban settings (Semenza 1998 UZB; Colford 2002 USA; Colford 2005 USA; Colford 2009 USA; Rodrigo 2011 AUS), five in peri‐urban settings (Quick 1999 BOL; Quick 2002 ZMB; du Preez 2010 ZAF; Jain 2010 GHA; Peletz 2012 ZMB), two in urban informal or squatter settlements (Handzel 1998 BGD; Luby 2004), two in camps for refugees or displaced persons (Roberts 2001 MWI; Doocy 2006 LBR), five in multiple settings (URL 1995; Clasen 2005 COL; Stauber 2009 DOM; du Preez 2011 KEN; Boisson 2013 IND), and the others in villages or other rural settings.
Primary drinking water supply and sanitation facilities
The primary drinking water supply before the intervention was 'unimproved' in 30 studies, 'improved' in 15 studies, and 'unclear' or unreported in five studies. Sanitation facilities in trial settings were 'improved' in 12 studies, 'unimproved' in 15 studies, and 'unclear' or unreported in 19 studies. Access to a water source was deemed 'sufficient' in 14 studies, 'insufficient' in four studies, and 'unclear' or unreported in the remaining studies. The quantity of water available to study participants was considered 'sufficient' in eight studies, 'insufficient' in four studies, and 'unclear' in 43 studies.
Seventeen studies measured water quality before the introduction of the intervention as an indication of the ambient risk and the microbiological quality of the water consumed by the control group. Details on the indicators used varied among the studies (see Table 2). Thirty‐five studies measured colony‐forming units (CFUs) of thermotolerant coliforms, faecal coliforms, or E. coli, reporting geometric means, arithmetic means, number of CFUs/100 mL, mean faecal coliforms/100 mL, E. coli most probable number, median, or log10CFUs/100 mL. Other studies measured the frequency of samples containing such bacteria, or the CFU of total coliforms or other indicators of microbial contamination. None continually measured the microbiological performance of their interventions against the full range of bacterial, viral, and protozoan pathogens known to cause diarrhoea.
1
| Trial | Water quality indicator | Water quality post‐intervention: Intervention group | Water quality post intervention: Control group |
| Abebe 2014 ZAF | CFUs/100 mL | 0 | 80% of control HHs had 10 to 10000 |
| Austin 1993a GMB | Geometric mean CFUs/100 mL | 178 | 3020 |
| Austin 1993b GMB | Geometric mean CFUs/100 mL | 42 | 3020 |
| Boisson 2009 ETH | Arithmetic mean TTC/100 mL (95% CI) | 0 | 725.7 (621.0 to 830.4) |
| Boisson 2010 DRC | Geometric mean TTC/100 mL (95% CI) | 1.3 (0.9 to 1.7) | 173.7 (136.6 to 220.9) |
| Boisson 2013 IND | Geometric mean TTC/100 mL (95% CI) | 50 (44 to 57) | 122 (107 to 139) |
| Brown 2008a KHM | Geometric mean E. coli /100 mL | 17 | 600 |
| Brown 2008b KHM | Geometric mean E. coli /100 mL | 15 | 600 |
| Clasen 2004b BOL | Mean TTC/100 mL | 0.13 | 108 |
| Clasen 2004c BOL | Arithmetic mean TTC/100 mL | 100% of intervention households: 0 | 16% of control households: 0 66% > 10, 34% > 100, and 11% > 1000 |
| Clasen 2005 COL | Arithmetic mean TTC/100 mL (95% CI) | 37.3 (6.3 to 48.3) | 150.6 (34.8 to 166.4) |
| Colford 2002 USA; Colford 2005 USA; Colford 2009 USA | All water met FDA requirements | Not measured because of high water quality | Not measured because of high water quality |
| Crump 2005a KEN | Samples met WHO guidelines for water quality | 82% | 14% |
| Crump 2005b KEN | Samples met WHO guidelines for water quality | 78% | 14% |
| du Preez 2008 ZAF/ZWE | Samples met WHO guidelines for water quality | 57% | 30% |
| du Preez 2010 ZAF | E. coli in concentrations/100 mL | 62% | "No significant difference between intervention and control groups" |
| du Preez 2011 KEN | E. coli ln concentrations/100 mL | Storage containers: 0.723 SODIS bottles: ‐0.727 | Not reported |
| Fabiszewski 2012 HND | Geometric mean E. coli counts per 100 mL (95% CI) | 23.4 (20.2 to 27.0) | 45.4 (38.6 to 53.4) |
| Gasana 2002 RWA | Total coliforms/100 mL | Range: 3 to 43 | Range: 4 to 1100 |
| Gruber 2013 MEX | Samples with detectableE. coli | 43% | 59% |
| Günther 2013 BEN | E. coli contamination > 1000 CFU/100 mL | Not reported specifically; findings imply a 70% reduction in E. coli incidence for intervention households | |
| Handzel 1998 BGD | Stored water samples with E. coli 100 MPN/100 mL | 3% | 16% |
| Jain 2010 GHA | Samples with E. coli | 8% | 54% |
| Jensen 2003 PAK | Geometric mean E. coli /100 mL | 3 | 49 |
| Kirchhoff 1985 BRA | Mean number of faecal coliforms/dL in the samples | 70 | 16000 |
| Kremer 2011 KEN | Average reduction in log E. coli | ‐1.07, corresponding to a 66% reduction | |
| Lule 2005 UGA | Median E. coli CFU/100 mL | 23 | 59 |
| McGuigan 2011 KHM | Geometric mean CFU/100 mL | 6.8 | 48 |
| Mengistie 2013 ETH | Mean E. coli | 0 | 60 |
| Peletz 2012 ZMB | Geometric mean TTC/100 mL | Stored water: 3 | Stored water: 181 |
| Quick 1999 BOL | Median E. coli /100 mL | 0 | 6400 |
| Quick 2002 ZMB | Median E. coli /100 mL | 0 | 3 |
| Reller 2003a GTM | Samples with < 1 E. coli /100 mL (flocculant/disinfectant) | 40% | 7% |
| Reller 2003b GTM | Samples with < 1 E. coli /100 mL (flocculant/disinfectant+ vessel) | 57% | 7% |
| Reller 2003c GTM | Samples with < 1 E. coli /100 mL (bleach) | 51% | 7% |
| Reller 2003d GTM | Samples with < 1 E. coli /100 mL (bleach + vessel) | 61% | 7% |
| Semenza 1998 UZB | Faecal colonies/100 mL | 47 | 52 |
| Stauber 2009 DOM | E. coli MPN/100 mL | 11 | 19 |
| Stauber 2012a KHM | E. coli CFU/100 mL | 2.9 | 19.7 |
| Stauber 2012b GHA | Geometric mean E. coli MPN/100 mL (95% CI) | Direct filtrate 16 (13 to 20) Stored filtrate: 76 (62 to 91) | 490 (426 to 549) |
| Tiwari 2009 KEN | Geometric mean faecal coliforms/100 mL (95% CI) | 30.0 (21.3 to 42.1) | 88.9 (58.7 to 135) |
| URL 1995a GTM | Samples with fecal coliforms | 91% had 0 fecal coliforms | Not reported |
| URL 1995b GTM | Samples with fecal coliforms | 91% had 0 fecal coliforms | Not reported |
Abbreviations: E. coli: Escherichia coli; FC: faecal coliform.
Eight studies did not report actually having measured microbiological water quality at all (Alam 1989 BGD; Xiao 1997 CHN; Luby 2006; Mäusezhal 2009 BOL; Opryszko 2010; Majuru 2011 ZAF; Rodrigo 2011 AUS; Lindquist 2014). Thus, it cannot be concluded definitively that the interventions investigated in these studies actually resulted in an improvement in drinking water quality.
Among the eight studies investigating interventions to improve water quality at the point of distribution, only four tested microbiological water quality (Torun 1982 GTM; Gasana 2002 RWA; Jensen 2003 PAK; Kremer 2011 KEN). As these tests were at the source or point of distribution and not the POU, their results do not reflect possible post‐collection contamination.
Interventions
Eight studies evaluated source‐based interventions: improved wells or boreholes (Alam 1989 BGD; Xiao 1997 CHN; Opryszko 2010b AFG; Opryszko 2010c AFG) or improved community sources and distribution to public tap stands (Torun 1982 GTM; Gasana 2002 RWA; Jensen 2003 PAK; Kremer 2011 KEN; Majuru 2011 ZAF); none evaluated reliable piped‐in household connections.
Fourty‐seven studies evaluated POU interventions: chlorination (17 studies), filtration (20 studies), combined flocculation and disinfection (five studies), SODIS solar disinfection (six studies), combination UV disinfection and filtration (one study), and improved storage (two studies). Significantly, there were no eligible studies that investigated the impact of boiling, even though that is by far the most common type of POU water treatment (Rosa 2010).
Many studies provided a supplementary hygiene education or instruction beyond the use of the intervention itself, and among POU interventions the primary intervention was often combined with some form of improved storage. In only three multiple‐intervention arm studies did study authors establish different intervention groups with and without hygiene or other non‐water improvement steps in order to isolate the impact of water quality (URL 1995; Opryszko 2010; Lindquist 2014).
Except in blinded trials involving placebos, control arms generally continued to use their pre‐trial water supply and treatment practices. In one trial of POU chlorination plus a safe storage container, however, control households also received the container (Jain 2010 GHA). In two of the solar disinfection studies (Conroy 1996 KEN; Conroy 1999 KEN) both intervention and control households received plastic bottles for storing their drinking water. The intervention group was instructed to place the bottles on roofs to expose them to the sun, while the control group was told to keep the filled bottles indoors. It is important to note that since improved storage even in the absence of treatment has been shown to improve microbial water quality (Wright 2004), the comparison between the intervention and control in these studies may understate the effectiveness of the intervention when compared to the controls following customary water handling practices.
Adherence with the intervention
Studies of source water interventions tended to assume adherence based on the fact that the primary water supply had been improved. Some studies of POU water treatment undertook indirect assessments of adherence by measuring residual chlorine levels in stored water, comparing microbiological water quality of intervention and control groups, conducting periodic or post‐study surveys, or counting the amount of intervention product used. Most other studies measured adherence only by occasional observation, while eight cluster‐RCTs did not report on adherence.
The studies of chlorine residuals reported adherence ranging from a high of 95% (Doocy 2006 LBR) to a low of 11% (Opryszko 2010a AFG). Even among these studies, however, investigators acknowledged that it was not possible to know to what extent intervention group participants actually consumed treated water or avoided consuming untreated water. For those studies that reported on adherence, three took the additional step of investigating and reporting on continued consumption of untreated water (Boisson 2010 DRC; Peletz 2012 ZMB; Boisson 2013 IND) a source of exposure that could be masked by less direct metrics of adherence.
Outcome measures
The studies' main outcome measure was diarrhoeal disease, but different methods were used to define, assess, and report this. Thirty‐six studies used the WHO's definition of diarrhoea, while other studies used the following definitions: the mother's or respondent's definition (Austin 1993; Gasana 2002 RWA; Reller 2003; Crump 2005; Chiller 2006 GTM); 'watery diarrhoea as a component of gastroenteritis' (Colford 2002 USA; Colford 2005 USA; Colford 2009 USA; Rodrigo 2011 AUS); the local term (Conroy 1996 KEN; Conroy 1999 KEN; Boisson 2009 ETH); "significant change in bowel habits towards decreased consistency or increased frequency" (Kirchhoff 1985 BRA); or dysentery (du Preez 2010 ZAF; du Preez 2011 KEN). Four studies did not report the case definition used for diarrhoea (Torun 1982 GTM; Xiao 1997 CHN; Günther 2013 BEN; Lindquist 2014).
The method of diarrhoea surveillance and assessment also varied. In most cases, participants were visited on a periodic basis, either weekly (19 studies), fortnightly (16 studies), or more infrequently (14 studies). Participants were asked to recall and report on cases of diarrhoea during a previous period, usually seven days (30 studies) or 14 days (six studies), with four studies having recall periods of one to four days and one trial having a recall period of four weeks (Günther 2013 BEN). Twelve studies asked each participant or a designated householder to keep a log or record to indicate days with or without diarrhoea, one procured data on diarrhoea from family records and disease registries (Mahfouz 1995 KSA), or used paediatricians to assess the participants during regular medical checkups (Gasana 2002 RWA). Only one trial did not report the method (Xiao 1997 CHN).
Using these data, study authors reported diarrhoeal disease using one or more of the following epidemiological measures of disease frequency: incidence (34 studies); period prevalence (12 studies); and longitudinal prevalence (nine studies). The studies also reported other measures of disease, including incidence of persistent diarrhoea, gastrointestinal illness, including specific symptoms thereof, incidence or prevalence of bloody diarrhoea, and days of work or school lost due to diarrhoea (Lule 2005 UGA). Seven studies also reported on mortality (Crump 2005; Colford 2009 USA; Boisson 2010 DRC; du Preez 2011 KEN; Kremer 2011 KEN; Peletz 2012 ZMB; Boisson 2013 IND). None reported adverse events.
None of these studies were primarily designed to investigate the impact of the intervention on death, and as such most were underpowered to evaluate this outcome.
Data presentation
Forty‐three studies presented results both for children aged under five years (or a subgroup thereof) and for all ages or older age groups, three presented results only for adults, and nine presented results only for children under five years (or a subgroup thereof). Most of the studies adjusted raw data to account for possible covariates, including age, sex, sanitation or hygiene practices, area of residence, household income or proxies thereof, education or maternal literacy, age and occupation of the head of household, number of participants in the household or absent there from, baseline diarrhoea or conditions at baseline, or other variables associated with the household environment and participant behaviour.
Most studies of interventions at the POU also used statistical methods to adjust their results, either for repeated episodes of diarrhoea by the same participant or for clustering within the household, village or both. The studies that did not adjust for clustering may receive excess weight in meta‐analysis due to artificial precision (Kirchhoff 1985 BRA; Austin 1993; Mahfouz 1995 KSA; URL 1995).
Excluded studies
We excluded 108 studies for the reasons given in the Characteristics of excluded studies table. Two studies that appear to meet this review's inclusion criteria are currently ongoing (see Characteristics of ongoing studies).
Risk of bias in included studies
We have summarized our judgements about the risk of bias of included studies in Figure 2.
Risk of bias graph: summary of authors' judgements about each 'Risk of bias' item presented as percentages across all included studies.
Allocation
The allocation sequence was generated using an adequate method and classified as 'low risk' in 36 of the 45 cluster‐RCTs, 'high risk' in two, and 'unclear' in seven Figure 2. The method of allocation concealment was 'low risk' in 34 trials and 'high risk' in two and 'unclear' in nine.
Comparability of baseline characteristics (confounding bias)
All the quasi‐RCTs and CBA studies were judged to be at low risk of bias for this criteria except Gasana 2002 RWA, which was at 'unclear' risk.
Contemporaneous data collection
We judged all the quasi‐RCTs and CBA studies to be at low risk of bias for this criteria except Gasana 2002 RWA, which was at 'unclear' risk.
Blinding
Nine trials were blinded at the participant level (Kirchhoff 1985 BRA; Austin 1993; Colford 2002 USA; Colford 2005 USA; Colford 2009 USA; Boisson 2010 DRC; Jain 2010 GHA; Rodrigo 2011 AUS; Boisson 2013 IND); all but two of these were blinded at the assessor level as well (Kirchhoff 1985 BRA; Austin 1993). The others followed an open design, classified as 'high risk' of bias. One of the principal objectives of Colford 2002 USA was to assess the effectiveness of its blinding methodology; it therefore provides the most comprehensive analysis of these issues. Colford 2002 USA, Colford 2005 USA, Boisson 2010 DRC and Rodrigo 2011 AUS all used household sham water filters. Austin 1993, Kirchhoff 1985 BRA, Jain 2010 GHA and Boisson 2013 IND, which were assessing the effectiveness of home‐based chlorination, provided placebos to control households.
Incomplete outcome data
Twenty four studies were at 'low risk' of bias, 18 at 'high risk', and three studies were unclear.
Effects of interventions
See: Table 1
Summary of findings for the main comparison
| Point‐of‐use water quality interventions for preventing diarrhoea in rural settings in low‐ and middle‐income countries | |||||
| Patient or population: adults and children Settings: low‐ and middle‐income countries in rural areas Intervention: point of use water quality interventions Comparison: no intervention | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (trials) | Quality of the evidence (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| Diarrhoea episodes | No intervention | Chlorination | RR 0.77 (0.65 to 0.91) | 30,746 (14 trials) | ⊕⊕⊝⊝ low1,2,3,4 |
| 3 episodes per person per year | 2.3 episodes
(2.0 to 2.7) | ||||
| No intervention | Flocculation/disinfection | RR 0.69 (0.58 to 0.82) | 11,788 (4 trials) | ⊕⊕⊕⊝ moderate1,3,4,5,6 | |
| 3 episodes per person per year | 2.1 episodes (1.7 to 2.5) | ||||
| No intervention | Filtration | RR 0.48 (0.38 to 0.59) | 15,582 (18 trials) | ⊕⊕⊕⊝ moderate1,3,4,5 | |
| 3 episodes per person per year | 1.4 episodes (1.1 to 1.8) | ||||
| No intervention | Solar disinfection (SODIS) | RR 0.62 (0.42 to 0.94) | 3460 (4 trials) | ⊕⊕⊕⊝ moderate1,3,4,5 | |
| 3 episodes per person per year | 1.9 episodes (1.3 to 2.8) | ||||
| The assumed risk is taken from Fischer Walker 2012 and represents an estimated average for the incidence of diarrhoea in low‐ and middle‐income countries. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; RR: risk ratio. | |||||
| GRADE Working Group grades of evidence High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate. | |||||
1Downgraded by 1 for serious risk of bias: the outcome was measured as self‐reported episodes of diarrhoea, and is susceptible to bias as most studies were unblinded.
2Downgraded by 1 for serious inconsistency: statistical heterogeneity was very high with six out of fourteen trials having point estimates close to no effect. A subgroup analysis by adherence with the intervention (assessed by measurements of residual chlorine in drinking water) found larger effects in the studies with better adherence but the results remained inconsistent.
3No serious indirectness: these studies are mainly from low‐ and middle‐income countries, in settings with both improved and unimproved water sources and sanitation.
4No serious imprecision: The analysis is adequately powered to detect this effect.
5No serious inconsistency: The evidence of benefit is consistent across trials, but there is substantial statistical heterogeneity in the size of the effect.
6 This analysis excludes one additional study which found a much larger effect than seen in the other four trials and was considered an outlier (Doocy 2006 LBR).
Analysis 1: Any water quality intervention versus no intervention
Diarrhoea episodes
An overall pooled analysis, across different trial designs, interventions and settings, finds the risk of diarrhoea to be lower with any water quality intervention compared to no intervention, both among all ages (RR 0.59, 95% CI 0.51 to 0.69, 81215 participants; 52 studies Analysis 1.1), and under fives (RR 0.61, 95% CI 0.49 to 0.75 Analysis 1.2). However, as would be expected given the diverse nature of the trials, statistical heterogeneity between trials is very high (I² statistic = 98% and 97%, respectively). Our primary analysis is therefore stratified by the specific intervention type (for example, interventions at water source, POU chlorination, POU filtration), and by study design (for example, cluster‐RCT, quasi‐RCT, CBAs).
Mortality
Only nine studies reported any deaths among study participants. Five reported the number of deaths in each study arm without differences evident (see Table 3). Two studies reported the total number of deaths without stating how many occurred in each group (du Preez 2010 ZAF; Boisson 2013 IND), and two reported recording deaths but the numbers were not presented in the papers (Boisson 2009 ETH; Kremer 2011 KEN).
2
| Study ID | Intervention | Control | P value | Comment | ||
| Deaths | Participants | Deaths | Participants | |||
| Boisson 2010 DRC | 12 | 546 | 8 | 598 | 0.27 | — |
| Colford 2009 USA | 7 | 385 | 6 | 385 | > 0.05 | — |
| Crump 2005a KEN | 17 | 2249 | 28 | 2277 | 0.108 | — |
| Crump 2005b KEN | 14 | 2124 | 28 | 2277 | 0.052 | — |
| du Preez 2011 KEN | 3 | 555 | 3 | 534 | > 0.05 | — |
| Peletz 2012 ZMB | 3 | 300 | 6 | 299 | 0.28 | — |
| Boisson 2013 IND | ? | 6119 | ? | 5965 | — | Only reports total deaths (46) |
| du Preez 2010 ZAF | ? | 383 | ? | 335 | — | Only reports total deaths (7) |
| Kremer 2011 KEN | ? | — | ? | — | — | Reports recording deaths but does not state how many |
| Boisson 2009 ETH | ? | 731 | ? | 785 | — | Reports recording deaths but does not state how many |
None of these studies were primarily designed to investigate the impact of the intervention on mortality, and all were underpowered to investigate these effects.
Adverse events
No trial reported adverse events from the interventions.
Analysis 2: Interventions at the water source
One cluster‐RCT and five CBA studies evaluated interventions at the water source (Table 4). All but one study were from settings with 'unimproved' water sources (unprotected wells or surface water), and all had unclear levels of sanitation. Three studies evaluated improved wells or boreholes, two evaluated chlorination or filtration of community water sources, and one evaluated an improved community piped supply. No studies evaluated reliable household connections to a clean water source (see Table 5 and Table 6 for a description of study settings and interventions).
3
| Improved water source compared with no intervention for preventing diarrhoea in rural settings in low‐ and middle‐income countries | |||||
| Patient or population: adults and children Settings: low‐ and middle‐income countries in rural areas Intervention: water source improvement Comparison: no intervention | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (studies) | Quality of the evidence (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| No intervention | Water source improvement | ||||
| Diarrhoea episodes Cluster‐RCTs | 3 episodes per person per year | 3.7 episodes per person per year (2.9 to 4.7) | RR 1.24 (0.98 to 1.57) | 3266 (1 trial) | ⊕⊝⊝⊝ very low1,2,3 |
| Diarrhoea episodes CBA studies | — | — | — | 5895 (5 studies) | ⊕⊝⊝⊝ very low1,4,5 |
| The basis for the assumed risk (for example, the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; RR: risk ratio. | |||||
| GRADE Working Group grades of evidence High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate. | |||||
The assumed risk is based on 2.9 episodes/child year in 2010 (Fischer Walker 2012).
1Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants this outcome is susceptible to bias from lack of blinding. None of these studies blinded participants and outcome assessors to the treatment allocation.
2No serious inconsistency.
3Downgraded by 2 for serious indirectness: this single RCT from Afghanistan evaluated the provision of protected wells. It is not possible to make broad generalizations to other settings.
4Downgraded by 1 for serious inconsistency: statistical heterogeneity was very high (I² statistic = 98%), such that the data could not be pooled. Some large and statistically significant effects were seen in some individual trials, but not others.
5Downgraded by 1 for serious indirectness: these studies are from a variety of low‐ and middle‐income countries (Bangladesh, Rwanda, Pakistan, South Africa, China). However, as only single trials evaluated each intervention it is not possible to make broad generalizations.
4
| Study ID | Study design | Setting | Incidence of diarrhoea in the control group | Intervention areas | Control areas | ||
| Water source intervention | Health promotion activities | Water source | Health promotion activities | ||||
| Opryszko 2010b AFG | Cluster‐RCT | Rural villages | 3.1 episodes per person per year | One well per 25 households providing 25 litres/person/day | None | 35% used unprotected hand dug wells | None |
| Alam 1989 BGD | CBA | Rural villages | 4.1 episodes per child per year | Provision of one hand pump per 4‐6 households (3 times as many as control areas) | Female health visitors visited peoples homes and organised group discussion and demonstrations to promote hygienic practices for hand pump use, water storage, child faeces disposal, hand washing. | Shallow, hand‐dug wells; some hand pumps | None described |
| Gasana 2002 RWA | CBA | Rural villages | 3 episodes per child per year | Site A: Sedimentation tank/Katadyn filter with communal tap Site B: Gravel‐sand‐charcoal filter on existing water spring Site C: Protective fence around an existing water spring | None described | An existing water spring | None described |
| Jensen 2003 PAK | CBA | Rural villages | 2.8 episodes per person per year | Chlorination of public water supply | None described | Unchlorinated poorly functioning sand filter system | None described |
| Majuru 2011 ZAF | CBA | Rural villages | 0.6 episodes per person per year | Provision of intermittently operated small community water systems distributing potable water to multiple taps throughout the community | None described | Untreated water from a river and its tributaries | None described |
| Xiao 1997 CHN | CBA | Rural villages | Not reported | Improved water supply through structural improvements to wells | Hygiene education | Not reported | None described |
5
| Trial | Description | Source1 | Access to source2 | Quantity available3 | Ambient water quality | Sanitation4 |
| Alam 1989 BGD | Shallow, hand‐dug wells; some hand pumps | Unimproved | Unclear | Unclear | Not tested | Unclear |
| Gasana 2002 RWA | Spring | Unimproved | Unclear | Unclear | Baseline range 4 to 1100 total coliforms/100 mL | Unimproved |
| Jensen 2003 PAK | Some slow sand filters in poor condition; some household taps; majority used ground water | Improved | Unclear | Unclear | Baseline geometric mean in intervention village: 13.3 E. coli CFU/100 mL; control villages: 137/100 mL | Unclear |
| Majuru 2011 ZAF | Surface water, boreholes, water tankers | Improved and unimproved | Unclear | Unclear | Not tested | Unclear |
| Opryszko 2010 | 35% use unprotected dug wells | Unimproved | Sufficient | Sufficient | Not tested | Unclear |
| Xiao 1997 CHN | Well water | Unimproved | Unclear | Unclear | Not tested | Unclear |
1'Improved' includes household connection, public standpipe, borehole, protected dug well, protected spring, rainwater collection; 'unimproved' includes unprotected well, unprotected spring, vendor‐provided water, bottled water; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
2'Sufficient' means located within 500 m, queuing no more than 15 minutes, no more than three minutes to fill 20 L container, and maintained so available consistently; 'insufficient' means that it does not meet any of above; and 'unclear' means unclear or not reported; definition based minimum standards established by The Sphere Project 2011.
3'Sufficient' means a minimum of 15 L/day/person; 'insufficient' means less than 15 L/day/person; and 'unclear' means unclear or not reported; definition based on minimum standards established by The Sphere Project 2011.
4'Improved' means connection to a public sewer or septic system, pour flush latrine, simple pit latrine, or ventilated improved pit latrine; 'unimproved' means service or bucket latrine, public latrines, open latrines; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
The single cluster‐RCT from Afghanistan reported no statistically significant difference in diarrhoea with improved wells compared to no intervention (one trial, 3266 participants; Analysis 2.1; very low quality evidence).
Comparison 2 Source: water supply improvement versus control, Outcome 1 Diarrhoea: CBA studies subgrouped by age.
The CBA studies evaluated different interventions, had variable findings, and were all at unclear risk of multiple sources of bias (see Figure 3). Three of the five studies reported statistically significant effects on diarrhoea (Analysis 2.1; Analysis 2.2): in Bangladesh, provision of one hand pump per four to six households (three times as many as control areas) was associated with a small reduction in diarrhoea over three‐years follow‐up (RR 0.83, 95% CI 0.71 to 0.97); in remote areas in South Africa a new community piped water supply was associated with around a 50% reduction in diarrhoea compared to untreated river water (RR 0.43, 95% CI 0.24 to 0.77); and in China structural well improvements were also associated with around a 50% reduction in diarrhoea (RR 0.45, 95% CI 0.43 to 0.47). In contrast, chlorination and filtration of community water supplies were not associated with positive benefits in Rwanda and Pakistan respectively. Overall, the body of evidence is judged to be of very low quality (Table 4). Given the variability in interventions, further subgroup analyses to try to understand the heterogeneity were not useful.
Forest plot of comparison: 2 Source: water supply improvement versus control, outcome: 2.1 Diarrhoea: CBA studies subgrouped by age.
Analysis 3. POU chlorination
Fourteen cluster‐RCTs, with 16 comparisons, evaluated POU chlorination versus control. Chlorine was delivered to households free of charge every one to four weeks, with instructions on how to use it, and in eight trials a water storage container was also provided (see Table 7 and Table 8 for a description of study settings and interventions).
6
| Trial | Study design | Chlorination product? | Distributed free? | Frequency of distribution? | Storage container also distributed? | Compliance | Additional hygiene promotion |
| Austin 1993a GMB | Cluster‐RCT | Sodium hypochlorite solution | Yes | Fortnightly | No | 40% compliance measured by residual chlorine | None |
| Austin 1993b GMB | Cluster‐RCT | Sodium hypochlorite solution | Yes | Fortnightly | No | 59% compliance measured by residual chlorine | None |
| Boisson 2013 IND | Cluster‐RCT | Sodim dichloro‐isocyanurate tablets | Yes | Bimonthly | No | 32% compliance measured by residual chlorine | None |
| Crump 2005a KEN | Cluster‐RCT | 1% sodium hypochlorite | Yes | Weekly | No | 61% compliance during unannounced weekly visits measured by residual chlorine | Use of ORS, treatment seeking for diarrhoea |
| Handzel 1998 BGD | Cluster‐RCT | 0.25% to 0.3% chlorine solution | Yes | Weekly | Yes | 90% compliance based on residual chlorine measurements | Hygiene and sanitation messages |
| Jain 2010 GHA | Cluster‐RCT | Sodim dichloro‐isocyanurate tablets | Yes | Twice weekly | Yes | 74% to 89% compliance measured by chlorine residual | ORS provided to those with diarrhoea |
| Kirchhoff 1985 BRA | Cluster‐RCT | 10% sodium hypochlorite | Yes | Daily | No | Not reported | Chlorination preformed by study staff |
| Luby 2006a PAK | Cluster‐RCT | Sodium hypochlorite solution | Yes | Unclear | Yes | Yes, though rate unclear | Encouraged to only drink treated water |
| Lule 2005 UGA | Cluster‐RCT | 0.5% sodium hypochlorite | Yes | Weekly | Yes | Not reported | hygiene education |
| Mahfouz 1995 KSA | Cluster‐RCT | Packets of 50 g calcium hypochloride 70%. | Yes | Unclear | No | Some residual chlorine in all intervention samples | None |
| Mengistie 2013 ETH | Cluster‐RCT | 1.25% sodium hypochlorite solution | Yes | Weekly | No | 80% compliance measured by chlorine residual | None |
| Opryszko 2010c AFG | Cluster‐RCT | 0.05% sodium hypochlorite solution | Yes | Monthly | Yes | 78% compliance measured by previous 2 weeks self‐report use of chlorine | None |
| Quick 1999 BOL | Cluster‐RCT | MIOX unit electrolytically produced disinfectant with 3% brine solution, hypochlorite, chlorine dioxide, ozone, peroxide and other oxidants. | Yes | Weekly | Yes | 63% compliance measured by water in vessel with chlorine residual, average across six rounds | Community health volunteers reinforced messages about proper use of the disinfectant and vessels and of different applications for treated water. |
| Reller 2003b GTM | Cluster‐RCT | Sodium hypochlorite solution (50,000 ppm) | Yes | Monthly | No | 36% compliance measure by residual chlorine > 0.1 mg/L on unannounced visits. | Motivational and educational messages about chlorination, use of ORS, care seeking for diarrhoea |
| Reller 2003c GTM | Cluster‐RCT | Sodium hypochlorite solution (50,000 ppm) | Yes | Monthly | Yes | 44% compliance measure by residual chlorine > 0.1 mg/L on unannounced visits. | Motivational and educational messages about chlorination, use of ORS, care seeking for diarrhoea |
| Semenza 1998 UZB | Cluster‐RCT | 1.5% chlorine solution | Yes | Unclear but households were visited twice weekly | Yes | 73% based on residual chlorine levels at time of visit | Only drink chlorinated water and wash all fruit and vegetables with chlorinated water |
| Luby 2004a PAK | CBA | Bleach (sodium hypochlorite) | Yes | Study workers visited weekly and re‐supplied the households with dilute bleach. | Yes | Not reported | Encouraged regular treatment of drinking water |
| Luby 2004b PAK | CBA | Bleach (sodium hypochlorite) | Yes | Study workers visited weekly and re‐supplied the households with dilute bleach. | Yes | Not reported | Encouraged regular treatment of drinking water |
| Quick 2002 ZMB | CBA | 0.5% sodium hypochlorite | Yes | Unclear but households were visited once every two weeks | HHs paid for vessel | 72% compliance measured by water in vessel with chlorine residual | Community volunteers, gave education about causes and prevention of diarrhoea and safe storage of water and motivated households about the intervention. |
7
| Trial | Description | Source1 | Access to source2 | Quantity available3 | Ambient water quality | Sanitation4 |
| Austin 1993 | Open wells | Unimproved | Sufficient | Unclear | Mean 1871 FC/100 mL in wells; among stored water samples: mean 3358 FC/100 mL in rainy season, 1014 FC/100 mL in dry season | Unclear |
| Boisson 2013 IND | 62% unprotected dug well, 17% tubewell, 14% tap, 5% surface water | Unimproved | Unlcear | Unclear | Baseline not reported. Control households: Geometric mean 122 TTC/100 mL | Unimproved |
| Crump 2005 | 50% ponds, 49% rivers | Unimproved | Unclear | Insufficient | Baseline mean 98 E. coli /100 mL | Unclear; 33% defecate on ground |
| Handzel 1998 BGD | 48% tap, 52% tubewell; 61% paid for drinking water | Improved | Sufficient | Sufficient | Baseline geometric mean 138.1 faecal coloform counts/100 mL | Unimproved |
| Jain 2010 GHA | 95% of households use tap, 84% surface water, 46% wells, 35% rainwater, 25% borehole | Improved and unimproved | Unclear | Unclear | Baseline: median E. coli MPN 93/100 mL | Unimproved |
| Kirchhoff 1985 BRA | Pond water stored in clay pots after filtering with cloth | Unimproved | Unclear | Insufficient | Source water: mean 970 faecal coliforms/100 mL | Unimproved |
| Luby 2004 | Tanker trucks, municipal taps (household and community level) | Mostly unimproved | Unclear | Unclear | Baseline: approximately 60% of stored drinking water samples were free of E. coli | Improved |
| Luby 2006 | Tanker trucks, municipal taps (household and community level), water bearer, boreholes | Mostly improved | Unclear | Unclear | Not tested | Improved |
| Lule 2005 UGA | 16% surface or shallow wells, 50% protected springs, 49% boreholes or taps | Unimproved | Sufficient | Sufficient | Source mean E. coli counts: 11/100 mL | Improved |
| Mahfouz 1995 KSA | Shallow wells | Unimproved | Unclear | Unclear | Source: 92% positive with E. coli; precise level not reported | Improved |
| Mengistie 2013 ETH | 50% well, 41% spring, 9% river | Unimproved | Unclear | Unclear | Baseline: E. coli MPN 70/100 mL | Unimproved |
| Opryszko 2010 | 35% use unprotected dug wells | Unimproved | Sufficient | Sufficient | Not tested | Unclear |
| Quick 1999 BOL | Shallow uncovered wells; 38% treated water | Unimproved | Unclear | Unclear | Source water: median colony count E. coli: 57,050/100 mL | Unimproved, but 47% used latrine |
| Quick 2002 ZMB | Shallow wells; some boiling | Unimproved | Unclear | Unclear | Source water: median colony count E. coli: 34/100 mL | Unclear |
| Reller 2003 | Surface water from shallow wells, rivers and springs | Unimproved | Unclear | Unclear | Baseline drinking water: median colony count E. coli 63/100 mL | Unclear |
| Semenza 1998 UZB | Households without piped water (procured from street tap, neighbour tap, well, vendor, or river) | Unimproved | Unclear | Unclear | Source water: 54 coliform colonies/100 mL | Unclear |
1'Improved' includes household connection, public standpipe, borehole, protected dug well, protected spring, rainwater collection; 'unimproved' includes unprotected well, unprotected spring, vendor‐provided water, bottled water; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
2'Sufficient' means located within 500 m, queuing no more than 15 minutes, no more than three minutes to fill 20 L container, and maintained so available consistently; 'insufficient' means that it does not meet any of above; and 'unclear' means unclear or not reported; definition based minimum standards established by The Sphere Project 2011.
3'Sufficient' means a minimum of 15 L/day/person; 'insufficient' means less than 15 L/day/person; and 'unclear' means unclear or not reported; definition based on minimum standards established by The Sphere Project 2011.
4'Improved' means connection to a public sewer or septic system, pour flush latrine, simple pit latrine, or ventilated improved pit latrine; 'unimproved' means service or bucket latrine, public latrines, open latrines; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
On average, POU chlorination in cluster RCTs reduced the risk of diarrhoea episodes by around a quarter, both for all ages (RR 0.77, 95% CI 0.65 to 0.91; 14 trials, 30,746 participants; Analysis 3.2) and for children under five years of age (RR 0.77, 95% CI 0.64 to 0.92; Analysis 3.2). However, there was substantial heterogeneity in the size of the effect which was not well explained by a series of subgroup analyses (Analysis 3.2 to Analysis 3.9).
Comparison 3 POU: water chlorination versus control, Outcome 2 Diarrhoea: cluster‐RCTs: subgrouped by age.
Comparison 3 POU: water chlorination versus control, Outcome 9 Diarrhoea: cluster‐RCTs; subgrouped by length of follow‐up.
As might be expected from an effective intervention, the trials finding larger effects from chlorination tended to be those where adherence with the intervention was higher (as measured by residual chlorine) (Analysis 3.3; Figure 4), but in the four trials which had adequate blinding no effects of water chlorination were seen (Analysis 3.4). A subgroup analysis looking at interventions with and without the provision of water storage containers did not find statistical evidence of subgroup differences (Analysis 3.5). Effects were seen in trials with 3, 6, and 12 months of follow‐up, but no effect was demonstrated in the two trials with follow‐up longer than 12 months (Analysis 3.9). The funnel plot for this comparison has some asymmetry which may be the result of publication bias (see Figure 5). The overall quality of the evidence was therefore judged to be low (Table 9).
Forest plot of comparison: 3 POU: water chlorination versus control, outcome: 3.3 Diarrhoea: cluster‐RCTs; subgrouped by adherence.
Funnel plot of comparison: 3 POU: water chlorination versus control, outcome: 3.1 Diarrhoea: subgrouped by study design.
8
| POU chlorination compared with no intervention for preventing diarrhoea | |||||
| Patient or population: adults and children Settings: low‐ and middle‐income countries Intervention: distribution of chlorine for POU water treatment and instruction on use Comparison: no intervention | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (studies) | Quality of the evidence (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| No intervention | POU Chlorination | ||||
| Diarrhoea episodes cluster‐RCTs | 3 episodes per person per year | 2.3 episodes per year
(2.0 to 2.7) | RR 0.77 (0.65 to 0.91) | 30,746 (14 trials) | ⊕⊕⊝⊝ low1,2,3,4 |
| Diarrhoea episodes
CBA studies | 3 episodes per person per year | 1.5 episodes per year
(1.0 to 2.3) | RR 0.51 (0.34 to 0.75) | 3948 (2 studies) | ⊕⊝⊝⊝ very low5,6,7,8 |
| The basis for the assumed risk is provided in the footnotes. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; RR: risk ratio. | |||||
| GRADE Working Group grades of evidence High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate. | |||||
The assumed risk is based on 2.9 episodes/child year in 2010 (Fischer Walker 2012).
1Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants this outcome is susceptible to bias from lack of blinding. Only two of these studies blinded participants and outcome assessors to the treatment allocation, and these two studies found no evidence of an effect with chlorination.
2Downgraded by 1 for serious inconsistency: statistical heterogeneity was very high (I² statistic = 91%). In a subgroup analysis by compliance with the intervention (assessed by measurements of residual chlorine in drinking water) found larger effects in the studies with better compliance.
3No serious indirectness: these studies are mainly from low‐ and middle‐income countries (the Gambia, India, Kenya, Bangladesh, Ghana, Brazil, Pakistan,Uganda, Saudi Arabia, Ethiopia, Afghanistan, Bolivia, Guatemala, and Uzbekistan). The interventions consisted of free distribution of chlorine (every one to four weeks) plus instructions on how to use it. In some cases, the intervention included hygiene education and storage containers in which to treat and store water.
4No serious imprecision: the average effect suggests POU chlorination may reduce diarrhoea episodes by about a quarter. The analysis is adequately powered to detect this effect.
5Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants this outcome is susceptible to bias from lack of blinding. None of these studies blinded participants and outcome assessors to the treatment allocation.
6Downgraded by 1 for serious inconsistency: statistical heterogeneity was very high (I² statistic = 63%).
7Downgraded by 1 for serious indirectness: there are only two studies (three comparisons) from Pakistan and Zambia.
8No serious imprecision.
Comparison 3 POU: water chlorination versus control, Outcome 3 Diarrhoea: cluster‐RCTs; subgrouped by adherence.
Comparison 3 POU: water chlorination versus control, Outcome 4 Diarrhoea: cluster‐RCTs by risk of bias by blinding of participants.
Comparison 3 POU: water chlorination versus control, Outcome 5 Diarrhoea: cluster‐RCTs; subgrouped by additional water storage intervention.
An additional two CBA studies evaluated POU chlorination but only provide very low quality evidence of any effect (Analysis 3.1, Table 9).
Analysis 4. POU combined flocculation and disinfection
Five cluster‐RCTs from low‐income settings evaluated interventions where sachets of flocculant and disinfectant were distributed to households to treat water from unimproved sources (three trials), improved sources (one trial), and unclear sources (one trial). Four trials also provided water containers and mixing equipment (see Table 10 and Table 11 for a description of study settings and interventions). None of the trials blinded the outcome assessment.
9
| Study ID | Study design | Setting | Intervention areas | Control areas | |||
| Water quality intervention | Health promotion activities | Compliance | Water source | Health promotion activities | |||
| Chiller 2006 GTM | Cluster‐RCT | Rural villages | Provided households with a large spoon and a wide‐mouthed bucket for mixing, a narrow‐topped vessel with a lid for storing treated water and provided households with sachets of the flocculant–disinfectant every week | None | 44% compliance measured by residual chlorine at week 10 of study | 31% tap, 40% river or spring and 25% well. | None |
| Crump 2005b KEN | Cluster‐RCT | Rural villages | Each week households were given sachets of the flocculant–disinfectant | None | 44% compliance during unannounced weekly visits measured by residual chlorine | 50% pond, 49% river and 2% spring | None |
| Doocy 2006 LBR | Cluster‐RCT | Liberian camps for displaced persons | Households received a bucket and large mixing spoon for preparation, a decanting cloth, a funnel and a storage container with a narrow opening and lid. Each household received a maximum of 21 flocculation–disinfectant packets per week | None | 85% compliance based on residual chlorine sampling | Received a funnel and an identical storage container | None |
| Luby 2006b PAK | Cluster‐RCT | Squatter settlements | Provided households with flocculant‐disinfectant sachets, a water vessel and soap. Weekly distributions of sachets | Field workers educated neighbourhoods about health problems resulting from hand and water contamination and instructed households on how and when to wash hands | Yes, though rate unclear | Municipal supply at household (33%), at community tap (37%), tanker truck (12%), water bearer (13%) and tube well (5%) | None |
| Luby 2006c PAK | Cluster‐RCT | Squatter settlements | Flocculant‐disinfectant and vessel. Weekly distributions of sachets | Field workers educated neighbourhoods about health problems resulting from hand and water contamination | Yes, though rate unclear | Municipal supply at household (33%), at community tap (37%), tanker truck (12%), water bearer (13%) and tube well (5%) | None |
| Reller 2003a GTM | Cluster‐RCT | Rural villages | Weekly distribution of flocculant‐disinfectant and gave 2 cloths initially, which could be exchanged | Field workers discussed the importance of water treatment and demonstrated the water preparation process | 27% compliance measure by residual chlorine > 0.1 mg/L on unannounced visits. | 33% tap, 46% river or spring, 21% well. | None |
| Reller 2003d GTM | Cluster‐RCT | Rural villages | Weekly distribution of flocculant‐disinfectant and gave 2 cloths initially, which could be exchanged and received a large plastic spoon for stirring, a large‐mouthed bucket for mixing, and a vessel with a secure lid and a spigot for storing treated water | Field workers discussed the importance of water treatment and demonstrated the water preparation process | 34% compliance measure by residual chlorine > 0.1 mg/L on unannounced visits. | 33% tap, 46% river or spring, 21% well. | None |
10
| Trial | Description | Source1 | Access to source2 | Quantity available3 | Ambient H2O quality | Sanitation4 |
| Chiller 2006 GTM | Rivers, springs, taps, and wells | Unclear | Unclear | Sufficient | 98% of source samples contained E. coli; precise level not reported | Mostly unimproved |
| Crump 2005b KEN | 50% ponds, 49% rivers | Unimproved | Unclear | Insufficient | Baseline mean 98 E. coli /100 mL | Unclear; 33% defecate on ground |
| Doocy 2006 LBR | Surface sources and some tap stands | Unimproved | Unclear | Insufficient | Source water: 88% samples tested positive for faecal contamination; precise level not reported | Unimproved |
| Luby 2006b PAK | Tanker trucks, municipal taps (household and community level), water bearer, boreholes | Mostly improved | Unclear | Unclear | Not tested | Improved |
| Reller 2003a GTM | Surface water from shallow wells, rivers and springs | Unimproved | Unclear | Unclear | Baseline drinking water: median colony count E. coli 63/100 mL | Unclear |
1'Improved' includes household connection, public standpipe, borehole, protected dug well, protected spring, rainwater collection; 'unimproved' includes unprotected well, unprotected spring, vendor‐provided water, bottled water; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
2'Sufficient' means located within 500 m, queuing no more than 15 minutes, no more than three minutes to fill 20 L container, and maintained so available consistently; 'insufficient' means that it does not meet any of above; and 'unclear' means unclear or not reported; definition based minimum standards established by The Sphere Project 2011.
3'Sufficient' means a minimum of 15 L/day/person; 'insufficient' means less than 15 L/day/person; and 'unclear' means unclear or not reported; definition based on minimum standards established by The Sphere Project 2011.
4'Improved' means connection to a public sewer or septic system, pour flush latrine, simple pit latrine, or ventilated improved pit latrine; 'unimproved' means service or bucket latrine, public latrines, open latrines; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
Four of the five trials found statistically significant reductions in diarrhoea with the intervention (Table 12), but statistical heterogeneity in the size of this effect made pooling the data difficult (I² statistic = 99%; Analysis 4.1). This heterogeneity relates to one trial from Liberia IDP camps, Doocy 2006 LBR, where the flocculation and disinfection kits reduced diarrhoea by 88% (RR 0.12, 95% CI 0.11 to 0.13; one trial, 2191 participants). Exclusion of this potential outlier finds a more modest effect with the other four trials both for all ages (RR 0.69, 95% CI 0.58 to 0.82; four trials, 11788 participants; Analysis 4.2) and for children under five years of age (RR 0.71, 95% CI 0.61 to 0.84; Analysis 4.2).
11
| POU water flocculation and disinfection compared with no intervention for preventing diarrhoea | |||||
| Patient or population: adults and children Settings: low‐ and middle‐income countries Intervention: distribution of sachets combining water flocculation and disinfection and instructions on use Comparison: no intervention | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (studies) | Quality of the evidence (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| No intervention | Water flocculation and disinfection | ||||
| Diarrhoea episodes Cluster‐RCTs | 3 episodes per person per year | 2.1 episodes per person per year (1.7 to 2.5) | RR 0.69 (0.58 to 0.82) | 11,788 (4 trials) | ⊕⊕⊕⊝ moderate1,2,3,4 |
| The basis for the assumed risk is provided in the footnotes. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; RR: risk ratio. | |||||
| GRADE Working Group grades of evidence High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate. | |||||
The assumed risk is based on 2.9 episodes/child year in 2010 (Fischer Walker 2012).
1Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants this outcome is susceptible to bias from lack of blinding. None of these studies blinded participants and outcome assessors to the treatment allocation.
2No serious inconsistency: In the complete analysis of five trials statistical heterogeneity was very high (I² statistic = 99%). However, this heterogeneity was related to a single trial showing very large effects conducted in an emergency setting in Liberia possibly due to epidemic diarrhoea. When this trial was removed as an outlier, there was a smaller, but more consistent effect.
3No serious indirectness: the studies were conducted in rural areas in Guatemala (two studies), and Kenya (one study), one trial was from a camp for displaced persons in Liberia and one from squatter settlements in Pakistan. Sanitation was improved in only one of these studies.
4No serious imprecision: all five studies found benefits with flocculation. The 95% CI of the pooled effect includes the possibility of no effect, but this imprecision is a result of the heterogeneity between studies.
Comparison 4 POU: flocculation and disinfection versus control, Outcome 1 Diarrhoea: cluster‐RCTs.
Comparison 4 POU: flocculation and disinfection versus control, Outcome 2 Diarrhoea: cluster‐RCTs: subgrouped by age; excluding Doocy 2006 LBR.
Adherence with the intervention, as measured by residual chlorine, was generally low (< 50%), but higher in the trial from Liberia showing large effects (Analysis 4.3). Larger effects tended to also be seen in the trials also providing water storage containers (Analysis 4.4). The effects were present in trials with both improved and unimproved water source and sanitation (Analysis 4.5; Analysis 4.6; Analysis 4.7). None of the trials had follow‐up longer than 12 months (Analysis 4.8).
Comparison 4 POU: flocculation and disinfection versus control, Outcome 3 Diarrhoea: cluster‐RCTs: subgrouped by adherence.
Comparison 4 POU: flocculation and disinfection versus control, Outcome 4 Diarrhoea: cluster‐RCTs: subgrouped by additional storage container.
Comparison 4 POU: flocculation and disinfection versus control, Outcome 5 Diarrhoea: cluster‐RCTs: subgrouped by sufficiency of water quantity.
Comparison 4 POU: flocculation and disinfection versus control, Outcome 6 Diarrhoea: cluster‐RCTs: subgrouped by water source.
Comparison 4 POU: flocculation and disinfection versus control, Outcome 7 Diarrhoea: cluster‐RCTs: subgrouped by sanitation level.
Analysis 5. POU filtration
Overall 20 cluster‐RCTs evaluated POU filtration: ceramic filtration (nine trials), biosand filtration (five trials), LifeStraw® filters (three trials), and plumbed‐in filtration (three trials) (see Table 13 and Table 14 for a description of study settings and interventions).
12
| Study ID | Intervention sub‐group | Study design | Setting | Intervention areas | Control areas | |||
| Water quality intervention | Health promotion activities | Compliance | Water source | Health promotion activities | ||||
| Abebe 2014 ZAF | Ceramic filter | Cluster‐RCT | Rural | Ceramic water filter impregnated with silver nanoparticles with safe storage containers | Education about safe water and hygiene and information on how to use the filter and maintain it. | Not reported | Personal tap in home (44%), community tap (44%) and river (3%) | Received usual clinical care including education about safe water and hygiene at the clinic |
| Brown 2008a KHM | Ceramic filter | Cluster‐RCT | Rural | CWP (Cambodian Ceramic Water Purifier) including safe storage container. | None | 98% compliance measured by self‐report | Surface water (55%) and ground water (48%) during the dry season and surface water (45%), ground water (48%) and rain water (73%) during the rainy season | None |
| Brown 2008b KHM | Ceramic filter | Cluster‐RCT | Rural | CWP‐Fe (iron‐rich ceramic water purifier) including safe storage container. | None | 98% compliance measured by self‐report | Surface water (55%) and ground water (48%) during the dry season and surface water (45%), ground water (48%) and rain water (73%) during the rainy season | None |
| Clasen 2004b BOL | Ceramic filter | Cluster‐RCT | Rural | Ceramic filters including improved storage | None | 67% of households had filters in regular use | 68% had taps and 11% boiled water. | None |
| Clasen 2004c BOL | Ceramic filter | Cluster‐RCT | Rural | Ceramic filters including improved storage | None | 100% of intervention households' water free of TTC | Water from canal (52%), river (35%) or rainwater (4%) | None |
| Clasen 2005 COL | Ceramic filter | Cluster‐RCT | Rural and urban affected by conflict | Ceramic water filter system including improved storage | None | Not reported | River (27.6%), rainwater(12.1%), yard tap (67.2%). 70.7% claimed to treat water. | None |
| du Preez 2008 ZAF/ZWE | Ceramic filter | Cluster‐RCT | Rural | Ceramic filters including improved storage | None | 55% compliance measured by water quality (approximate compliance across intervention households in Zimbabwe and South Africa). | Protected water source (53.8%) and unprotected water source (46.2%) | None |
| Lindquist 2014a BOL | Ceramic filter | Cluster‐RCT | Peri‐urban | Received a PointONE Filter and a 30 L bucket (with lid) | Participants were instructed on diarrhoeal transmission (biological versus cultural beliefs‐based), prevention and treatment. | 97% compliance based on reported use | 83% used water from tanker trucks and 12% from water coolers. | Received weekly messages on life skills and attitudes. Also were instructed on diarrhoeal transmission, prevention and treatment. |
| Lindquist 2014b BOL | Ceramic filter | Cluster‐RCT | Peri‐urban | Received a PointONE Filter and a 30‐L bucket (with lid) and WASH education | Participants received weekly WASH messages on personal and family hygiene, sanitation, boiling and chlorine‐based water treatments (excluding filtration),vitamin A, hygienic food preparation and cleaning, and parasite prevention. | 90% compliance based on reported use | 83% used water from tanker trucks and 12% from water coolers. | Received weekly messages on life skills and attitudes. Also were instructed on diarrhoeal transmission, prevention and treatment. |
| URL 1995a GTM | Ceramic filter | Cluster‐RCT | Rural | Handmade ceramic water filter | None | 87% to 93% use of filter by children | Majority of households collected water from household tap (not chlorinated) | None |
| URL 1995b GTM | Ceramic filter | Cluster‐RCT | Rural | Handmade ceramic water filter | Education on nutrition (ORS, basic nutrition and maternal and child nutrition), health (hygiene) and family values. | As above | Majority of households collected water from household tap (not chlorinated) | None |
| Fabiszewski 2012 HND | Sand filtration | Cluster‐RCT | Rural | Hydraid plastic‐housing BioSand filter (BSF) + 20 L water jug | Training for the use and maintenance of the BSF and general education about hygiene and sanitation. | Not reported | Among all study participants‐ the main source of drinking water were: protected water sources (49% to 69% households per month), protected sources (24% to 50% per month), piped water (1% to 11% per month), and rainwater (0% to 2% per month). | Training for the use and maintenance of the BSF and general education about hygiene and sanitation. |
| Stauber 2009 DOM | Sand filtration | Cluster‐RCT | Semi‐rural and urban | Received a biosand filter and safe storage container | Nothing | Water quality testing, however no intervention household level compliance reported | 42% reported treating drinking water. | None |
| Stauber 2012a KHM | Sand filtration | Cluster‐RCT | Rural | Plastic biosand filter. HHs were asked to pay USD 10 for the filter. | Health and hygiene education sessions | 89% compliance measured by household‐reported use at least 3 times per week | Improved water sources during the dry season (7.1%) and during the rainy season (88.9%). 49.5% reported boiling drinking water. | Health and hygiene education sessions |
| Stauber 2012b GHA | Sand filtration | Cluster‐RCT | Rural | Plastic biosand filter | Not specified | 97% compliance measured by household‐reported use | Use surface water during dry season (95%) and use surface water during rainy season (70.6%). 96.5% reported sieving drinking water through cloth. | nothing |
| Tiwari 2009 KEN | Sand filtration | Cluster‐RCT | Rural | Provided with the concrete BioSand Filter | At each visit, three oral rehydration packets and instructions were provided. | Not reported | All control houses reported drinking river or unprotected spring water; drink rainwater (96.6%), drink improved source (24.1%). 34.5% reported boiling drinking water. | At each visit, three oral rehydration packets and instructions were provided. |
| Boisson 2009 ETH | LifeStraw® Personal | Cluster‐RCT | Rural | A LifeStraw® personal pipe‐style water treatment device was given to each member of the household >6 months and encouraged to use it at home and away from home. | None | 13% report use today | The primary drinking water source for 84% was from spring, 12% from rivers, 2.5% from hand dug wells and 4% from communal taps. | None |
| Boisson 2010 DRC | LifeStraw® Family | Cluster‐RCT | Rural | Households received a LifeStraw® Family filters | None | 76% compliance measured by self‐report use today or yesterday (at 14 month follow‐up) | Received a placebo filter. | None |
| Peletz 2012 ZMB | LifeStraw® Family | Cluster‐RCT | Peri‐urban | Households received a LifeStraw® Family filter and two 5 L safe storage containers. | None | 87% compliance measured by improved water quality | 46% use unprotected dug wells, 19% boreholes, 17% public standpipes, 12% protected dug well, 5% piped into home or yard and 2% surface water. | None |
| Colford 2002 USA | Plumbed in filter | Cluster‐RCT | Urban | Installation of water treatment devices to 1 tap in HH that include: a 1‐micron absolute prefilter cartridge and a UV lamp. | None | 96% compliance measured by not dropping out of study (plumbed‐in unit) | Sham device | None |
| Colford 2005 USA | Plumbed in filter | Cluster‐RCT | Urban | Installation of filter (1‐micron filter and a UV lamp) to main faucet of household | All participants received the current CDC safe drinking water guidelines for immuno‐compromised persons | 90% compliance measured by not dropping out of study (filter attached to kitchen sink) | Sham device | All participants received the current CDC safe drinking water guidelines for immuno‐compromised persons |
| Colford 2009 USA | Plumbed in filter | Cluster‐RCT | Urban | Installation of filter (1‐micron filter and a UV lamp) to main faucet of household | None | 83% compliance measured by not dropping out of study (filter attached to kitchen sink) | Sham device | None |
| Rodrigo 2011 AUS | Ceramic filter/plumbed in | Cluster‐RCT | Urban | Bench‐top silver impregnated ceramic water treatment units, which required participants to use fill it but then households that had rainwater piped into kitchen were offered an under sink unit | None | Not reported | Sham water treatment unit | None |
13
| Trial | Description | Source1 | Access to source2 | Quantity available3 | Ambient H2O quality | Sanitation4 |
| Abebe 2014 ZAF | In‐home taps or community taps | Improved | Sufficient | Unclear | 80% of households had contamination between 10 to 10000 CFUs/100 mL | Unclear |
| Brown 2008 | 62% households rely on surface water during dry season and 55% rely on surface water during rainy season | Unimproved | Unlcear | Unclear | Baseline not reported. Control households: Geometric mean 600 E. coli /100 mL | Improved |
| Clasen 2004b BOL | 80% yard taps supplied by untreated surface source, 20% directly from untreated surface sources | 80% improved, 20% unimproved | Sufficient | Sufficient | Baseline arithmetic mean 86 TTC/100 mL | Unimproved |
| Clasen 2004c BOL | Irrigation canals and other surface sources | Unimproved | Sufficient | Sufficient | Baseline arithmetic mean 797 TTC/100 mL | Unimproved |
| Clasen 2005 COL | 67% yard tap from municipality (not treated), 28% river, 12% rainwater | Unimproved | Unclear | Unclear | Baseline not reported. Control households: arithmetic mean 151 TTC/100 mL | Mostly improved |
| du Preez 2008 ZAF/ZWE | Protected wells | Improved | Sufficient | Unclear | Baseline not reported. Control households: 30% samples post‐intervention met WHO guidelines for water quality | Improved |
| Lindquist 2014 | Municipal supply | Improved | Sufficient | Unclear | Not tested | Unimproved |
| URL 1995 | Household tap (27%), public tap (21%), well (23%) | Improved | Unclear | Unclear | Range 5 to 260; average 106 faecal coliforms/100 mL across three sites. | Improved |
| Fabiszewski 2012 HND | 49% to 69% households use unprotected sources, 24% to 50% use protected sources, 1% to 11% piped water, 0% to 2 % rainwater | Improved and unimproved | Unclear | Unclear | Geometric mean E. coli concentrations of both unprotected and protected sources were > 100 MPN/100 mL | Unimproved |
| Stauber 2009 DOM | Unclear | Unclear | Unclear | Unclear | Baseline: geometric mean 21 MPN E. coli /100 mL | Improved |
| Stauber 2012a KHM | 77% used improved water source during dry season, 89% during rainy season | Improved | Unclear | Unclear | Baseline: geometric mean 27.5 CFU/100 mL | Unimproved |
| Stauber 2012b GHA | Surface water 70% in dry season, 95% in rainy season | Unimproved | Unclear | Unclear | Baseline: geometric mean 792 or 832 E. coli /100 mL for control and intervention households, respectively | Unimproved |
| Tiwari 2009 KEN | Primarily river water; 27% drink protected sources | Unimproved | Unclear | Unclear | Baseline not reported. Control households: 88.9 faecal coliforms/100 mL | Unclear |
| Boisson 2009 ETH | 84% springs, 12% river, 2% handdug well, 4% communal tap | Unimproved | Unclear | Unclear | Baseline arithmetic mean 449 TTC/100 mL | Unimproved |
| Boisson 2010 DRC | 97% surface water, 38% rainwater, 16% springs | Unimproved | Unclear | Unclear | Source drinking water: 75% of household samples > 1000 TTC/100 mL | Unimproved |
| Peletz 2012 ZMB | 46% unprotected dug wells, 22% taps, 16% borehole or protected dug well, 2% surface water | Improved and unimproved | Unclear | Unclear | Unfiltered water: Geometric mean 190 TTC/100 mL | Unimproved |
| Colford 2002 USA | Household taps supplied by municipal water treatment | Improved | Sufficient | Sufficient | Data from water treatment plant: met US federal and California drinking water standards | Improved |
| Colford 2005 USA | Household taps supplied by municipal water treatment | Improved | Sufficient | Sufficent | Data from water treatment plant: met US federal drinking water standards | Improved |
| Colford 2009 USA | Household taps supplied by municipal water treatment | Improved | Sufficient | Sufficient | Data from water treatment plant: met US federal drinking water standards | Improved |
| Rodrigo 2011 AUS | Untreated rainwater | Improved | Sufficient | Sufficient | Not tested | Improved |
Abbreviations: TTC: thermotolerant coliforms, MPN: most probable number, CFU: colony‐forming units
1'Improved' includes household connection, public standpipe, borehole, protected dug well, protected spring, rainwater collection; 'unimproved' includes unprotected well, unprotected spring, vendor‐provided water, bottled water; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
2'Sufficient' means located within 500 m, queuing no more than 15 minutes, no more than three minutes to fill 20 L container, and maintained so available consistently; 'insufficient' means that it does not meet any of above; and 'unclear' means unclear or not reported; definition based minimum standards established by The Sphere Project 2011.
3'Sufficient' means a minimum of 15 L/day/person; 'insufficient' means less than 15 L/day/person; and 'unclear' means unclear or not reported; definition based on minimum standards established by The Sphere Project 2011.
4'Improved' means connection to a public sewer or septic system, pour flush latrine, simple pit latrine, or ventilated improved pit latrine; 'unimproved' means service or bucket latrine, public latrines, open latrines; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
On average, POU filtration technologies reduced diarrhoea by around a half, both for all ages (RR 0.48, 95% CI 0.38 to 0.59; 18 trials, 15,582 participants; Analysis 5.1) and for children under five years of age (RR 0.49, 95% CI 0.38 to 0.62; Analysis 5.1). However, the number of trials and the quality of evidence was different for each specific intervention (Analysis 5.2; Figure 6). The lack of blinding in these studies is a major concern: of the five trials with adequate blinding only one found a statistically significant effect (Analysis 5.3). The quality of evidence was therefore downgraded for all types of filters due to risk of bias (Table 15).
Forest plot of comparison: 4 POU: filtration versus control, outcome: 4.2 Diarrhoea: cluster‐RCTs: subgrouped by type of filtration.
14
| POU filtration compared with no intervention for preventing diarrhoea | |||||
| Patient or population: adults and children Settings: low‐, middle‐ and high‐income countries Intervention: distribution of water filters and instructions on use Comparison: no intervention | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (studies) | Quality of the evidence (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| No intervention | Water filtration | ||||
| Diarrhoea episodes Cluster‐RCTs | 3 episodes per person per year | All filters | RR 0.48 (0.38 to 0.59) | 15,582 (18 trials) | ⊕⊕⊕⊝ moderate1,2,3,4 |
| 1.4 episodes per person per year (1.1 to 1.8) | |||||
| 3 episodes per person per year | Ceramic filters | RR 0.39 (0.29 to 0.53) | 5763 (8 trials) | ⊕⊕⊕⊝ moderate2,4,5,6 | |
| 1.1 episodes per person per year (0.8 to 1.5) | |||||
| Biosand filters | RR 0.47 (0.39 to 0.57) | 5504 (4 trials) | ⊕⊕⊕⊝ moderate4,7,8,9 | ||
| 1.4 episodes per person per year (1.2 to 1.7) | |||||
| LifeStraw®filters | RR 0.69 (0.51 to 0.93) | 3259 (3 trials) | ⊕⊕⊝⊝ low2,4,10,11 | ||
| 2.1 episodes per person per year (1.5 to 2.8) | |||||
| Plumbed filters | RR 0.73 (0.52 to 1.03) | 1056 (3 trials) | ⊕⊕⊕⊝ moderate2,4,12,13 | ||
| 2.2 episodes per person per year (1.6 to 3.1) | |||||
| The basis for the assumed risk is provided in the footnotes. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; RR: risk ratio. | |||||
| GRADE Working Group grades of evidence High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate. | |||||
The assumed risk is based on 2.9 episodes/child year in 2010 (Fischer Walker 2012).
1Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants, this outcome is susceptible to bias from lack of blinding. Only five studies blinded participants and outcome assessors to the treatment allocation and only one found an effect of the intervention.
2No serious inconsistency: statistical heterogeneity was very high, however there is consistency in the direction of the effect.
3No serious indirectness: these studies are from a variety of low‐, middle‐, and high‐income countries (South Africa, Ethiopia, Democratic Republic of Congo, Cambodia, Bolivia, Colombia, USA, Australia, Honduras, Zimbabwe, Zambia, Dominican Republic, Ghana, Kenya and Guatemala).
4No serious imprecision.
5Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants, this outcome is susceptible to bias from lack of blinding. Only one of these studies, Rodrigo 2011 AUS, blinded participants and outcome assessors to the treatment allocation.
6No serious indirectness: these studies are from a variety of low‐, middle‐, and high‐income countries (South Africa, Cambodia, Bolivia, Colombia, Zimbabwe, Guatemala and Australia). The interventions consisted of distribution of water filters (which included a safe storage chamber) plus instructions on how to use them. In some cases, the intervention included hygiene education.
7Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants, this outcome is susceptible to bias from lack of blinding. None these studies blinded participants and outcome assessors to the treatment allocation.
8No serious inconsistency: there was no statistical heterogeneity between studies, I² statistic = 0%.
9No serious indirectness: the studies were conducted in a variety of rural and urban settings in a variety of low‐ and middle‐income countries (Honduras, Dominican Republic, Cambodia, Ghana and Kenya). The interventions consisted of distribution of water filters plus instructions on how to use them. In some cases, the intervention included hygiene education and a separate storage vessel.
10Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants this outcome is susceptible to bias from lack of blinding. Only one of these studies, Boisson 2010 DRC, blinded participants and outcome assessors to the treatment allocation and found no evidence of effect of the filter.
11Downgraded by 1 for some indirectness, the studies were only performed in three sub‐Saharan African countries (Ethiopia, Democratic Republic of Congo, and Zambia).
12No serious risk of bias: the three studies blinded participants and outcome assessors to the treatment allocation.
13Downgraded by 1 for some indirectness, the three studies were only performed in the USA in water conditions that presumed to meet US EPA standards.
Comparison 5 POU: filtration versus control, Outcome 1 Diarrhoea: cluster‐RCTs: subgrouped by age.
Comparison 5 POU: filtration versus control, Outcome 2 Diarrhoea: cluster‐RCTs: subgrouped by type of filtration.
Comparison 5 POU: filtration versus control, Outcome 3 Diarrhoea: cluster‐RCTs: subgrouped by blinding of participants.
POU ceramic filters reduced diarrhoea by around 60% in nine trials mainly from low‐ or middle‐income countries, regardless of whether the water source or sanitation was classified as improved or unimproved (RR 0.39, 95% CI 0.29 to 0.53, eight trials, 5763 participants; Analysis 5.3; Analysis 5.4; moderate quality evidence).
Comparison 5 POU: filtration versus control, Outcome 4 Diarrhoea: ceramic filter studies subgrouped by water source.
Similarly, biosand filtration reduced diarrhoea by around a half consistently across five trials from low‐ or middle‐income settings, again regardless of whether the water source or sanitation was improved or unimproved (RR 0.47, 95% CI 0.39 to 0.57, four trials, 5504 participants; Analysis 5.6; Analysis 5.7; moderate quality evidence).
Comparison 5 POU: filtration versus control, Outcome 6 Diarrhoea: sand filter studies: subgrouped by water source.
Comparison 5 POU: filtration versus control, Outcome 7 Diarrhoea: sand filter studies: subgrouped by sanitation level.
On average, the use of LifeStraw® filters reduced diarrhoea by around a third in three trials from low‐income settings with unimproved water sources (RR 0.69, 95% CI 0.51 to 0.93; three trials, 3259 participants; Analysis 5.2; low quality evidence).
Plumbed‐in filtration has only been evaluated in high‐income settings (USA). There is a modest effect in all three trials, although only one reaches standard levels of statistical significance. The overall meta‐analysis has similar effect sizes with both fixed effects and random effects models, but wider confidence intervals with random effects (Fixed‐effects: RR 0.81, 95% CI 0.70 to 0.94; Random‐effects: RR 0.73, 95% CI 0.52 to 1.03; three trials, 1056 participants; Analysis 5.2; moderate quality evidence).
Adherence with the filtration systems was reported by 14 trials, of which eight assessed this by self‐reported use which is at high risk of bias due to the lack of blinding. Adherence was generally reported as high, and larger effects were apparent in trials with higher adherence (Analysis 5.8). A subgroup analysis looking at filtration interventions with and without the provision of water storage containers (excluding the trials evaluating plumbed in filtration), found larger effects in the nine trials providing containers (Analysis 5.9). Effects were seen in trials with 3, 6, and 12 months of follow‐up, but no effect was demonstrated in the one trial with follow‐up longer than 12 months (Analysis 5.10).
Comparison 5 POU: filtration versus control, Outcome 8 Diarrhoea: cluster‐RCTs: subgrouped by adherence.
Comparison 5 POU: filtration versus control, Outcome 9 Diarrhoea: cluster‐RCTs: subgrouped by additional water storage intervention.
Analysis 6. POU solar disinfection (SODIS)
Four cluster‐RCTs and two quasi‐RCTs evaluated solar disinfection of water from improved sources (one study) and unimproved sources (five studies) in low‐income settings. Plastic bottles were distributed to households with instructions to leave filled bottles in direct sunlight for at least six hours before drinking (see Table 16 and Table 17 for a description of study settings and interventions).
15
| Study ID | Study design | Setting | Intervention areas | Control areas | |||
| Water quality intervention | Health promotion activities | Compliance | Water source | Health promotion activities | |||
| Conroy 1996 KEN | Quasi‐RCT | Rural | Children were given two 1.5 L plastic bottles and told to keep the bottles on the roof of the hut throughout the day in full sunlight | None | 100%‐ random checks by project workers uncovered no evidence of non‐compliance | Children were given two 1.5 L plastic bottles and told to keep the bottles indoors | None |
| Conroy 1999 KEN | Quasi‐RCT | Rural | Mothers were given plastic bottles and told to keep the bottles on the roof of the hut throughout the day in full sunlight | None | Not reported | Mothers were given plastic bottles and told to keep the bottles indoors | None |
| du Preez 2010 ZAF | Cluster‐RCT | Peri urban | Received two 2 L polyethylene terephtalate (PET) bottles for each child. Carers were instructed to fill one bottle and place it in full, unobscured sunlight for a minimum of 6 h every day. | None | 25% compliance measured by participants filling out diarrhoeal diaries at least 75% of the time | No SODIS bottles and maintain their usual practices | None |
| du Preez 2011 KEN | Cluster‐RCT | Peri urban and rural | Received two 2 L PET bottles for each child. Carers were instructed to fill one bottle and place it in full, unobscured sunlight for a minimum of 6 h every day. | None | Not specified. | No SODIS bottles and maintain their usual practices | None |
| Mäusezhal 2009 BOL | Cluster‐RCT | Rural | Households were supplied regularly with clean, PET bottles. They were instructed to expose the waterfilled bottles for at least 6 h to the sun. | Households were taught about the importance and benefits of drinking only treated water, the germ–disease concept, and promoted hygiene measures such as safe drinking water storage and hand washing. | 32% compliance measured by observation | Drinking water from spring (48.1%), tap (51.9%), river (22.1%), rain (14.9%) and dug well (14.9%) | None |
| McGuigan 2011 KHM | Cluster‐RCT | Rural | Households were provided with two transparent 2 L plastic bottles for each child and a sheet of corrugated iron on which to place the bottles to expose them to sunlight. Carers were instructed to fill one bottle and place it in full, unobscured sunlight for a minimum of 6 h every day. | The parents or carers were given verbal and written information on the disease concept and a simple explanation of the solar disinfection process and its effect on the microbial quality of their drinking water and subsequently the health of their children | 90% (5% of children having < 10 months of follow‐up and 2.3% having < 6 months) | Almost all of the households (97%) obtained water from unprotected boreholes. An important subgroup of these, 25%, drew water from shallow tube wells fitted with hand pumps. The remainder used unprotected wells or surface ponds | None |
16
| Trial | Description | Source1 | Access to source2 | Quantity available3 | Ambient H2O quality | Sanitation4 |
| Conroy 1996 KEN | Open water holes, tank fed by untreated piped water supply. | Unimproved | Unclear | Unclear | Source water: 103 CFU/100 mL | Unclear |
| Conroy 1999 KEN | Open water holes, tank fed by untreated piped water supply. | Unimproved | Unclear | Unclear | Source water: 103 CFU/100 mL | Unclear |
| du Preez 2010 ZAF | 39% standpipes, 28% protected borehole, 10% unprotected boreholes, protected springs | Mostly improved | Sufficient | Sufficient | Baseline not reported. Intervention households: 62% of samples met WHO guidelines for water quality; no significant difference from control households | Unclear |
| du Preez 2011 KEN | Spring, protected and unprotected dug wells protected, canals, other | Mostly unimproved | Unclear | Unclear | 50% of samples from stored water had 10 CFU/100 mL or less; no significant difference for intervention and controls | Unclear |
| Mäusezhal 2009 BOL | 48% spring, 52% tap, 22% river, 15% rain, 15% dug well | Improved and unimproved | Sufficient | Sufficient | Not tested | Unimproved |
| McGuigan 2011 KHM | 97% households use unprotected sources: unprotected wells, surface ponds | Unimproved | Unclear | Unclear | Baseline not reported. Control households: geometric mean 48 CFU/100 mL | Unimproved |
1'Improved' includes household connection, public standpipe, borehole, protected dug well, protected spring, rainwater collection; 'unimproved' includes unprotected well, unprotected spring, vendor‐provided water, bottled water; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
2'Sufficient' means located within 500 m, queuing no more than 15 minutes, no more than three minutes to fill 20 L container, and maintained so available consistently; 'insufficient' means that it does not meet any of above; and 'unclear' means unclear or not reported; definition based minimum standards established by The Sphere Project 2011.
3'Sufficient' means a minimum of 15 L/day/person; 'insufficient' means less than 15 L/day/person; and 'unclear' means unclear or not reported; definition based on minimum standards established by The Sphere Project 2011.
4'Improved' means connection to a public sewer or septic system, pour flush latrine, simple pit latrine, or ventilated improved pit latrine; 'unimproved' means service or bucket latrine, public latrines, open latrines; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
Overall in the cluster‐RCTs, solar disinfection reduced diarrhoea by around a third for all ages (RR 0.62, 95% CI 0.42 to 0.94; four trials, 3460 participants; Analysis 6.1), and almost a half in children under five years of age (RR 0.55, 95% CI 0.34 to 0.91; Analysis 6.2). The largest effect was seen in the trial with the highest adherence (Analysis 6.3). The quality of evidence was downgraded to moderate due to the lack of blinding and the inherent risk of bias (Table 18).
17
| POU solar disinfection (SODIS) of water compared with no intervention for preventing diarrhoea | |||||
| Patient or population: adults and children Settings: low‐ and middle‐income countries Intervention: distribution of plastic bottles with instructions on using them to treat water using the SODIS method. Comparison: no intervention | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (studies) | Quality of the evidence (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| No intervention | SODIS | ||||
| Diarrhoea episodes
Cluster‐RCTs | 3 episodes per person per year | 1.9 episodes per person per year (1.3 to 2.8) | RR 0.62 (0.42 to 0.94) | 3460 (4 trials) | ⊕⊕⊕⊝ moderate1,2,3,4 |
| Diarrhoea episodes Quasi‐RCTs | 3 episodes per person per year | 2.5 episodes per person per year (2.1 to 2.9) | RR 0.82 (0.69 to 0.97) | 555 (2 studies) | ⊕⊕⊝⊝ low1,5,6,7 |
| GRADE Working Group grades of evidence High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate. | |||||
The assumed risk is based on 2.9 episodes/child year in 2010 (Fischer Walker 2012).
1Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants this outcome is susceptible to bias from lack of blinding. None of these studies blinded participants and outcome assessors to the treatment allocation.
2No serious inconsistency: statistical heterogeneity was very high (I² statistic = 89%), however there is consistency in the direction of the effect. This heterogeneity may relate to differences in compliance across the studies, however compliance was not measured in the same way across studies.
3No serious indirectness: the studies were conducted in peri‐urban South Africa (one study), peri‐urban and rural Kenya (one study), rural Bolivia (one study) and rural Cambodia (one study).
4No serious imprecision: the average effect suggests that the intervention may reduce diarrhoea episodes by about one third.
5No serious inconsistency: statistical heterogeneity was low (I² statistic = 0%).
6Downgraded by 1 for serious indirectness: there are only two studies and both were conducted in the same province in Kenya (one study included children five to 16 years old and the other included children younger than six years old).
7No serious imprecision.
Comparison 6 POU: solar disinfection versus control, Outcome 1 Diarrhoea: subgrouped by study design.
Comparison 6 POU: solar disinfection versus control, Outcome 2 Diarrhoea: cluster‐RCTs; subgrouped by age.
Comparison 6 POU: solar disinfection versus control, Outcome 3 Diarrhoea: cluster‐RCTs; subgrouped by adherence.
In the quasi‐RCTs the observed effect was lower (RR 0.82, 95% CI 0.69 to 0.97; two trials, 555 participants; Analysis 6.1).
Analysis 7. POU UV disinfection
One cluster‐RCT from Mexico evaluated an UV tube disinfection technology (Gruber 2013 MEX; see Table 19 and Table 20 for a description of the study setting and intervention).
18
| Study ID | Study design | Setting | Intervention areas | Control areas | |||
| Water quality intervention | Health promotion activities | Compliance | Water source | Health promotion activities | |||
| Gruber 2013 MEX | Cluster‐RCT | Rural | Promotion of the UV Tube disinfection technology and safe storage | Unclear | 51% compliance measured by access to treatment device | Unclear | None |
19
| Trial | Description | Source1 | Access to source2 | Quantity available3 | Ambient H2O quality | Sanitation4 |
| Gruber 2013 MEX | Unclear | Unclear | Unclear | Unclear | Baseline: 60% of samples with detectable E. coli | Improved |
1'Improved' includes household connection, public standpipe, borehole, protected dug well, protected spring, rainwater collection; 'unimproved' includes unprotected well, unprotected spring, vendor‐provided water, bottled water; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
2'Sufficient' means located within 500 m, queuing no more than 15 minutes, no more than three minutes to fill 20 L container, and maintained so available consistently; 'insufficient' means that it does not meet any of above; and 'unclear' means unclear or not reported; definition based minimum standards established by The Sphere Project 2011.
3'Sufficient' means a minimum of 15 L/day/person; 'insufficient' means less than 15 L/day/person; and 'unclear' means unclear or not reported; definition based on minimum standards established by The Sphere Project 2011.
4'Improved' means connection to a public sewer or septic system, pour flush latrine, simple pit latrine, or ventilated improved pit latrine; 'unimproved' means service or bucket latrine, public latrines, open latrines; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
The effect on diarrhoea among all age populations did not reach standard levels of statistical significance (RR 0.79, 95% CI 0.49 to 1.27; one trial, 1913 participants; Analysis 7.1), and did not report separately for children under five years of age.
Analysis 8. POU improved storage
Two trials from Malawi and Benin evaluated the distribution of improved water storage containers in settings with improved water sources (see Table 21 and Table 22 for a description of the study setting and intervention).
20
| Study ID | Study design | Setting | Intervention areas | Control areas | |||
| Water quality intervention | Health promotion activities | Compliance | Water source | Health promotion activities | |||
| Günther 2013 BEN | Cluster‐RCT | Rural | Provided households with a new 30 L household water storage with a tap at the bottom, a new plastic container to transport water from the water source to the household and a sign attached to the transport and storage containers which emphasized the importance of avoiding hand‐contact with the water and to only use water from an improved water source. | None | After 7 months, 88% of households were still using the improved storage containers | 68% only consume improved water source | None |
| Roberts 2001 MWI | Cluster‐RCT | Refugee camp | All of the participating household's water collection vessels were exchanged for improved buckets (20 L with a narrow opening to limit hand entry). Households were offered 1 improved bucket in exchange for 1 vessel, 2 for 2, and 3 improved buckets for any number of containers > 2. Households were asked never to put their hands in the improved buckets and were shown how to rinse the bucket without hand entry. | None | Intervention householders received buckets; actual use was not reported | Provided with 20 L standard ration bucket | None |
21
| Trial | Description | Source1 | Access to source2 | Quantity available3 | Ambient H2O quality | Sanitation4 |
| Günther 2013 BEN | Public tap or pump | Improved | Sufficient | Unclear | 12% source water contaminated (≥ 1000 CFU per 100 mL) | Unclear |
| Roberts 2001 MWI | Traditional pots or standard ration buckets filled at refugee camp water point | Improved | Unclear | Unclear | Source water: 71% of samples had ≤ 1 faecal coliform/100 mL | Unclear |
1'Improved' includes household connection, public standpipe, borehole, protected dug well, protected spring, rainwater collection; 'unimproved' includes unprotected well, unprotected spring, vendor‐provided water, bottled water; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
2'Sufficient' means located within 500 m, queuing no more than 15 minutes, no more than three minutes to fill 20 L container, and maintained so available consistently; 'insufficient' means that it does not meet any of above; and 'unclear' means unclear or not reported; definition based minimum standards established by The Sphere Project 2011.
3'Sufficient' means a minimum of 15 L/day/person; 'insufficient' means less than 15 L/day/person; and 'unclear' means unclear or not reported; definition based on minimum standards established by The Sphere Project 2011.
4'Improved' means connection to a public sewer or septic system, pour flush latrine, simple pit latrine, or ventilated improved pit latrine; 'unimproved' means service or bucket latrine, public latrines, open latrines; and 'unclear' means unclear or not reported; definition based on WHO/UNICEF 2015.
Overall, there was no statistically significant effect on diarrhoea for all ages (RR 0.91, 95% CI 0.74 to 1.11; two trials, 1871 participants; Analysis 8.1), or children under five years of age (RR 0.69, 95% CI 0.47 to 1.01; Analysis 8.1). Both studies were at high risk of bias due to being non‐blinded, and the overall quality of the evidence was judged to be low (Table 23).
22
| Improved water storage compared with no intervention for preventing diarrhoea | |||||
| Patient or population: adults and children in sub‐Saharan Africa Settings: areas with improved water sources Intervention: distribution of improved water containers Comparison: no intervention | |||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | Number of participants (studies) | Quality of the evidence (GRADE) | |
| Assumed risk | Corresponding risk | ||||
| No intervention | Water storage | ||||
| Diarrhoea episodes Cluster‐RCTs | 3 episodes per person per year | 2.7 episodes per person per year (2.2 to 3.3 ) | RR 0.91 (0.74 to 1.11) | 1871 (2 trials) | ⊕⊕⊝⊝ low1,2,3,4 |
| The basis for the assumed risk is the median control group risk across studies. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; RR: risk ratio. | |||||
| GRADE Working Group grades of evidence High quality: further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: we are very uncertain about the estimate. | |||||
The assumed risk is based on 2.9 episodes/child year in 2010 (Fischer Walker 2012).
1Downgraded by 1 for serious risk of bias: as diarrhoea episodes were reported by participants this outcome is susceptible to bias from lack of blinding. None of these studies blinded participants and outcome assessors to the treatment allocation.
2No serious inconsistency.
3Downgraded by 1 for indirectness: only 2 studies, from rural Benin and a refugee camp in Malawi, have been conducted to assess improved water storage.
4No serious imprecision.
Analyses adjusted for non‐blinding
In Table 24 we have presented meta‐analysis results adjusted for non‐blinding using an approach described in the Methods section and based in part on those employed by other researchers (Hunter 2009; Wolf 2014). In these analyses, the effects of POU chlorination and filtration are smaller but remain statistically significant; the effect of POU solar disinfection becomes borderline non‐significant.
23
| POU intervention | Number of comparisons | Not adjusted for non‐blinding | Adjusted for non‐blinding | ||
| RR | 95% CI | RR | 95% CI | ||
| All | 55 | 0.56 | (0.46 to 0.68) | 0.70 | (0.64 to 0.77) |
| Chlorination | 19 | 0.72 | (0.61 to 0.84) | 0.80 | (0.69 to 0.92) |
| Filtration | 23 | 0.48 | (0.38 to 0.59) | 0.62 | (0.55 to 0.70) |
| Flocculation and disinfection | 7 | 0.48 | (0.20 to 1.16) | 0.65 | (0.40 to 1.09) |
| SODIS | 6 | 0.68 | (0.53 to 0.89) | 0.80 | (0.60 to 1.01) |
Abbreviation: SODIS: solar disinfection; CI: confidence interval.
Discussion
Summary of main results
There is currently insufficient evidence to know if source‐based improvements such as protected wells, communal tap stands, or chlorination/filtration of community sources consistently reduce diarrhoea (very low quality evidence).
The distribution and promotion of point‐of‐use water chlorination products may reduce diarrhoea by around one quarter (low quality evidence). Similarly, distribution and promotion of flocculation and disinfection sachets probably reduces diarrhoea but had highly variable effects (moderate quality evidence).
Point‐of‐use filtration systems probably reduce diarrhoea by around a half (moderate quality evidence). This reduction was apparent for ceramic filters, biosand systems and LifeStraw® filters, but plumbed in filtration has only been evaluated in high‐ income settings and a statistically significant effect has not been demonstrated.
In low‐income settings, distribution of plastic bottles with instructions to leave filled bottles in direct sunlight for at least six hours before drinking (SODIS) probably reduces diarrhoea by around a third (moderate quality evidence).
In subgroup analyses, larger effects were seen in trials with higher adherence, and trials that provided a safe storage container.
Overall completeness and applicability of evidence
Fifty‐five studies met the inclusion criteria, of which most studies were conducted in low‐ or middle‐income countries (50 studies), with unimproved water sources (30 studies), and unimproved or unclear sanitation (34 studies).
For water source interventions, there are simply too few studies to make conclusions about what may or may not be effective in different settings. While protective effects were seen in some individual trials, it is unclear whether these effects could be expected to be reproducible in other settings, and all of the trials had multiple potential sources of bias. Significantly, we found no studies evaluating reliable, piped‐in water supplies.
In contrast, some POU interventions do appear to be broadly protective against diarrhoea across many settings regardless of whether water sources and sanitation are 'improved' or 'unimproved'. This finding affirms the current strategy of the WHO and UNICEF to promote POU water treatment and safe storage, even though this will not increase the number of households with access to improved water supplies and therefore will not contribute towards achieving current international water targets (WHO 2011). The effectiveness of POU interventions in settings without improved sanitation contradicts earlier findings that interventions to improve water quality are effective only where sanitation has already been addressed (Esrey 1986; VanDerslice 1995), or that environmental interventions to prevent diarrhoea are effective only by employing an integrated approach (Eisenberg 2007).
Although we provide average estimates of effect for each individual POU intervention, we recommend caution in using these estimates to conclude the superiority of one intervention over another. Such an observational analysis would be highly susceptible to confounding by study setting and population, and may not represent true differences in the size of the effects. Head‐to‐head trials would be necessary to reliably conclude superiority and these were not the focus of this review.
As few studies continued follow‐up beyond 12 months, we are unable to comment reliably on the long‐term sustainability of these effects. While pooled estimates of studies with follow‐up periods under 12 months were generally protective, those with follow‐up periods in excess of 12 months were not.
Quality of the evidence
The quality of evidence for the effects of the individual interventions on diarrhoea ranged from moderate (for ceramic filters and biosand filtration), to low (for distribution of chlorination kits, flocculation and disinfection sachets, and LifeStraw® filters), to very low (for water source improvements).
The primary reason for downgrading the quality of evidence was the risk of bias inherent in unblinded studies evaluating the efficacy of an intervention on a self‐reported outcome. Notably, only one of the nine blinded trials reported a statistically significant protective effect, but this observation may be explained by other confounding factors present in these nine trials (see Table 25):
24
| Study | Risk from ambient water quality | Compliance | Other issues |
| Colford 2002 USA | Very low (USA) | High (Sham filter) | None |
| Colford 2005 USA | Very low (USA) | High (Sham filter) | None |
| Colford 2009 USA | Very low (USA) | High (Sham filter) | None |
| Rodrigo 2011 AUS | Very low (Australia) | Not reported | None |
| Jain 2010 GHA | Low (11 CFU/100 mL) | High (RFC) | Control group received jerry can; 13 week follow‐up |
| Kirchhoff 1985 BRA | Very high (mean 16000 FC/dL) | Not reported | Only 112 persons from 16 households; 18 week trial |
| Austin 1993 | High (1871 FC/100 mL) | Low ("50% to 60%") | No test of blinding; not peer reviewed |
| Boisson 2010 DRC | High (75% of samples > 1000 TTC/100 mL) | High, but 73% of adults and 95% of children drank from untreated sources | "Placebo" removed > 90% of TTC in control arm |
| Boisson 2013 IND | Moderate (mean 122 TTC/100 mL) | Low and inconsistent (32% of samples positive for RFC) | None |
Abbreviations: TTC: thermotolerant coliforms, CFU: colony‐forming units, FC: faecal coliforms, RFC: residual free chlorine.
- Four studies were conducted in high‐income countries where the water was of good microbiological quality even in the control groups (Colford 2002 USA; Colford 2005 USA; Colford 2009 USA; Rodrigo 2011 AUS).
- One further trial from Ghana found very low levels of faecal contamination of water supplies in the control group which were likely to present only minimal risk (Jain 2010 GHA).
- Three studies had either low adherence with the intervention (Austin 1993; Boisson 2013 IND), or very high reported use of drinking untreated water from other sources (Boisson 2010 DRC).
- Two studies employed control interventions which may have improved water quality: Boisson 2010 DRC employed a "placebo" that actually removed one log (90%) of faecal indicator bacteria and Jain 2010 GHA provided control households with safe storage.
The second common reason for downgrading the quality of evidence was unexplained heterogeneity. For some of the POU interventions, the protective effect varied considerably across studies. Some of this variability could be explained by adherence with the intervention, with larger effects in studies with higher adherence, but some variability remained which we were unable to explain despite multiple subgroup analyses. This is likely to reflect important underlying clinical heterogeneity: the aetiology and epidemiology of diarrhoea is complex and variable, transmission pathways are multiple, and even the portion of diarrhoea that is waterborne is not well understood (Eisenberg 2012).
There was also some evidence of possible publication bias in the trials evaluating home chlorination but this was not strong enough to further downgrade the quality of evidence.
Potential biases in the review process
A number of the included studies had multiple intervention arms comparing two or more intervention groups against a single control group. In some analyses, we included multiple comparisons from the same trial which double counts the control group participants and yields results in the meta‐analysis that are artificially precise. However, this bias is unlikely to have significantly impacted the overall quality of evidence or conclusions.
Agreements and disagreements with other studies or reviews
Our results are generally consistent with the prior version of this Cochrane Review (Clasen 2006) and with other reviews of water quality interventions (Fewtrell 2005; Arnold 2007; Waddington 2009; Cairncross 2010; Wolf 2014).
One additional review of water quality interventions reports no effect with POU interventions once blinding is taken into account (Engell 2013). While we share the concerns about the lack of blinding in many of these trials (and have downgraded the quality of evidence accordingly), and also found no effect in any of the trials with adequate blinding, we have identified several possible confounders in this observation (discussed above), and retain low to moderate confidence that these interventions are effective.
Although we found no controlled trials evaluating piped‐in water supplies, a recent review that also included some observational studies reported some evidence of a protective effect with this intervention (Wolf 2014).
The finding of larger effects with increased adherence is consistent with modelling data based on quantitative microbial risk assessment which suggest a dose‐response association between water quality and diarrhoea (Brown 2012; Enger 2013).
Authors' conclusions
What's new
| Date | Event | Description |
|---|---|---|
| 21 October 2015 | Amended | Amended author affiliations. |
History
Protocol first published: Issue 2, 2004
Review first published: Issue 3, 2006
| Date | Event | Description |
|---|---|---|
| 15 October 2015 | New search has been performed | The review authors updated the review, and included several new studies, a 'Summary of findings' table, and 'Risk of bias' assessments. |
| 15 October 2015 | New citation required and conclusions have changed | The review authors performed an updated literature search, reapplied the inclusion criteria, repeated data extraction, added new studies, and used the GRADE approach to assess the quality of the evidence. They also applied statistical methods to unify the measures of effect and applied additional criteria for subgrouping based on study design, setting, and length of follow‐up. |
Acknowledgements
We gratefully acknowledge co‐authors of the previous version of this Cochrane Review: Ian Roberts, Tamer Rabie, and Wolf‐Peter Schmidt (Clasen 2006). We are also grateful to the following people for their research, advice, assistance, and other valuable contributions: Greg Allgood, Jamie Bartram, Joseph Brown, Jack Colford, John Crump, Tom Chiller, Val Curtis, Shannon Doocy, Lorna Fewtrell, Carrol Gamble, Bruce Gordon, Stephen Gundry, Paul Hunter, Bruce Keswick, Steve Luby, Rob Quick, Mark Sobsey, Sara Thomas, and James Wright. We also appreciate the assistance and help provided by CIDG members and by the referees of both this review and the protocol.
The editorial base for the Cochrane Infectious Diseases Group is funded by the UK Department for International Development (DFID) for the benefit of developing countries.
Appendices
Appendix 1. Search methods: detailed search strategies
| Search set | CIDG SRa | CENTRAL | MEDLINEb | EMBASEb | LILACSb |
| 1 | water | WATER PURIFICATION | WATER PURIFICATION | WATER PURIFICATION | water |
| 2 | purification OR treatment OR chlorination OR decontamination OR filtration OR supply OR storage OR consumption | WATER MICROBIOLOGY | WATER MICROBIOLOGY | WATER MICROBIOLOGY | purification OR treatment OR chlorination OR decontamination OR filtration OR supply OR storage OR consumption |
| 3 | diarrhea | 1 OR 2 | 1 OR 2 | 1 OR 2 | diarrhea |
| 4 | 1 AND 2 AND 3 | water | water | water | 1 AND 2 AND 3 |
| 5 | — | purification OR treatment OR chlorination OR decontamination OR filtration OR supply OR storage OR consumption OR drink* | purification OR treatment OR chlorination OR decontamination OR filtration OR supply OR storage OR consumption OR drink* | purification OR treatment OR chlorination OR decontamination OR filtration OR supply OR storage OR consumption OR drink$ | — |
| 6 | — | 4 AND 5 | 4 AND 5 | 4 AND 5 | — |
| 7 | — | 3 OR 6 | 3 OR 6 | 3 OR 6 | — |
| 8 | — | DIARRHEA/EPIDEMIOLOGY | DIARRHEA/EPIDEMIOLOGY | DIARRHEA/EPIDEMIOLOGY | — |
| 9 | — | DIARRHEA/MICROBIOLOGY | DIARRHEA/MICROBIOLOGY | DIARRHEA/PREVENTION | — |
| 10 | — | DIARRHEA/PREVENTION AND CONTROL | DIARRHEA/PREVENTION AND CONTROL | waterborne infection$ | — |
| 11 | — | waterborne infection* | waterborne infection* | cholera OR shigell$ OR dysenter$ OR cryptosporidi$ OR giardia$ OR Escherichia coli OR clostridium | — |
| 12 | — | INTESTINAL DISEASES | INTESTINAL DISEASES | ENTEROBACTERIACEAE | — |
| 13 | — | cholera OR shigell* OR dysenter* OR cryptosporidi* OR giardia* OR Escherichia coli OR clostridium | cholera OR shigell* OR dysenter* OR cryptosporidi* OR giardia* OR Escherichia coli OR clostridium | 8‐12/OR | — |
| 14 | — | ENTEROBACTERIACEAE | ENTEROBACTERIACEAE | 7 AND 13 | — |
| 15 | — | 8‐14/OR | 8‐14/OR | LIMIT 14 TO HUMAN | — |
| 16 | — | 7 AND 15 | 7 AND 15 | — | — |
| 17 | — | — | LIMIT 16 TO HUMAN | — | — |
aCochrane Infectious Diseases Group Specialized Register.
bSearch terms used in combination with the search strategy for retrieving trials developed by Cochrane (Higgins 2005); upper case: MeSH or EMTREE heading; lower case: free text term.
Appendix 2. Data extracted from included studies
| Type | Fields |
| Trial data | Country and setting (urban, rural) |
| Number of participants/groups | |
| Unit of randomization, and whether measurement of effect adjusts for clustering where randomization is other than individual | |
| Definition and practices of control group | |
| Type and details of water quality intervention (filtration, flocculation, chemical disinfection, heat, or UV radiation) | |
| Other components of intervention (hygiene message, improved supply, improved sanitation, improved storage) | |
| Whether water protected to POU (i.e. by pipe, residual disinfection, or safe storage) | |
| Case definition of diarrhoea | |
| Method for diarrhoea assessment (self‐reported, observed, or clinically confirmed) | |
| Where self reported, recall period used | |
| Study duration; Adherence rates | |
| Publication status | |
| Prescribed criteria of methodological quality | |
| Individual characteristics | Age group |
| Type and description of water source | |
| Level of faecal contamination of control water (low (< 100 thermotolerant coliforms (TTC)/100 mL), medium (100 to 1000 TTC/100 mL), and high (> 1000 TTC/100 mL) | |
| Causative agents identified (yes or no) | |
| Water collection, storage, and drawing practices | |
| Distance to and other constraints regarding water supply | |
| Sanitation facilities (improved or unimproved) | |
| Hygiene practices | |
| Outcomes | Pre‐ and post‐intervention faecal contamination of drinking water, and method of assessment (including indicator used) |
| Diarrhoea morbidity and 95% CI for each age group reported | |
| Manner of measuring diarrhoea morbidity | |
| Mortality attributed to diarrhoea | |
| Rate of utilization of intervention and manner of assessing same |
Abbreviations: POU: point of use; CI: confidence interval; UV: ultraviolet.
Notes
Unchanged
Data and analyses
Comparison 1
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: all ages | 64 | 81215 | Risk Ratio (Random, 95% CI) | 0.59 [0.51, 0.69] |
| 1.1 Source water improvement | 6 | 9161 | Risk Ratio (Random, 95% CI) | 0.76 [0.48, 1.19] |
| 1.2 POU treatment | 58 | 72054 | Risk Ratio (Random, 95% CI) | 0.58 [0.48, 0.69] |
| 2 Diarrhoea: children < 5 years | 49 | Risk Ratio (Random, 95% CI) | 0.61 [0.49, 0.75] | |
| 2.1 Source water improvement | 4 | Risk Ratio (Random, 95% CI) | 0.96 [0.82, 1.12] | |
| 2.2 POU treatment | 45 | Risk Ratio (Random, 95% CI) | 0.58 [0.46, 0.73] |
Comparison 2
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: CBA studies subgrouped by age | 6 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 1.1 Cluster‐RCTs | 1 | 3266 | Risk Ratio (Random, 95% CI) | 1.24 [0.98, 1.57] |
| 1.2 CBA studies | 5 | 5895 | Risk Ratio (Random, 95% CI) | 0.68 [0.42, 1.09] |
| 2 Diarrhoea: CBA studies subgrouped by age | 5 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 2.1 All ages | 5 | 5895 | Risk Ratio (Random, 95% CI) | 0.68 [0.42, 1.09] |
| 2.2 < 5 years | 3 | 999 | Risk Ratio (Random, 95% CI) | 0.92 [0.79, 1.07] |
Comparison 3
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: subgrouped by study design | 19 | 34694 | Risk Ratio (Random, 95% CI) | 0.72 [0.61, 0.84] |
| 1.1 Cluster‐RCTs | 16 | 30746 | Risk Ratio (Random, 95% CI) | 0.77 [0.65, 0.91] |
| 1.2 CBA studies | 3 | 3948 | Risk Ratio (Random, 95% CI) | 0.51 [0.34, 0.75] |
| 2 Diarrhoea: cluster‐RCTs: subgrouped by age | 16 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 2.1 All ages | 16 | Risk Ratio (Random, 95% CI) | 0.77 [0.65, 0.91] | |
| 2.2 < 5 years | 15 | Risk Ratio (Random, 95% CI) | 0.77 [0.64, 0.92] | |
| 3 Diarrhoea: cluster‐RCTs; subgrouped by adherence | 16 | 30746 | Risk Ratio (Random, 95% CI) | 0.77 [0.65, 0.91] |
| 3.1 Residual chlorine in 86 to 100% of samples | 1 | 276 | Risk Ratio (Random, 95% CI) | 0.78 [0.73, 0.83] |
| 3.2 Residual chlorine in 51 to 85% of samples | 6 | 9994 | Risk Ratio (Random, 95% CI) | 0.60 [0.40, 0.91] |
| 3.3 Residual chlorine in ≤ 50% of samples | 4 | 12613 | Risk Ratio (Random, 95% CI) | 0.90 [0.76, 1.06] |
| 3.4 Residual chlorine not reported | 5 | 7863 | Risk Ratio (Random, 95% CI) | 0.85 [0.65, 1.12] |
| 4 Diarrhoea: cluster‐RCTs by risk of bias by blinding of participants | 16 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 4.1 Low risk | 5 | 15867 | Risk Ratio (Random, 95% CI) | 1.07 [0.97, 1.17] |
| 4.2 High risk | 11 | 14879 | Risk Ratio (Random, 95% CI) | 0.68 [0.56, 0.83] |
| 5 Diarrhoea: cluster‐RCTs; subgrouped by additional water storage intervention | 16 | Risk Ratio (Random, 95% CI) | 0.77 [0.65, 0.91] | |
| 5.1 Chlorination kit alone | 8 | Risk Ratio (Random, 95% CI) | 0.75 [0.54, 1.05] | |
| 5.2 Chlorination kit plus water storage | 8 | Risk Ratio (Random, 95% CI) | 0.80 [0.66, 0.97] | |
| 6 Diarrhoea: cluster‐RCTs: subgrouped by sufficiency of water quantity | 16 | 30746 | Risk Ratio (Random, 95% CI) | 0.77 [0.65, 0.91] |
| 6.1 Sufficient | 3 | 5352 | Risk Ratio (Random, 95% CI) | 0.90 [0.69, 1.17] |
| 6.2 Insufficient | 2 | 3499 | Risk Ratio (Random, 95% CI) | 0.91 [0.66, 1.26] |
| 6.3 Unclear | 11 | 21895 | Risk Ratio (Random, 95% CI) | 0.67 [0.50, 0.88] |
| 7 Diarrhoea: cluster‐RCTs: subgrouped by water source | 16 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 7.1 Improved water source | 3 | 5880 | Risk Ratio (Random, 95% CI) | 0.82 [0.59, 1.14] |
| 7.2 Unimproved water source | 13 | 24866 | Risk Ratio (Random, 95% CI) | 0.75 [0.59, 0.93] |
| 8 Diarrhoea: cluster‐RCTs: subgrouped by sanitation level | 16 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 8.1 Improved sanitation | 3 | 4876 | Risk Ratio (Random, 95% CI) | 0.64 [0.44, 0.92] |
| 8.2 Unimproved sanitation | 6 | 17352 | Risk Ratio (Random, 95% CI) | 0.81 [0.63, 1.05] |
| 8.3 Unclear | 7 | 8518 | Risk Ratio (Random, 95% CI) | 0.75 [0.54, 1.05] |
| 9 Diarrhoea: cluster‐RCTs; subgrouped by length of follow‐up | 16 | Risk Ratio (Random, 95% CI) | 0.77 [0.65, 0.91] | |
| 9.1 ≤ 3 months | 2 | Risk Ratio (Random, 95% CI) | 0.42 [0.06, 3.03] | |
| 9.2 > 3 to 6 months | 7 | Risk Ratio (Random, 95% CI) | 0.71 [0.51, 0.99] | |
| 9.3 > 6 to 12 months | 5 | Risk Ratio (Random, 95% CI) | 0.82 [0.71, 0.96] | |
| 9.4 > 12 months | 2 | Risk Ratio (Random, 95% CI) | 0.99 [0.66, 1.48] |
Comparison 3 POU: water chlorination versus control, Outcome 6 Diarrhoea: cluster‐RCTs: subgrouped by sufficiency of water quantity.
Comparison 3 POU: water chlorination versus control, Outcome 7 Diarrhoea: cluster‐RCTs: subgrouped by water source.
Comparison 3 POU: water chlorination versus control, Outcome 8 Diarrhoea: cluster‐RCTs: subgrouped by sanitation level.
Comparison 4
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: cluster‐RCTs | 7 | Risk Ratio (Random, 95% CI) | 0.48 [0.20, 1.16] | |
| 2 Diarrhoea: cluster‐RCTs: subgrouped by age; excluding Doocy 2006 LBR | 6 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 2.1 All ages | 6 | 11788 | Risk Ratio (Random, 95% CI) | 0.69 [0.58, 0.82] |
| 2.2 < 5 | 6 | 0 | Risk Ratio (Random, 95% CI) | 0.71 [0.61, 0.84] |
| 3 Diarrhoea: cluster‐RCTs: subgrouped by adherence | 7 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 3.2 Residual chlorine 51 to 85% | 1 | 2191 | Risk Ratio (Random, 95% CI) | 0.12 [0.11, 0.13] |
| 3.3 Residual chlorine < 50% | 4 | 6914 | Risk Ratio (Random, 95% CI) | 0.76 [0.67, 0.85] |
| 3.4 Residual chlorine not measured | 2 | 4874 | Risk Ratio (Random, 95% CI) | 0.41 [0.26, 0.64] |
| 4 Diarrhoea: cluster‐RCTs: subgrouped by additional storage container | 7 | Risk Ratio (Random, 95% CI) | 0.48 [0.20, 1.16] | |
| 4.1 No storage container | 2 | Risk Ratio (Random, 95% CI) | 0.81 [0.69, 0.95] | |
| 4.2 Storage container | 5 | Risk Ratio (Random, 95% CI) | 0.39 [0.14, 1.08] | |
| 5 Diarrhoea: cluster‐RCTs: subgrouped by sufficiency of water quantity | 7 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 5.1 Sufficient | 1 | 3401 | Risk Ratio (Random, 95% CI) | 0.62 [0.47, 0.82] |
| 5.2 Insufficient | 2 | 5454 | Risk Ratio (Random, 95% CI) | 0.31 [0.05, 2.09] |
| 5.3 Unclear | 4 | 5124 | Risk Ratio (Random, 95% CI) | 0.64 [0.49, 0.85] |
| 6 Diarrhoea: cluster‐RCTs: subgrouped by water source | 7 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 6.1 Improved water source | 2 | 4874 | Risk Ratio (Random, 95% CI) | 0.41 [0.26, 0.64] |
| 6.2 Unimproved water source | 4 | 5704 | Risk Ratio (Random, 95% CI) | 0.49 [0.14, 1.68] |
| 6.3 Unclear | 1 | 3401 | Risk Ratio (Random, 95% CI) | 0.62 [0.47, 0.82] |
| 7 Diarrhoea: cluster‐RCTs: subgrouped by sanitation level | 7 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 7.1 Improved sanitation | 2 | 4874 | Risk Ratio (Random, 95% CI) | 0.41 [0.26, 0.64] |
| 7.2 Unimproved sanitation | 2 | 5592 | Risk Ratio (Random, 95% CI) | 0.27 [0.05, 1.36] |
| 7.3 Unclear | 3 | 3513 | Risk Ratio (Random, 95% CI) | 0.79 [0.69, 0.90] |
| 8 Diarrhoea: cluster‐RCTs: subgrouped by length of follow‐up | 7 | 13979 | Risk Ratio (Random, 95% CI) | 0.48 [0.20, 1.16] |
| 8.1 ≤ 3 months | 2 | 5592 | Risk Ratio (Random, 95% CI) | 0.27 [0.05, 1.36] |
| 8.2 > 3 to 6 months | 1 | 3263 | Risk Ratio (Random, 95% CI) | 0.83 [0.67, 1.03] |
| 8.3 > 6 to 12 months | 4 | 5124 | Risk Ratio (Random, 95% CI) | 0.64 [0.49, 0.85] |
Comparison 5
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: cluster‐RCTs: subgrouped by age | 23 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 1.1 All ages | 23 | Risk Ratio (Random, 95% CI) | 0.48 [0.38, 0.59] | |
| 1.2 < 5 years | 19 | Risk Ratio (Random, 95% CI) | 0.49 [0.38, 0.62] | |
| 2 Diarrhoea: cluster‐RCTs: subgrouped by type of filtration | 23 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 2.1 Ceramic filter | 12 | 5763 | Risk Ratio (Random, 95% CI) | 0.39 [0.29, 0.53] |
| 2.2 Sand filtration | 5 | 5504 | Risk Ratio (Random, 95% CI) | 0.47 [0.39, 0.57] |
| 2.3 LifeStraw® | 3 | 3259 | Risk Ratio (Random, 95% CI) | 0.69 [0.51, 0.93] |
| 2.4 Plumbed | 3 | 1056 | Risk Ratio (Random, 95% CI) | 0.73 [0.52, 1.03] |
| 3 Diarrhoea: cluster‐RCTs: subgrouped by blinding of participants | 23 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 3.1 Low risk | 5 | Risk Ratio (Random, 95% CI) | 0.80 [0.68, 0.94] | |
| 3.2 High risk | 18 | Risk Ratio (Random, 95% CI) | 0.41 [0.33, 0.52] | |
| 4 Diarrhoea: ceramic filter studies subgrouped by water source | 12 | 5763 | Risk Ratio (Random, 95% CI) | 0.39 [0.29, 0.53] |
| 4.1 Improved water source | 8 | 3607 | Risk Ratio (Random, 95% CI) | 0.33 [0.23, 0.46] |
| 4.2 Unimproved water source | 4 | 2156 | Risk Ratio (Random, 95% CI) | 0.54 [0.48, 0.61] |
| 5 Diarrhoea: ceramic filter studies subgrouped by sanitation level | 12 | 5763 | Risk Ratio (Random, 95% CI) | 0.39 [0.29, 0.53] |
| 5.1 Improved sanitation | 7 | 4198 | Risk Ratio (Random, 95% CI) | 0.49 [0.38, 0.64] |
| 5.2 Unimproved sanitation | 4 | 1491 | Risk Ratio (Random, 95% CI) | 0.35 [0.22, 0.56] |
| 5.3 Unclear | 1 | 74 | Risk Ratio (Random, 95% CI) | 0.21 [0.18, 0.25] |
| 6 Diarrhoea: sand filter studies: subgrouped by water source | 5 | Risk Ratio (Random, 95% CI) | 0.47 [0.39, 0.57] | |
| 6.1 Improved water source | 2 | Risk Ratio (Random, 95% CI) | 0.50 [0.33, 0.75] | |
| 6.2 Unimproved water source | 2 | Risk Ratio (Random, 95% CI) | 0.44 [0.25, 0.76] | |
| 6.3 Unclear | 1 | Risk Ratio (Random, 95% CI) | 0.47 [0.37, 0.60] | |
| 7 Diarrhoea: sand filter studies: subgrouped by sanitation level | 5 | Risk Ratio (Random, 95% CI) | 0.47 [0.39, 0.57] | |
| 7.1 Improved sanitation | 1 | Risk Ratio (Random, 95% CI) | 0.47 [0.37, 0.60] | |
| 7.2 Unimproved sanitation | 3 | Risk Ratio (Random, 95% CI) | 0.48 [0.34, 0.68] | |
| 7.3 Unclear | 1 | Risk Ratio (Random, 95% CI) | 0.46 [0.22, 0.96] | |
| 8 Diarrhoea: cluster‐RCTs: subgrouped by adherence | 23 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 8.1 86 to 100% | 12 | 7300 | Risk Ratio (Random, 95% CI) | 0.43 [0.34, 0.55] |
| 8.2 51 to 85% | 4 | 2346 | Risk Ratio (Random, 95% CI) | 0.56 [0.33, 0.95] |
| 8.3 ≤ 50% | 1 | 1516 | Risk Ratio (Random, 95% CI) | 0.75 [0.60, 0.94] |
| 8.4 Not reported | 6 | 4420 | Risk Ratio (Random, 95% CI) | 0.46 [0.28, 0.75] |
| 9 Diarrhoea: cluster‐RCTs: subgrouped by additional water storage intervention | 19 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 9.1 Filtration alone | 8 | Risk Ratio (Random, 95% CI) | 0.60 [0.48, 0.76] | |
| 9.2 Filtration plus storage | 11 | Risk Ratio (Random, 95% CI) | 0.38 [0.29, 0.49] | |
| 10 Diarrhoea: cluster‐RCTs; subgrouped by length of follow‐up | 23 | Risk Ratio (Random, 95% CI) | 0.48 [0.38, 0.59] | |
| 10.1 ≤ 3 months | 3 | Risk Ratio (Random, 95% CI) | 0.26 [0.20, 0.33] | |
| 10.2 > 3 to 6 months | 11 | Risk Ratio (Random, 95% CI) | 0.52 [0.44, 0.60] | |
| 10.3 > 6 to 12 months | 8 | Risk Ratio (Random, 95% CI) | 0.51 [0.30, 0.87] | |
| 10.4 > 12 months | 1 | Risk Ratio (Random, 95% CI) | 0.87 [0.74, 1.02] |
Comparison 5 POU: filtration versus control, Outcome 5 Diarrhoea: ceramic filter studies subgrouped by sanitation level.
Comparison 6
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: subgrouped by study design | 6 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 1.1 Cluster‐RCTs | 4 | 3460 | Risk Ratio (Random, 95% CI) | 0.62 [0.42, 0.94] |
| 1.2 Quasi‐RCTs | 2 | 555 | Risk Ratio (Random, 95% CI) | 0.82 [0.69, 0.97] |
| 2 Diarrhoea: cluster‐RCTs; subgrouped by age | 4 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 2.1 All ages | 4 | Risk Ratio (Random, 95% CI) | 0.62 [0.42, 0.94] | |
| 2.2 < 5 | 3 | Risk Ratio (Random, 95% CI) | 0.55 [0.34, 0.91] | |
| 3 Diarrhoea: cluster‐RCTs; subgrouped by adherence | 4 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 3.1 86 to 100% | 1 | 928 | Risk Ratio (Random, 95% CI) | 0.37 [0.29, 0.47] |
| 3.2 51 to 85% | 0 | 0 | Risk Ratio (Random, 95% CI) | 0.0 [0.0, 0.0] |
| 3.3 ≤ 50% | 2 | 1443 | Risk Ratio (Random, 95% CI) | 0.80 [0.57, 1.11] |
| 3.4 Not reported | 1 | 1089 | Risk Ratio (Random, 95% CI) | 0.73 [0.63, 0.85] |
| 4 Diarrhoea: cluster‐RCTs; subgrouped by sufficiency of water supply level | 4 | 3460 | Risk Ratio (Random, 95% CI) | 0.62 [0.42, 0.94] |
| 4.1 Sufficient | 2 | 1443 | Risk Ratio (Random, 95% CI) | 0.80 [0.57, 1.11] |
| 4.3 Unclear | 2 | 2017 | Risk Ratio (Random, 95% CI) | 0.52 [0.27, 1.02] |
| 5 Diarrhoea: cluster‐RCTs; subgrouped by water source | 4 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 5.1 Improved water source | 1 | 718 | Risk Ratio (Random, 95% CI) | 0.64 [0.39, 1.05] |
| 5.2 Unimproved water source | 3 | 2742 | Risk Ratio (Random, 95% CI) | 0.62 [0.38, 1.02] |
| 6 Diarrhoea: cluster‐RCTs; subgrouped by sanitation level | 4 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 6.1 Improved sanitation | 0 | 0 | Risk Ratio (Random, 95% CI) | 0.0 [0.0, 0.0] |
| 6.2 Unimproved sanitation | 2 | 1653 | Risk Ratio (Random, 95% CI) | 0.57 [0.24, 1.39] |
| 6.3 Unclear | 2 | 1807 | Risk Ratio (Random, 95% CI) | 0.72 [0.63, 0.83] |
| 7 Diarrhoea: cluster‐RCTs; subgrouped by length of follow‐up | 4 | 3460 | Risk Ratio (Random, 95% CI) | 0.62 [0.42, 0.94] |
| 7.2 > 6 to 12 months | 3 | 2371 | Risk Ratio (Random, 95% CI) | 0.59 [0.32, 1.09] |
| 7.3 > 12 months | 1 | 1089 | Risk Ratio (Random, 95% CI) | 0.73 [0.63, 0.85] |
Comparison 6 POU: solar disinfection versus control, Outcome 4 Diarrhoea: cluster‐RCTs; subgrouped by sufficiency of water supply level.
Comparison 6 POU: solar disinfection versus control, Outcome 5 Diarrhoea: cluster‐RCTs; subgrouped by water source.
Comparison 6 POU: solar disinfection versus control, Outcome 6 Diarrhoea: cluster‐RCTs; subgrouped by sanitation level.
Comparison 6 POU: solar disinfection versus control, Outcome 7 Diarrhoea: cluster‐RCTs; subgrouped by length of follow‐up.
Comparison 7
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: cluster‐RCT | 1 | Risk Ratio (Random, 95% CI) | Subtotals only |
Comparison 8
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1 Diarrhoea: cluster‐RCTs: subgrouped by age | 2 | Risk Ratio (Random, 95% CI) | Subtotals only | |
| 1.1 All ages | 2 | Risk Ratio (Random, 95% CI) | 0.91 [0.74, 1.11] | |
| 1.2 < 5 | 1 | Risk Ratio (Random, 95% CI) | 0.69 [0.47, 1.01] |
Characteristics of studies
Characteristics of included studies [ordered by study ID]
| Methods | RCT | |
| Participants | Number: 74 individuals Inclusion criteria: 18 years or older, receiving anti‐retroviral therapy for at least 6 months | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural South Africa Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Permuted block randomization system. |
| Allocation concealment (selection bias) | Low risk | Permuted block randomization system. |
| Comparability of characteristics | Unclear risk | Not described. |
| Contemporaneous data collection | Unclear risk | Not described. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | > 20% loss to follow‐up. |
| Methods | Quasi‐RCT | |
| Participants | Number: 623 children Inclusion criteria: households with children aged 6 to 23 months | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 5 political subunits in a village in rural Bangladesh Length: 3 years Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrevelant to study design. |
| Allocation concealment (selection bias) | Low risk | Irrevelant to study design. |
| Comparability of characteristics | Low risk | No substantial differences at baseline. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrevelant to study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrevelant to study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrevelant to study design. |
| Methods | RCT | |
| Participants | Number: 287 children Inclusion criteria: households with children aged 25 to 60 months (group B) from villages primarily using open, shallow wells for drinking water | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 22 rural villages in The Gambia Length: 20 weeks Publication status: PhD dissertation | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number table. |
| Allocation concealment (selection bias) | Low risk | Numbers assigned to villages. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 89.4% of participants included in analysis. |
| Methods | See Austin 1993a GMB | |
| Participants | Number: 144 children between 6 and 24 months Inclusion criteria: as above | |
| Interventions | As above | |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number table. |
| Allocation concealment (selection bias) | Low risk | Numbers assigned to villages. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 89.4% of participants included in analysis. |
| Methods | RCT | |
| Participants | Number: 196 children under 5, 1516 people, 313 households Inclusion criteria: householders were eligible to participate in the study if (i) at least one member of the household worked away from home during the day in a setting without adequate water supply, and (ii) the household was not already practicing an effective POU water treatment method | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Oromia, Ethiopia Length: 5 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Lottery used to randomly allocate eligible households into intervention and control groups. |
| Allocation concealment (selection bias) | Low risk | Lottery used to randomly allocate eligible households into intervention and control groups. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 4% of person‐weeks data lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 190 children under 5, 1144 people, 240 households Inclusion criteria: unimproved water sources that tested over 1000 thermotolerant coliforms (TTC)/100 ml, reported low use of household water treatment, were easily accessible all year round and were motivated to take part in the project | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural eastern province of Kasai, Democratic Republic of Congo Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator. |
| Allocation concealment (selection bias) | Low risk | "Randomisation was stratified by village and was conducted by the trial manager who played no part in the collection of the data". |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Double‐blinded; however filters removed turbidity, so controls were not always successfully blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Double‐blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 18.2% person‐weeks missing due to families moving out of study area, or not being home at time of visit. |
| Methods | RCT | |
| Participants | Number: 2986 children under 5, 12,454 people, 2163 households Inclusion criteria: households were eligible if there was at least one child under 5, and they lived permanently in the study area | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: informal settlements of Orissa, India Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | "The randomisation list was generated using Stata 10 and was conducted by the trial manager who played no part in the collection of the data". |
| Allocation concealment (selection bias) | Low risk | "The randomisation list was generated using Stata 10 and was conducted by the trial manager who played no part in the collection of the data". |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | "The active and placebo tablets were packaged in identical boxes of three strips containing ten tablets each". |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | "The labeling of the boxes was conducted by members of staff who were neither involved in the implementation nor data collection or analysis". |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 12% days of observation lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 239 children under 5, 1196 people, 180 households (across both interventions) Inclusion criteria: households were eligible if they stored drinking water at the household level, if they have at least one child under 5, and if the household was located in the study village | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Kandal Province, Cambodia Length: 18 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random numbers table. |
| Allocation concealment (selection bias) | Low risk | Households were approached in group‐randomized order. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 2% households lost to follow‐up. |
| Methods | See Brown 2008a KHM | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random numbers table. |
| Allocation concealment (selection bias) | Low risk | Households were approached in group‐randomized order. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 2% households lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 3401 persons from 514 households Inclusion criteria: households with at least one child under 1 year | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 42 neighbourhood clusters in 12 rural villages in Guatemala Length: 13 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator used to assigned neighbourhoods to intervention or control group. |
| Allocation concealment (selection bias) | Low risk | Random number generator used to assigned neighbourhoods to intervention or control group. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 8% of households lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 324 persons of all ages from 60 households Inclusion criteria: all households in the community | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Bolivian community Length: 9 months Publication status: unpublished | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Households were randomly allocated by names drawn from a hat in a public assembly. |
| Allocation concealment (selection bias) | Low risk | Households were randomly allocated by names drawn from a hat in a public assembly. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | No participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 50 households with 280 persons, of which 32 (11%) were under age 5 Inclusion criteria: all households in the community | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Bolivia Length: 6 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Households were randomly allocated by lottery, half to an intervention group and half to a control group. |
| Allocation concealment (selection bias) | Low risk | Households were randomly allocated by lottery, half to an intervention group and half to a control group. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 1% participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 140 children under 5, 680 people, 140 households Inclusion criteria: all households in the community | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: three rural villages in Colombia Length: six months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Public lottery. |
| Allocation concealment (selection bias) | Low risk | Lottery conducted at each study site to randomly allocate households. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 5% of households lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 236 people from 77 households Inclusion criteria: families were required to own their own homes, use municipal tap water as their main drinking water and have no seriously immunocompromised household members | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: urban community in California, USA Length: 4 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Two random sequences generated to allocated households to intervention or control groups. |
| Allocation concealment (selection bias) | Low risk | Two random sequences generated to allocated households to intervention or control groups. |
| Comparability of characteristics | Unclear risk | Irrelevant to study design. |
| Contemporaneous data collection | Unclear risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | One investigator, not involved in analyses prepared coded labels for the placebo and active devices. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Triple‐blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 1% households lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 50 HIV+ people, all over 30 years Inclusion criteria: confirmed HIV+ status, uses tap water 75% of the time, no children residing in the home | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: San Francisco, USA Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Computer generated random numbers. |
| Allocation concealment (selection bias) | Low risk | The manufacturer provided a list of device serial numbers and their corresponding active/sham status to facilitate device assignment. All study participants, the study investigators (including clinic personnel and those performing data analysis) and the device installer were blinded throughout the trial as to device assignment. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | All study participants, the study investigators (including clinic personnel and those performing data analysis) and the device installer were blinded throughout the trial as to device assignment. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | All study participants, the study investigators (including clinic personnel and those performing data analysis) and the device installer were blinded throughout the trial as to device assignment. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 10% participants withdrew from study (mixed from active and sham devices). |
| Methods | Randomized controlled (crossover) trial | |
| Participants | Number: 988 people, 714 households Inclusion criteria: households were eligible if they had one or more persons 55 or older | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: Sonoma County, USA Length: 13.5 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Households were block‐randomized in blocks of 10, with an equal probability of receiving either a sham or an active device. |
| Allocation concealment (selection bias) | Low risk | Households were block‐randomized in blocks of 10, with an equal probability of receiving either a sham or an active device. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | All study staff involved in installation and contact with participants were blinded to device assignments throughout the trial. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Assessors blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | "Among households initially assigned to receive an active device, 89% completed cycle 1 and 83% also completed cycle 2; among households initially assigned to receive a sham device, 90% completed cycle 1 and 82% also completed cycle 2". |
| Methods | RCT | |
| Participants | Number: 206 Maasai children aged 5 to 16 years in 3 adjoining areas of single province Inclusion criteria: all households in the village | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: single province of rural Kenya Length: 12 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Interventions assigned by alternate household. |
| Allocation concealment (selection bias) | High risk | Interventions assigned by alternate household. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | No loss to follow‐up. |
| Methods | RCT | |
| Participants | Number: 349 Maasai children < 6 years in 140 households Inclusion criteria: all households in the village | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Kenya Length: 1 year Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Interventions assigned by alternate household. |
| Allocation concealment (selection bias) | High risk | Interventions assigned by alternative household. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | > 20% children lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 6650 persons of all ages in 604 family compounds Inclusion criteria: family compounds with at least 1 child < 2 years and likely to be using highly turbid source water | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 49 rural villages in western Kenya Length: 20 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | Insufficient detail. |
| Allocation concealment (selection bias) | Unclear risk | Insufficient detail. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 82% participants lost to follow‐up. |
| Methods | See Crump 2005a KEN | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | Insufficient detail. |
| Allocation concealment (selection bias) | Unclear risk | Insufficient detail. |
| Comparability of characteristics | Low risk | Irrelevant to study design, |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 82% participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 2191 persons of all ages (1138 intervention, 1053 controls), of which 735 are children < 5 (395 intervention, 340 controls) Inclusion criteria: households in settlement area not using treated water for drinking | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: Liberian camp for displaced persons Length: 12 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random division of households by blocks and subsections. |
| Allocation concealment (selection bias) | Low risk | Households were systematically selected based on their assigned plot number. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 1% of households lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 115 children < 5 years Inclusion criteria: households were randomly selected from a list of eligible households from an earlier study: if they had no in‐house piped water, and if they had at least one child 12 to 24 months of age | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural South Africa and Zimbabwe Length: 6 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | Reported to be randomized, but no description of method of randomization process. |
| Allocation concealment (selection bias) | Unclear risk | Insufficient detail. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Unclear risk | Insufficient detail. |
| Methods | RCT | |
| Participants | Number: 824 children, 649 households Inclusion criteria: households were eligible if they had no in‐house piped water, and if they had at least one child over 6 months and under 5 years. | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: four peri‐urban districts of Gauteng Province, South Africa Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number table. |
| Allocation concealment (selection bias) | Low risk | This table was not available to field workers until after the sample frame was drawn up. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 13% of children lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 1089 children, 765 households Inclusion criteria: eligible households stored water in containers in‐house, did not have a drinking water tap in the house or yard, and had at least one child (but not more than 5) between 6 months and 5 years old residing in the house. | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: three urban slums, three rural areas near Nakuru, Kenya\ Length: 17 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random numbers between zero and one were generated and allocated to the households. If the random number allocated to a household was less than 0.5 the household was randomized to the test group. If the allocated number was above 0.5 the house was randomized to the control group. |
| Allocation concealment (selection bias) | Low risk | Field workers were unaware of how the numbers were allocated. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 4% children lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 230 children < 5, 1020 people, 178 households Inclusion criteria: households were eligible if they had a least one child under 5, did not have year‐round access to piped water, and did not use bottled water | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 11 rural communities in Copan, Honduras Length: six month follow‐up Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generation. |
| Allocation concealment (selection bias) | Low risk | No one knew which group they were assigned to until the day before. |
| Comparability of characteristics | Low risk | Irrelevant to this study design. |
| Contemporaneous data collection | Low risk | Irrelevant to this study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 1% lost to follow‐up. |
| Methods | Quasi‐RCT | |
| Participants | Number: 150 children < 5 years Inclusion criteria: all households with at least one child < 5 | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Rwanda Length: 24 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant to study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant to study design. |
| Comparability of characteristics | Unclear risk | Not described. |
| Contemporaneous data collection | Unclear risk | Not described. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant to study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant to study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant to study design. |
| Methods | RCT | |
| Participants | Number: 1916 people, 444 households Inclusion criteria: households were eligible if they did not have access to centrally treated drinking water and collected water from local sources year‐round | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Baja California Sur, Mexico Length: 15 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Eligible communities assigned a random number between zero and one by an investigator using STATA. |
| Allocation concealment (selection bias) | Low risk | Every 2 months another community was randomly allocated to intervention group; no one knew in advance. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 15% participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 364 intervention households; 347 control households Inclusion criteria: all households in intervention villages | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Benin Length: 3 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | Insufficient detail. |
| Allocation concealment (selection bias) | Unclear risk | Insufficient detail. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 64% of sample with follow‐up data (due to budgetary constraints). |
| Methods | RCT | |
| Participants | Number: 447 children aged 3 to 60 months from 276 households Inclusion criteria: households with children 3 to 60 months of age using municipal water (household taps) as primary source of drinking water which had tested positive at baseline for E. coli | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: informal settlement in urban Bangladesh Length: 8 months Publication status: PhD dissertation | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Lottery. |
| Allocation concealment (selection bias) | Low risk | Consent was obtained from participating households; none knew whether they would be placed into the intervention or comparison group. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 8% participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 549 children under five, 3240 individuals, 240 households Inclusion criteria: households were eligible if there was at least one child < 5 | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: peri‐urban communities of Tamale, Ghana Length: 12 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number table. |
| Allocation concealment (selection bias) | Low risk | Only technical staff at Medentech, Ltd knew which tablets were placebo and which were NaDCC. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Triple blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Triple blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 1% of households lost to follow‐up. |
| Methods | Quasi‐RCT | |
| Participants | Number: 226 children < 5 years of age Inclusion criteria: all households that had children aged less than five years and that primarily obtained drinking‐water from the water supply systems | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 2 villages in Pakistan Length: 6 months Publication status: journal Controlled for sanitation and water storage status of households, and for seasonality | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant to study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant to study design. |
| Comparability of characteristics | Low risk | Water quality at baseline significantly different between intervention and control villages. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant to study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant to study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant to study design. |
| Methods | RCT | |
| Participants | Number: 112 persons (all ages) from 20 families Inclusion criteria: households with at least 2 children living at home and using water from pond exclusively | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Brazil Length: 18 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | High risk | Sequences could be related to outcomes (eligible households which agreed to participate were enrolled). |
| Allocation concealment (selection bias) | High risk | Sequences could be related to outcomes (eligible households which agreed to participate were enrolled). |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Study staff and participants blinded (placebo). |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | Approximately 20% participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 184 springs; 1354 households Inclusion criteria: springs that were not seasonally dry, landownder gave approval to be protected | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural western Kenya Length: 2 years Publication status: economics quarterly journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator assigned springs into year of treatment. |
| Allocation concealment (selection bias) | Low risk | Random selection of households at each intervention spring. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 95% of all households were surveyed for baseline and at least two follow‐up rounds. |
| Methods | RCT | |
| Participants | Number: 330 intervention households; 279 control households Inclusion criteria: households: with children less than 60 months of age, in squatter or low‐income rental housing, receive their primary drinking/household water from a non‐municipal source, and no access to a direct municipal sewer line. Enrollment was limited to one child per household | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Bolivia Length: 3 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator. |
| Allocation concealment (selection bias) | Low risk | Randomization done at neighbourhood level. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | > 20% lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 285 intervention households; 279 control households Inclusion criteria: as above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator. |
| Allocation concealment (selection bias) | Low risk | Randomization done at neighbourhood level. |
| Comparability of characteristics | Low risk | Irrelevant to study design. |
| Contemporaneous data collection | Low risk | Irrelevant to study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | > 20% lost to follow‐up. |
| Methods | Quasi‐RCT | |
| Participants | Number: 2365 persons < 15 years from 285 households Inclusion criteria: eligible households included at least one child less than five years of age and two children less than 15 years of age, had sufficient water supply for the children to bathe daily, and planned to continue to reside in their homes for at least the ensuing four months. | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 3 neighbourhoods in squatter settlements in Karachi, Pakistan Length: 6 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant for study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant for study design. |
| Comparability of characteristics | Low risk | Baseline characteristics did not differ significantly between groups. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant for study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant for study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant for study design. |
| Methods | See Luby 2004a PAK | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant for study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant for study design. |
| Comparability of characteristics | Low risk | No substantial differences at baseline. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant for study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant for study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant for study design. |
| Methods | RCT | |
| Participants | Number: 5520 persons of all ages Inclusion criteria: running water at least one hour twice a week and at least one child under 5 | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 47 squatter settlements of Karachi, Pakistan Length: 8 months Publication status: unpublished | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Computer‐generated random number assigned households to groups. |
| Allocation concealment (selection bias) | Low risk | Households consented to study before computer randomly assigned them to specific groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Overall less than 8% of participants lost to follow‐up (averaged across all groups). |
| Methods | See Luby 2006a PAK | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Computer‐generated random number assigned households to groups. |
| Allocation concealment (selection bias) | Low risk | Households consented to study before computer randomly assigned them to specific groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Overall less than 8% of participants lost to follow‐up (averaged across all groups). |
| Methods | See Luby 2006a PAK | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Computer‐generated random number assigned households to groups. |
| Allocation concealment (selection bias) | Low risk | Households consented to study before computer randomly assigned them to specific groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Overall less than 8% of participants lost to follow‐up (averaged across all groups). |
| Methods | RCT | |
| Participants | Number: 2201 persons of all ages among 458 households Inclusion criteria: households without access to chlorinated municipal water; at least 1 resident of each household was HIV+ | |
| Interventions |
Note: hygiene education was provided to both groups | |
| Outcomes |
| |
| Notes | Location: households in rural Uganda Length: 5 months Publication status: unpublished Succeeded by 18‐month RCT that included cotrimoxazole prophylaxis | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | Insufficient detail. |
| Allocation concealment (selection bias) | Unclear risk | Insufficient detail. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 8% of participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 311 children < 5 years (among intervention households, among controls) among 171 families Inclusion criteria: households with at least one child less than 5 years of age | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 9 villages in rural Saudi Arabia Length: 6 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | No description of randomization process (for villages). No description of how households were chosen. |
| Allocation concealment (selection bias) | Unclear risk | No description of how chosen families were selected or contacted |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded |
| Incomplete outcome data (attrition bias) All outcomes | High risk | Large loss to follow‐up in intervention and control groups |
| Methods | Quasi‐RCT | |
| Participants | Number: community 1, 234 individuals; community 2, 173 individuals; reference community, 146 individuals Inclusion criteria: new community level piped water supply | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural, remote communities, Limpopo Province, South Africa Length: approximately 10 months of follow‐up Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant for study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant for study design. |
| Comparability of characteristics | Low risk | No substantial differences at baseline. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant for study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant for study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant for study design. |
| Methods | RCT | |
| Participants | Number: 964 children in 782 households Inclusion criteria: households were eligible if they were permanent residents in the area, had at least one child 6 months to 5 years old, and did not use other methods of household water treatment | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural communities in Prey Veng and Svey Rieng provinces, Cambodia Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Randomized raffle system of interested households during initial meeting. |
| Allocation concealment (selection bias) | Low risk | Households were randomly allocated to intervention or control groups at community meeting. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessor not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 5% of participants had less than 10 months of follow‐up. |
| Methods | RCT | |
| Participants | Number: 36 clusters, 569 households, 845 children < 5 Inclusion criteria: households were eligible if they had at least one child < 5 | |
| Interventions | Chlorine disinfection (WaterGuard) (427 children < 5) Primary drinking supply (422 children < 5) | |
| Outcomes | Diarrhoeal episodes for children < 5 Intervention compliance | |
| Notes | Location: rural communities, Kersa district, Ethiopia Length: 16 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Computer generated random sample. |
| Allocation concealment (selection bias) | Low risk | Randomization of clusters done in community meeting. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 2% to 3% of person‐weeks of observation lost. |
| Methods | RCT | |
| Participants | Number: 484 households, 819 children < 5 Inclusion criteria: communities had to have at least 30 children < 5 and rely on contaminated drinking water sources | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Totora District, Cochabamba Department, Bolivia Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random assignment during public event. |
| Allocation concealment (selection bias) | Low risk | Balls with community codes inscribed on them were drawn from a box; the first ball drawn would be the intervention community. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 21% of person‐days of observation missing. |
| Methods | RCT | |
| Participants | Number: 553 households, 4507 individuals Inclusion criteria: inadequate access to improved water sources; high areas of diarrhoeal disease according to 2004 census | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural communities, Wardak province, Afghanistan Length: 16 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Randomly allocated. |
| Allocation concealment (selection bias) | Low risk | Randomly allocated by numbered lists. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 10% of households data missing at follow‐up. |
| Methods | See Opryszko 2010a AFG | |
| Participants | Number: 600 households, 4,966 individuals Inclusion criteria: inadequate access to improved water sources; high areas of diarrhoeal disease according to 2004 census | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Randomly allocated. |
| Allocation concealment (selection bias) | Low risk | Randomly allocated by numbered lists. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 10% of households data missing at follow‐up. |
| Methods | See Opryszko 2010a AFG | |
| Participants | Number: 591 households, 4575 individuals Inclusion criteria: inadequate access to improved water sources; high areas of diarrhoeal disease according to 2004 census | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Randomly allocated. |
| Allocation concealment (selection bias) | Low risk | Randomly allocated by numbered lists. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 10% of households data missing at follow‐up. |
| Methods | RCT | |
| Participants | Number: 42 schools Inclusion criteria: schools were eligible if they were not near urban centres and did not have pre‐existing water‐treatment promotion activities | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural Nyanza province, Kenya Length: 2 years Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random allocation from census list. |
| Allocation concealment (selection bias) | Low risk | Random allocation from census list. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 32% students lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 120 households, 599 individuals, 121 children < 2 Inclusion criteria: mothers who disclosed their HIV status, had a child 6‐12 months old, and permanently resided in the catchment area | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: two peri‐urban neighbourhoods, Chongwe district, Zambia Length: 12 month Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator. |
| Allocation concealment (selection bias) | Low risk | Randomization conducted by person not involved in study. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | More than 80% of person‐weeks of observation completed. |
| Methods | RCT | |
| Participants | Number: 791 persons of all ages from 127 households Inclusion criteria: all households in the community | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 2 peri‐urban communities in Bolivia Length: 5 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Randomized by public lottery into two groups. |
| Allocation concealment (selection bias) | Low risk | Randomized by public lottery into two groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 10% of participants lost to follow‐up. |
| Methods | Quasi‐RCT | |
| Participants | Number: 1584 persons of all ages from 260 households Inclusion criteria: lack of piped water and presence of health clinic in community | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 2 peri‐urban communities in Zambia Length: 3 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant for study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant for study design. |
| Comparability of characteristics | Low risk | No substantial differences at baseline. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant for study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant for study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant for study design. |
| Methods | RCT | |
| Participants | Number: 492 households Inclusion criteria: household with a child < 12 months or mother in last trimester of pregnancy | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 12 villages in rural Guatemala Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Allocation concealment (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | Approximately 13% of participants lost to follow‐up. |
| Methods | See Reller 2003a GTM | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Allocation concealment (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | Approximately 13% of participants lost to follow‐up. |
| Methods | See Reller 2003a GTM | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Allocation concealment (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | Approximately 13% of participants lost to follow‐up. |
| Methods | See Reller 2003a GTM | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Allocation concealment (selection bias) | Low risk | Random number generator assigned eligible households to groups. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | Approximately 13% of participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 1160 persons of all ages; of these, 208 were children < 5 years Inclusion criteria: all households in refugee camp | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: Malawi refugee camp Length: 4 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | High risk | "One fourth of the interviewed households were selected at random to receive the improved buckets". |
| Allocation concealment (selection bias) | High risk | "One fourth of the interviewed households were selected at random to receive the improved buckets". |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 88.8% of participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 300 households, 1352 individuals, 185 children < 5 Inclusion criteria: households were eligible if they use untreated rainwater as their primary drinking source | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: Adelaide, Australia Length: 12 months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number sequence by independent researcher. |
| Allocation concealment (selection bias) | Low risk | Random number sequence by independent researcher. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Sham device (placebo) utilised. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | High risk | 31% households lost to follow‐up. |
| Methods | RCT | |
| Participants | Number and inclusion criteria: 1583 persons of all ages from 240 households, half with access to piped water (first control group) and half without (of which 62 received intervention, and 58 served as a second control group); these included 344 children < 5 | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: urban Uzbekistan Length: 9.5 weeks Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Households randomly selected from map of neighbourhoods. |
| Allocation concealment (selection bias) | Low risk | Households randomly selected from map of neighbourhoods. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Unclear risk | Lost to follow‐up not discussed. |
| Methods | RCT | |
| Participants | Number: 167 households, 907 individuals, 243 children < 5 Inclusion criteria: households were eligible if there was no biosand filter in the house, and there was at least one child < 5 | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: one semi‐rural and one urban community, Bonao, Dominican Republic Length: six months follow‐up Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generation assigned 50% of households to intervention group. |
| Allocation concealment (selection bias) | Unclear risk | Households were unaware of whether they would be assigned to the intervention or control group until one week before BSF installation, but it is not clear whether this was foreknowledge of group assignment. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 7% participants lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 189 households, 1147 individuals, 242 children < 5 Inclusion criteria: households were eligible if there was at least one child < 5 | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 13 rural communities, Angk Snoul district, Cambodia Length: four months follow‐up Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generation assigned 7 of 13 villages to intervention group. |
| Allocation concealment (selection bias) | Low risk | All villages were told they would not know to which group they were assigned until halfway through the study (due to surveillance period, pre‐intervention). |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | 4% of person‐observation weeks missing. |
| Methods | RCT | |
| Participants | Number: 2043 individuals, of which 440 were children < 5, from 260 households Inclusion criteria: households were eligible if there was at least one child < 5 | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: six rural communities, Tamale, Ghana Length: three months follow‐up Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Random number generator assigned 3 of the 6 villages to the intervention group. |
| Allocation concealment (selection bias) | Unclear risk | Not discussed. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Less than 3% of households lost to follow‐up. |
| Methods | RCT | |
| Participants | Number: 387 individuals, of which 114 were children < 5, from 60 households Inclusion criteria: households were eligible if they had at least one child < 3, used river water as their primary or secondary drinking water source, stable residence for next 12 months, and indicators of lower socio‐economic status | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: rural households in River Njoro watershed, Nakuru and Molo districts, Kenya Length: six months Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | No description of randomization process. |
| Allocation concealment (selection bias) | Unclear risk | No description of steps to conceal allocation. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | After randomization, 75 (93%) and 79 (92%) of BSF and control households, respectively, completed the study. |
| Methods | Quasi‐RCT | |
| Participants | Number: 2103 persons of all ages from 2 villages Inclusion critera: all households within 2 villages | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 2 small villages in Guatemala Length: 12 months Publication status: book | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant for study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant for study design. |
| Comparability of characteristics | Low risk | No substantial differences at baseline. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant for study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant for study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant for study design. |
| Methods | RCT | |
| Participants | Number: 1120 children < 5 years (265 and 289 allocated to the water quality intervention arms, 297 to an education only arm, and 269 to the control arm) from 680 families from three demographic regions Inclusion criteria: households must have children <5 and have indicators of low socio‐economic status and microbiological contamination of water source | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 3 demographic regions of Guatemala Length: 12 months Publication status: unpublished | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | Reported to be randomized, but no description of method of randomization process. |
| Allocation concealment (selection bias) | Unclear risk | No description of allocation concealment. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | Participants not blinded. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Unclear risk | Not discussed. |
| Methods | See URL 1995a GTM | |
| Participants | As above | |
| Interventions |
| |
| Outcomes | As above | |
| Notes | As above | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk | Reported to be randomized, but no description of method of randomization process. |
| Allocation concealment (selection bias) | Unclear risk | No description of allocation concealment. |
| Comparability of characteristics | Low risk | Irrelevant for study design. |
| Contemporaneous data collection | Low risk | Irrelevant for study design. |
| Blinding of participants and personnel (performance bias) All outcomes | High risk | No placebo used. |
| Blinding of outcome assessment (detection bias) All outcomes | High risk | Assessors not blinded. |
| Incomplete outcome data (attrition bias) All outcomes | Unclear risk | Not discussed. |
| Methods | Quasi‐RCT | |
| Participants | Number: 4649 people of all ages Inclusion criteria: all households within villages | |
| Interventions |
| |
| Outcomes |
| |
| Notes | Location: 2 villages in rural China Length: 3 years Publication status: journal | |
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Low risk | Irrelevant for study design. |
| Allocation concealment (selection bias) | Low risk | Irrelevant for study design. |
| Comparability of characteristics | Low risk | No substantial differences at baseline. |
| Contemporaneous data collection | Low risk | Data collected at similar points in time. |
| Blinding of participants and personnel (performance bias) All outcomes | Low risk | Irrelevant for study design. |
| Blinding of outcome assessment (detection bias) All outcomes | Low risk | Irrelevant for study design. |
| Incomplete outcome data (attrition bias) All outcomes | Low risk | Irrelevant for study design. |
Characteristics of excluded studies [ordered by study ID]
| Study | Reason for exclusion |
|---|---|
| Ahoyo 2011 | Allocation was neither randomized nor quasi‐randomized. |
| Aiken 2011 | Allocation was neither randomized nor quasi‐randomized. |
| Alexander 2013 | Outcome measures did not include diarrhoea. |
| Arnold 2009 | Allocation was neither randomized nor quasi‐randomized. |
| Arnold 2012a | Comment paper. |
| Arnold 2013 | Design paper. |
| Asaolu 2002 | Allocation was neither randomized nor quasi‐randomized; outcome measures did not include diarrhoea. |
| Aziz 1990 BGD | The intervention included the provision of sanitation facilities. |
| Azurin 1974 | Outcome measures did not include diarrhoea. |
| Bahl 1976 | Allocation was neither randomized nor quasi‐randomized. |
| Bajer 2012 | Allocation was neither randomized nor quasi‐randomized, outcome not diarrhoea. |
| Barreto 2007 | Allocation was neither randomized nor quasi‐randomized. |
| Barzilay 2011 | Allocation was neither randomized nor quasi‐randomized. |
| Bersh 1985 | Allocation was neither randomized nor quasi‐randomized. |
| Boubacar 2014 | Allocation was neither randomized nor quasi‐randomized. |
| Brown 2012a | Modelling paper. |
| Capuno 2011 | Allocation was neither randomized nor quasi‐randomized. |
| Cavallaro 2011 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Chang 2012 | Outcomes did not include diarrhoea. |
| Chongsuvivatwong 1994 | Allocation was neither randomized nor quasi‐randomized. |
| Christen 2011 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Clasen 2012 | No water quality intervention. |
| Colford 2005 | Outcomes did not include diarrhoea. |
| Colwell 2003 | Outcomes did not include diarrhoea. |
| Conroy 2001 | Outcomes did not include diarrhoea. |
| Coulliette 2013 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Crump 2007 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Davis 2011 | Outcomes did not include diarrhoea. |
| Deb 1986 | Outcomes did not include diarrhoea. |
| Denslow 2010 | Allocation was neither randomized nor quasi‐randomized. |
| Devoto 2011 | Intervention did not affect water quality. |
| Dorevitch 2011 | Outcomes did not include diarrhoea. |
| Dreibelbis 2014a KEN | School‐based study. |
| Dreibelbis 2014b KEN | School‐based study. |
| Dreibelbis 2014c KEN | School‐based study. |
| du Preez 2012 | Response to comments. |
| Eisenberg 2006 | Study on risk assessment. |
| Enger 2012 | Modelling paper. |
| Esrey 1988 | Allocation was neither randomized nor quasi‐randomized. |
| Fewtrell 1994 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Fewtrell 1997 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Firth 2010 | Outcomes did not include diarrhoea. |
| Fisher 2011 | Allocation was neither randomized nor quasi‐randomized. |
| Freeman 2012 | Outcomes did not include diarrhoea. |
| Freeman 2014a KEN | School‐based study. |
| Freeman 2014b KEN | School‐based study. |
| Freeman 2014c KEN | School‐based study. |
| Fry 2010 | Modelling paper. |
| Galiani 2009 | Allocation was neither randomized nor quasi‐randomized |
| Garrett 2008 KEN | The intervention included the provision of sanitation facilities. |
| Ghannoum 1981 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Gorelick 2011 | Allocation was neither randomized nor quasi‐randomized. |
| Greene 2012 | Outcome not diarrhoea, see Freeman 2012. |
| Gómez‐Couso 2012 | Allocation was neither randomized nor quasi‐randomized, outcome not diarrhoea. |
| Habib 2013 | Water quality intervention applied once children had experienced diarrhoea. |
| Harris 2009 | Allocation was neither randomized nor quasi‐randomized. |
| Harshfield 2012 | Allocation was neither randomized nor quasi‐randomized. |
| Hartinger 2011 | Design paper. |
| Hartinger 2012 | Outcome measures did not include diarrhoea. |
| Hellard 2001 | Outcome measures did not include diarrhoea. |
| Hoque 1996 | Allocation was neither randomized nor quasi‐randomized. |
| Huda 2012 | Allocation was neither randomized nor quasi‐randomized. |
| Hunter 2010 | Allocation was neither randomized nor quasi‐randomized |
| Iijima 2001 | Allocation was neither randomized nor quasi‐randomized. |
| Islam 2011 | Allocation was neither randomized nor quasi‐randomized. |
| Jensen 2002 | Outcome not diarrhoea. |
| Kariuki 2012 | Intervention not water. |
| Karon 2011 | Outcome not diarrhoea. |
| Keraita 2007 | Outcome not diarrhoea. |
| Khan 1984 | Outcome not diarrhoea. |
| Luby 2008 | Allocation was neither randomized nor quasi‐randomized. |
| Luoto 2011 | Outcome not diarrhoea. |
| Luoto 2012 | Outcome not diarrhoea. |
| Macy 1998 | Allocation was neither randomized nor quasi‐randomized; intervention not an improvement in water quality; outcome not diarrhoea. |
| McCabe 1957 | Intervention not an improvement in water quality. |
| Mertens 1990 | Allocation was neither randomized nor quasi‐randomized, intervention not an improvement in water quality; outcome not diarrhoea. |
| Messou 1997 | The intervention included the provision of sanitation facilities. |
| Mäusezahl 2003 | Allocation was neither randomized nor quasi‐randomized. |
| Nanan 2003 | Allocation was neither randomized nor quasi‐randomized. |
| Nerkar 2014 | Allocation was neither randomized nor quasi‐randomized. |
| Nnane 2011 | Allocation was neither randomized nor quasi‐randomized, no intervention. |
| Oluyege 2011 | Allocation was neither randomized nor quasi‐randomized, no intervention. |
| Palit 2012 | Allocation was neither randomized nor quasi‐randomized. |
| Pavlinac 2014 | Allocation was neither randomized nor quasi‐randomized. |
| Payment 1991a | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Payment 1991b | Outcomes did not include diarrhoea. |
| Peletz 2013 | Outcomes did not include diarrhoea. |
| Pinfold 1990 | Intervention not an improvement in water quality; outcome not diarrhoea. |
| Psutka 2012 | Allocation was neither randomized nor quasi‐randomized, outcomes did not include diarrhoea. |
| Rosa 2014 | Outcomes did not include diarrhoea. |
| Rose 2006 | Allocation was neither randomized nor quasi‐randomized. |
| Rubenstein 1969 | Allocation was neither randomized nor quasi‐randomized. |
| Russo 2012 | Allocation was neither randomized nor quasi‐randomized. |
| Sathe 1996 | Allocation was neither randomized nor quasi‐randomized. |
| Shah 2012 | Review paper. |
| Sharan 2011 | Allocation was neither randomized nor quasi‐randomized, outcome not diarrhoea. |
| Sheth 2010 | Allocation was neither randomized nor quasi‐randomized, outcome not diarrhoea. |
| Shiffman 1978 | Allocation was neither randomized nor quasi‐randomized. |
| Shrestha 2006 | Cost‐effectiveness paper. |
| Shum 1971 | Allocation was neither randomized nor quasi‐randomized, intervention not an improvement in water quality; outcome not diarrhoea. |
| Sima 2012 | Allocation was neither randomized nor quasi‐randomized. |
| Sorvillo 1994 | Outcomes did not include diarrhoea. |
| Stauber 2013 | Outcomes did not include diarrhoea. |
| Sutha 2011 | Review paper. |
| Tonglet 1992 | Allocation was neither randomized nor quasi‐randomized. |
| Trivedi 1971 | Allocation was neither randomized nor quasi‐randomized. |
| VanDerslice 1995 | Allocation was neither randomized nor quasi‐randomized, intervention not an improvement in water quality. |
| Varghese 2002 | Allocation was neither randomized nor quasi‐randomized. |
| Wiedenmann 2006 | Intervention not an improvement in water quality. |
| Wolf 2014 | Review. |
| Wood 2012 | Qualitative study. |
| Wu 2011 | Allocation was neither randomized nor quasi‐randomized. |
Characteristics of ongoing studies [ordered by study ID]
| Trial name or title | Impact of Low‐Cost In‐Line Chlorination Systems in Urban Dhaka on Water Quality and Child Health |
| Methods | RCT |
| Participants | All poor households, with at least one child under five, that access one of 160 studied shared water points in Dhaka. |
| Interventions | In‐line chlorination |
| Outcomes | Water quality, diarrhoea in children under five, weight of children, cost of instilling and maintaining system, hospital visits, health care expenditures, other household expenditures |
| Starting date | Early 2015 |
| Contact information | |
| Notes | Funded by SIEF, World Bank |
| Trial name or title | WASH Benefits Bangladesh: A Cluster Randomized Controlled Trial of the Benefits of Water, Sanitation, Hygiene Plus Nutrition Interventions on Child Growth |
| Methods | Parallel, cluster‐RCT |
| Participants | Estimated enrolment: 5040 |
| Interventions |
|
| Outcomes |
|
| Starting date | May 2012 |
| Contact information | International Centre for Diarrhoeal Disease Research, Bangladesh |
| Notes |
| Trial name or title | WASH‐Benefits study, Kenya |
| Methods | Parallel, cluster‐RCT |
| Participants | Estimated: 8000 |
| Interventions |
|
| Outcomes |
|
| Starting date | September 2012 |
| Contact information | Innovations for Poverty Action, Kenya |
| Notes |
Differences between protocol and review
Risk of bias has been assessed using GRADE rather than the original methods expressed in the protocol. Statistical methods have been used to pool odds ratios, rate ratios, RRs and longitudinal prevalence ratios. Subgrouping has been done separately for each water quality intervention, and additional subgrouping has been conducted based on study design and length of follow up. Data has been provided on adjustment of studies for non‐blinding.
Contributions of authors
TC and SC conceived the review. TC coordinated the review. TC, KA, SB, RP, HC, and SC designed the review. TC and authors of the initial review drafted the protocol. SB and Cochrane Infectious Diseases Group (CIDG) performed the search strategy. SB and RP screened search results. KA, SB, and RP retrieved papers. SB and RP applied inclusion criteria. KA, SB, and RP extracted data. KA, SB, RP, HC, and FM computed estimates of effect. KA, TC, FM, and DS applied quality criteria. KA contacted study authors for additional information. TC, KA, HC, DS, and CIDG addressed statistical issues. KA entered data into Review Manager (RevMan). TC, KA, and DS drafted the review. SB, RP, HC, and SC commented on the review. TC, KA, HC, FM, and DS prepared tables. KA prepared figures. TC is guarantor of this Cochrane Review.
Sources of support
Internal sources
- Liverpool School of Tropical Medicine, UK.
External sources
- Department for International Development (DFID), UK.
Declarations of interest
TC, KA, SB, and SC have provided research or consulting services for Unilever, Ltd., Medentech, Ltd., DelAgua Health and Science, Ltd., and Vestergaard‐Frandsen SA who manufacture or sell household‐based water treatment devices.
References
References to studies included in this review
Abebe 2014 ZAF {published data only}
- Abebe LS, Smith JA, Narkiewicz S, Oyanedel‐Craver V, Conaway M, Singo A, et al. Ceramic water filters impregnated with silver nanoparticles as a point‐of‐use water‐treatment intervention for HIV‐positive individuals in Limpopo Province, South Africa: a pilot study of technological performance and human health benefits. Journal of Water and Health 2014;12(2):288‐300. [PubMed] [Google Scholar]
Alam 1989 BGD {published data only}
- Alam N, Wojtyniak B, Henry FJ, Rahaman MM. Mothers' personal and domestic hygiene and diarrhoea incidence in young children in rural Bangladesh. International Journal of Epidemiology 1989;18(1):242‐7. [PubMed] [Google Scholar]
Austin 1993a GMB {unpublished data only}
- Austin CJ. Investigation of in‐house water chlorination and its effectiveness for rural areas of the Gambia [dissertation]. New Orleans: Tulane University School of Public Health and Tropical Medicine, 1993. [Google Scholar]
Austin 1993b GMB {unpublished data only}
- Austin CJ. Investigation of in‐house water chlorination and its effectiveness for rural areas of the Gambia [dissertation]. New Orleans: Tulane University School of Public Health and Topical Medicine, 1993. [Google Scholar]
Boisson 2009 ETH {published data only}
- Boisson S, Schmidt WP, Berhanu T, Gezahegn H, Clasen T. Randomized controlled trial in rural Ethiopia to assess a portable water treatment device. Environmental Science & Technology 2009;43(15):5934‐9. [PubMed] [Google Scholar]
Boisson 2010 DRC {published data only}
- Boisson S, Kiyombo M, Sthreshley L, Tumba S, Makambo J, Clasen T. Field assessment of a novel household‐based water filtration device: a randomised, placebo‐controlled trial in the Democratic Republic of Congo. PLoS One 2010;5(9):e12613. [PMC free article] [PubMed] [Google Scholar]
Boisson 2013 IND {published data only}
- Boisson S, Stevenson M, Shapiro L, Kumar V, Singh LP, Ward D, et al. Effect of household‐based drinking water chlorination on diarrhoea among children under five in Orissa, India: a double‐blind randomised placebo‐controlled trial. PLoS Medicine 2013;10(8):e1001497. [PMC free article] [PubMed] [Google Scholar]
Brown 2008a KHM {published data only}
- Brown J, Sobsey MD, Loomis D. Local drinking water filters reduce diarrheal disease in Cambodia: a randomized, controlled trial of the ceramic water purifier. American Journal of Tropical Medicine and Hygiene 2008;79(3):394‐400. [PubMed] [Google Scholar]
Brown 2008b KHM {published data only}
- Brown J, Sobsey MD, Loomis D. Local drinking water filters reduce diarrheal disease in Cambodia: a randomized, controlled trial of the ceramic water purifier. American Journal of Tropical Medicine and Hygiene 2008;79(3):394‐400. [PubMed] [Google Scholar]
Chiller 2006 GTM {published data only}
- Chiller TM, Mendoza CE, Lopez MB, Alvarez M, Hoekstra RM, Keswick BH, et al. Reducing diarrhoea in Guatemalan children: randomized controlled trial of flocculant‐disinfectant for drinking‐water. Bulletin of the World Health Organization 2006;84(1):28‐35. [PMC free article] [PubMed] [Google Scholar]
Clasen 2004b BOL {published and unpublished data}
- Clasen TF, Brown J, Collin SM. Preventing diarrhoea with household ceramic water filters: assessment of a pilot project in Bolivia. International Journal of Environmental Health Research 2006;16(3):231‐9. [PubMed] [Google Scholar]
Clasen 2004c BOL {published data only}
- Clasen TF, Brown J, Collin S, Suntura O, Cairncross S. Reducing diarrhea through the use of household‐based ceramic water filters: a randomized, controlled trial in rural Bolivia. American Journal of Tropical Medicine and Hygiene 2004;70(6):651‐7. [PubMed] [Google Scholar]
Clasen 2005 COL {published data only}
- Clasen T, Parra GG, Boisson S, Collin S. Household‐based ceramic water filters for the prevention of diarrhea: a randomized, controlled trial of a pilot program in Colombia. American Society of Tropical Medicine and Hygiene 2005;73(4):790‐5. [PubMed] [Google Scholar]
Colford 2002 USA {published data only}
- Colford JM Jr, Rees JR, Wade TJ, Khalakdina A, Hilton JF, Ergas IJ, et al. Participant blinding and gastrointestinal illness in a randomized, controlled trial of an in‐home drinking water intervention. Emerging Infectous Diseases 2002;8(1):29‐36. [PubMed] [Google Scholar]
Colford 2005 USA {published data only}
- Colford JM Jr, Saha SR, Wade TJ, Wright CC, Vu M, Charles S, et al. A pilot randomized, controlled trial of an in‐home drinking water intervention among HIV+ persons. Journal of Water and Health 2005;3(2):173‐84. [PubMed] [Google Scholar]
Colford 2009 USA {published data only}
- Colford JM Jr, Hilton JF, Wright CC, Arnold BF, Saha S, Wade TJ, et al. The Sonoma water evaluation trial: a randomized drinking water intervention trial to reduce gastrointestinal illness in older adults. American Journal of Public Health 2009;99(11):1988‐95. [PMC free article] [PubMed] [Google Scholar]
Conroy 1996 KEN {published data only}
- Conroy RM, Elmore‐Meegan M, Joyce T, McGuigan KG, Barnes J. Solar disinfection of drinking water and diarrhoea in Maasai children: a controlled field trial. Lancet 1996;348(9043):1695‐7. [PubMed] [Google Scholar]
Conroy 1999 KEN {published data only}
- Conroy RM, Meegan ME, Joyce T, McGuigan K, Barnes J. Solar disinfection of water reduces diarrhoeal disease: an update. Archives of Disease in Childhood 1999;81(4):337‐8. [PMC free article] [PubMed] [Google Scholar]
Crump 2005a KEN {published data only}
- Crump JA, Otieno PO, Slutsker L, Keswick BH, Rosen DH, Hoekstra RM, et al. Household based treatment of drinking water with flocculant‐disinfectant for preventing diarrhoea in areas with turbid source water in rural western Kenya: cluster randomised controlled trial. BMJ 2005;331(7515):478. [PMC free article] [PubMed] [Google Scholar]
Crump 2005b KEN {unpublished data only}
- Crump JA, Otieno PO, Slutsker L, Keswick BH, Rosen DH, Hoekstra RM, et al. Otieno PO, Slutsker L, Keswick BH, Rosen DH, Hoekstra RM, et al. Household based treatment of drinking water with flocculant‐disinfectant for preventing diarrhoea in areas with turbid source water in rural western Kenya: cluster randomised controlled trial. BMJ 2005;331(7515):478. [PMC free article] [PubMed] [Google Scholar]
Doocy 2006 LBR {published data only}
- Doocy S, Burnham G. Point‐of‐use water treatment and diarrhoea reduction in the emergency context: an effectiveness trial in Liberia. Tropical Medicine & International Health 2006;11(10):1542‐52. [PubMed] [Google Scholar]
du Preez 2008 ZAF/ZWE {published and unpublished data}
- du Preez M, Conroy RM, Wright JA, Moyo S, Potgieter N, Gundry SW. Use of ceramic water filtration in the prevention of diarrheal disease: a randomized controlled trial in rural South Africa and Zimbabwe. American Journal of Tropical Medicine and Hygiene 2008;79(5):696‐701. [PubMed] [Google Scholar]
du Preez 2010 ZAF {published data only}
- du Preez M, Mcguigan KG, Conroy RM. Solar disinfection of drinking water In the prevention of dysentery in South African children aged under 5 years: the role of participant motivation. Environmental Science & Technology 2010;44(22):8744‐9. [PubMed] [Google Scholar]
du Preez 2011 KEN {published data only}
- du Preez M, Conroy RM, Ligondo S, Hennessy J, Elmore‐Meegan M, Soita A, et al. Randomized intervention study of solar disinfection of drinking water in the prevention of dysentery in Kenyan children aged under 5 years. Environmental Science & Technology 2011;45(21):9315‐23. [PubMed] [Google Scholar]
Fabiszewski 2012 HND {published data only}
- Fabiszewski de Aceituno AM, Stauber CE, Walters AR, Meza Sanchez RE, Sobsey MD. A randomized controlled trial of the plastic‐housing BioSand filter and its impact on diarrheal disease in Copan, Honduras. American Journal of Tropical Medicine and Hygiene 2012;86(6):913‐21. [PMC free article] [PubMed] [Google Scholar]
Gasana 2002 RWA {published data only}
- Gasana J, Morin J, Ndikuyeze A, Kamoso P. Impact of water supply and sanitation on diarrheal morbidity among young children in the socioeconomic and cultural context of Rwanda (Africa). Environmental Research 2002;90(2):76‐88. [PubMed] [Google Scholar]
Gruber 2013 MEX {published data only}
- Gruber JS, Reygadas F, Arnold BF, Ray I, Nelson K, Colford JM Jr. A stepped wedge, cluster‐randomized trial of a household UV‐disinfection and safe storage drinking water intervention in rural Baja California Sur, Mexico. American Journal of Tropical Medicine and Hygiene 2013;89(2):238‐45. [PMC free article] [PubMed] [Google Scholar]
Günther 2013 BEN {published data only}
- Günther I, Schipper Y. Pumps, germs and storage: the impact of improved water containers on water quality and health. Health Economics 2013;22(7):757‐74. [PubMed] [Google Scholar]
Handzel 1998 BGD {published and unpublished data}
- Handzel T. The effect of improved drinking water quality on the risk of diarrhoeal disease in an urban slum of Dhakar, Bangladesh: a home chlorination intervention trial [dissertation]. Chapel Hill (NC): University of North Carolina at Chapel Hill, 1998. [Google Scholar]
- Sobsey MD, Handzel T, Venczel L. Chlorination and safe storage of household drinking water in developing countries to reduce waterborne disease. Water Science and Technology 2003;47(3):221‐8. [PubMed] [Google Scholar]
Jain 2010 GHA {published data only}
- Jain S, Sahanoon OK, Blanton E, Schmitz A, Wannemuehler KA, Hoekstra RM, et al. Sodium dichloroisocyanurate tablets for routine treatment of household drinking water in periurban Ghana: a randomized controlled trial. American Journal of Tropical Medicine and Hygiene 2010;82(1):16‐22. [PMC free article] [PubMed] [Google Scholar]
Jensen 2003 PAK {published data only}
- Jensen PK, Ensink JH, Jayasinghe G, Hoek W, Cairncross S, Dalsgaard A. Effect of chlorination of drinking‐water on water quality and childhood diarrhoea in a village in Pakistan. Journal of Health, Population, and Nutrition 2003;21(1):26‐31. [PubMed] [Google Scholar]
Kirchhoff 1985 BRA {published data only}
- Kirchhoff LV, McClelland KE, Do Carmo Pinho M, Araujo JG, Sousa MA, Guerrant RL. Feasibility and efficacy of in‐home water chlorination in rural North‐eastern Brazil. Journal of Hygiene 1985;94(2):173‐80. [PMC free article] [PubMed] [Google Scholar]
Kremer 2011 KEN {published and unpublished data}
- Kremer M, Leino J, Miguel E, Zwane AP. Spring cleaning: rural water impacts, valuation, and property rights institutions. Quarterly Journal of Economics 2011;126(1):145‐205. [PubMed] [Google Scholar]
Lindquist 2014a BOL {published data only}
- Lindquist ED, George CM, Perin J, Neiswender de Calani KJ, Norman WR, Davis TP Jr, et al. A cluster randomized controlled trial to reduce childhood diarrhea using hollow fiber water filter and/or hygiene–sanitation educational interventions. American Journal of Tropical Medicine and Hygiene 2014;91(1):190‐7. [PMC free article] [PubMed] [Google Scholar]
Lindquist 2014b BOL {published data only}
- Lindquist ED, George CM, Perin J, Neiswender de Calani KJ, Norman WR, Davis TP Jr, et al. A cluster randomized controlled trial to reduce childhood diarrhea using hollow fiber water filter and/or hygiene–sanitation educational interventions. American Journal of Tropical Medicine and Hygiene 2014;91(1):190‐7. [PMC free article] [PubMed] [Google Scholar]
Luby 2004a PAK {published data only}
- Luby SP, Agboatwalla M, Hoekstra RM, Rahbar MH, Billhimer W, Keswick BH. Delayed effectiveness of home‐based interventions in reducing childhood diarrhea, Karachi, Pakistan. American Journal of Tropical Medicine and Hygiene 2004;71(4):420‐7. [PubMed] [Google Scholar]
Luby 2004b PAK {published data only}
- Luby SP, Agboatwalla M, Hoekstra RM, Rahbar MH, Billhimer W, Keswick BH. Delayed effectiveness of home‐based interventions in reducing childhood diarrhea, Karachi, Pakistan. American Journal of Tropical Medicine and Hygiene 2004;71(4):420‐7. [PubMed] [Google Scholar]
Luby 2006a PAK {published and unpublished data}
- Luby SP, Agboatwalla M, Painter J, Altaf A, Billhimer W, Keswick B, et al. Combining drinking water treatment and hand washing for diarrhoea prevention, a cluster randomised controlled trial. Tropical Medicine & International Health 2006;11(4):479‐89. [PubMed] [Google Scholar]
Luby 2006b PAK {unpublished data only}
- Luby SP, Agboatwalla M, Painter J, Keswick B, Billhimer W, Altaf A, et al. Effect of a novel water treatment and handwashing promotion on childhood diarrhea in Pakistan: a randomized controlled trial. Tropical Medicine & International Health 2006;11(4):479‐89. [PubMed] [Google Scholar]
Luby 2006c PAK {unpublished data only}
- Luby SP, Agboatwalla M, Painter J, Keswick B, Billhimer W, Altaf A, et al. Effect of a novel water treatment and handwashing promotion on childhood diarrhea in Pakistan: a randomized controlled trial. Tropical Medicine & International Health 2006;11(4):479‐89. [PubMed] [Google Scholar]
Lule 2005 UGA {published data only}
- Lule JR, Mermin J, Ekwaru JP, Malamba S, Downing R, Ransom R, et al. Effect of home‐based water chlorination and safe storage on diarrhea among persons with human immunodeficiency virus in Uganda. American Journal of Tropical Medicine and Hygiene 2005;73(5):926‐33. [PubMed] [Google Scholar]
Mahfouz 1995 KSA {published data only}
- Mahfouz AA, Abdel‐Moneim M, al‐Erian RA, al‐Amari OM. Impact of chlorination of water in domestic storage tanks on childhood diarrhoea: a community trial in the rural areas of Saudi Arabia. American Journal of Tropical Medicine and Hygiene 1995;98(2):126‐30. [PubMed] [Google Scholar]
Majuru 2011 ZAF {published data only}
- Majuru B, Michael Mokoena M, Jagals P, Hunter PR. Health impact of small‐community water supply reliability. International Journal of Hygiene and Environmental Health 2011;214(2):162‐6. [PubMed] [Google Scholar]
Mäusezhal 2009 BOL {published data only}
- Mäusezahl D, Christen A, Pacheco GD, Tellez FA, Iriarte M, Zapata ME, et al. Solar Drinking Water Disinfection (SODIS) to reduce childhood diarrhoea in rural Bolivia: a cluster‐randomized, controlled trial. PLoS Medicine 2009;6(8):e1000125. [PMC free article] [PubMed] [Google Scholar]
McGuigan 2011 KHM {published data only}
- McGuigan KG, Samaiyar P, du Preez M, Conroy RM. High compliance randomized controlled field trial of solar disinfection of drinking water and its impact on childhood diarrhea in rural Cambodia. Environmental Science & Technology 2011;45(18):7862‐7. [PubMed] [Google Scholar]
Mengistie 2013 ETH {published data only}
- Mengistie B, Berhane Y, Worku A. Household water chlorination reduces incidence of diarrhea among under‐five children in rural Ethiopia: a cluster randomized controlled trial. PLoS One 2013;8(10):e77887. [PMC free article] [PubMed] [Google Scholar]
Opryszko 2010a AFG {published data only}
- Opryszko MC, Majeed SW, Hansen PM, Myers JA, Baba D, Thompson RE, et al. Water and hygiene interventions to reduce diarrhoea in rural Afghanistan: a randomized controlled study. Journal of Water and Health 2010;8(4):687‐702. [PubMed] [Google Scholar]
Opryszko 2010b AFG {published data only}
- Opryszko MC, Majeed SW, Hansen PM, Myers JA, Baba D, Thompson RE, et al. Water and hygiene interventions to reduce diarrhoea in rural Afghanistan: a randomized controlled study. Journal of Water and Health 2010;8(4):687‐702. [PubMed] [Google Scholar]
Opryszko 2010c AFG {published data only}
- Opryszko MC, Majeed SW, Hansen PM, Myers JA, Baba D, Thompson RE, et al. Water and hygiene interventions to reduce diarrhoea in rural Afghanistan: a randomized controlled study. Journal of Water and Health 2010;8(4):687‐702. [PubMed] [Google Scholar]
Patel 2012 KEN {published and unpublished data}
- Patel MK, Harris JR, Juliao P, Nygren B, Were V, Kola S, et al. Impact of a hygiene curriculum and the installation of simple handwashing and drinking water stations in rural Kenyan primary schools on student health and hygiene practices. American Journal of Tropical Medicine and Hygiene 2012;87(4):594‐601. [PMC free article] [PubMed] [Google Scholar]
Peletz 2012 ZMB {published data only}
- Peletz R, Simunyama M, Sarenje K, Baisley K, Filteau S, Kelly P, et al. Assessing water filtration and safe storage in households with young children of HIV‐positive mothers: a randomized, controlled trial in Zambia. PLoS One 2012;7(10):e46548. [PMC free article] [PubMed] [Google Scholar]
Quick 1999 BOL {published and unpublished data}
- Quick RE, Venczel LV, Mintz ED, Soleto L, Aparicio J, Gironaz M, et al. Diarrhoea prevention in Bolivia through point‐of‐use water treatment and safe storage: a promising new strategy. Epidemiology and Infection 1999;122(1):83‐90. [PMC free article] [PubMed] [Google Scholar]
- Venczel L. Evaluation and application of a mixed oxidant disinfection system for waterborne disease prevention [dissertation]. Chapel Hill (NC): University of North Carolina at Chapel Hill, 1997. [Google Scholar]
Quick 2002 ZMB {published data only}
- Quick RE, Kimura A, Thevos A, Tembo M, Shamputa I, Hutwagner L, et al. Diarrhea prevention through household‐level water disinfection and safe storage in Zambia. American Journal of Tropical Medicine and Hygiene 2002;66(5):584‐9. [PubMed] [Google Scholar]
Reller 2003a GTM {published data only}
- Reller ME, Mendoza CE, Lopez MB, Alvarez M, Hoekstra AR, Olson CA, et al. A randomized controlled trial of household‐based flocculant‐disinfectant drinking water treatment for diarrhoea prevention in rural Guatemala. American Journal of Tropical Medicine and Hygiene 2003;69(4):411‐9. [PubMed] [Google Scholar]
Reller 2003b GTM {published data only}
- Reller ME, Mendoza CE, Lopez MB, Alvarez M, Hoekstra AR, Olson CA, et al. A randomized controlled trial of household‐based flocculant‐disinfectant drinking water treatment for diarrhoea prevention in rural Guatemala. American Journal of Tropical Medicine and Hygiene 2003;69(4):411‐9. [PubMed] [Google Scholar]
Reller 2003c GTM {published data only}
- Reller ME, Mendoza CE, Lopez MB, Alvarez M, Hoekstra AR, Olson CA, et al. A randomized controlled trial of household‐based flocculant‐disinfectant drinking water treatment for diarrhoea prevention in rural Guatemala. American Journal of Tropical Medicine and Hygiene 2003;69(4):411‐9. [PubMed] [Google Scholar]
Reller 2003d GTM {published data only}
- Reller ME, Mendoza CE, Lopez MB, Alvarez M, Hoekstra AR, Olson CA, et al. A randomized controlled trial of household‐based flocculant‐disinfectant drinking water treatment for diarrhoea prevention in rural Guatemala. American Journal of Tropical Medicine and Hygiene 2003;69(4):411‐9. [PubMed] [Google Scholar]
Roberts 2001 MWI {published data only}
- Roberts L, Chartier Y, Chartier O, Malenga G, Toole M, Rodka H. Keeping clean water clean in a Malawi refugee camp: a randomized intervention trial. Bulletin of the World Health Organization 2001;79(4):280‐7. [PMC free article] [PubMed] [Google Scholar]
Rodrigo 2011 AUS {published data only}
- Rodrigo S, Sinclair M, Forbes A, Cunliffe D, Leder K. Drinking rainwater: a double‐blinded, randomized controlled study of water treatment filters and gastroenteritis incidence. American Journal of Public Health 2011;101(5):842‐7. [PMC free article] [PubMed] [Google Scholar]
Semenza 1998 UZB {published data only}
- Semenza JC, Roberts L, Henderson A, Bogan J, Rubin CH. Water distribution system and diarrheal disease transmission: a case study in Uzbekistan. American Journal of Tropical Medicine and Hygiene 1998;59(6):941‐6. [PubMed] [Google Scholar]
Stauber 2009 DOM {published and unpublished data}
- Stauber CE, Ortiz GM, Loomis DP, Sobsey MD. A randomized controlled trial of the concrete Biosand filter and its impact on diarrheal disease in Bonao, Dominican Republic. American Journal of Tropical Medicine and Hygiene 2009;80(2):286‐93. [PubMed] [Google Scholar]
Stauber 2012a KHM {published data only}
- Stauber CE, Printy ER, McCarty FA, Liang KR, Sobsey MD. Cluster randomized controlled trial of the plastic BioSand water filter in Cambodia. Environmental Science & Technology 2012;46(2):722‐8. [PubMed] [Google Scholar]
Stauber 2012b GHA {published and unpublished data}
- Stauber C, Kominek B, Liang K, Osman M, Sobsey M. Evaluation of the impact of the plastic BioSand filter on health and drinking water quality in rural Tamale, Ghana. International Journal of Environmental Research and Public Health 2012;9(11):3806‐23. [PMC free article] [PubMed] [Google Scholar]
Tiwari 2009 KEN {published data only}
- Tiwari SS, Schmidt WP, Darby J, Kariuki ZG, Jenkins MW. Intermittent slow sand filtration for preventing diarrhoea among children in Kenyan households using unimproved water sources: randomized controlled trial. Tropical Medicine & International Health 2009;14(11):1374‐82. [PubMed] [Google Scholar]
Torun 1982 GTM {published data only}
- Torun B. Environmental and educational interventions against diarrhea in Guatemala. In: Chen LC, Scrimshaw NS editor(s). Diarrhea and Malnutrition: Interactions, Mechanisms and Interventions. New York: Plenum Press, 1982:235‐66. [Google Scholar]
URL 1995a GTM {published data only}
- Universidad Rafael Landivar. Preventing infant morbidity: artisanal filters and education [Contra la morbilidad infantil: filtros artesanales y education]. Revista de Estudios Sociales 1995;IV(53):1‐66. [Google Scholar]
URL 1995b GTM {published data only}
- Universidad Rafael Landivar. Preventing infant morbidity: artisanal filters and education [Contra la morbilidad infantil: filtros artesanales y education]. Revista de Estudios Sociales 1995;IV(53):1‐66. [Google Scholar]
Xiao 1997 CHN {published data only}
- Xiao S, Lin C, Chen K. Evaluation of effectiveness of comprehensive control for diarrhea diseases in rural areas of east Fujian and analysis of its cost‐benefit [Chinese]. Zhonghua Yu Fang Yi Xue Za Zhi [Chinese Journal of Preventive Medicine] 1997;31(1):40‐1. [PubMed] [Google Scholar]
References to studies excluded from this review
Ahoyo 2011 {published data only}
- Ahoyo TA, Fatombi KJ, Boco M, Aminou T, Dramane KL. Impact of water quality and environmental sanitation on the health of schoolchildren in a suburban area of Benin: findings in the Savalou‐Banté and Dassa‐Glazoué sanitary districts [Impact de la qualité de l'eau et de l'assainissement sur la santé des enfants en milieu périurbain au Bénin: cas des zones sanitaires Savalou‐Banté et Dassa‐Glazoué]. Médecine tropicale 2011;71(3):281‐5. [PubMed] [Google Scholar]
Aiken 2011 {published data only}
- Aiken BA, Stauber CE, Ortiz GM, Sobsey MD. An assessment of continued use and health impact of the concrete biosand filter in Bonao, Dominican Republic. American Journal of Tropical Medicine & Hygiene 2011;85(2):309‐17. [PMC free article] [PubMed] [Google Scholar]
Alexander 2013 {published data only}
- Alexander KT, Dreibelbis R, Freeman MC, Ojeny B, Rheingans R. Improving service delivery of water, sanitation, and hygiene in primary schools: a cluster‐randomized trial in western Kenya. Journal of Water and Health 2013;11(3):507‐19. [PubMed] [Google Scholar]
Arnold 2009 {published data only}
- Arnold B, Arana B, Mäusezahl D, Hubbard A, Colford JM Jr. Evaluation of a pre‐existing, 3‐year household water treatment and handwashing intervention in rural Guatemala. International Journal of Epidemiology 2009;38(6):1651‐61. [PMC free article] [PubMed] [Google Scholar]
Arnold 2012a {published data only}
- Arnold BF, Mäusezahl D, Schmidt WP, Christen A, Colford, JM. Comment on randomized intervention study of solar disinfection of drinking water in the prevention of dysentery in Kenyan children aged under 5 years. Environmental Science & Technology 2012;46(5):3031‐2. [PubMed] [Google Scholar]
Arnold 2013 {published data only}
- Arnold BF, Null C, Luby SP, Unicomb L, Stewart CP, Dewey KG, et al. Cluster‐randomised controlled trials of individual and combined water, sanitation, hygiene and nutritional interventions in rural Bangladesh and Kenya: the WASH Benefits study design and rationale. BMJ Open 2013;3(8):e003476. [PMC free article] [PubMed] [Google Scholar]
Asaolu 2002 {published data only}
- Asaolu SO, Ofoezie IE, Odumuyiwa PA, Sowemimo OA, Ogunniyi TA. Effect of water supply and sanitation on the prevalence and intensity of Ascarias lumbricoides among pre‐school‐age children in Ajebandele and Ifewara, Osun State, Nigeria. Transactions of the Royal Society of Tropical Medicine and Hygiene 2002;96(6):600‐4. [PubMed] [Google Scholar]
Aziz 1990 BGD {published data only}
- Aziz KM, Hoque BA, Hasan KZ, Patwary MY, Huttly SR, Rahaman MM, et al. Reduction in diarrhoeal diseases in children in rural Bangladesh by environmental and behavioural modifications. Transactions of the Royal Society of Tropical Medicine and Hygiene 1990;84(3):433‐8. [PubMed] [Google Scholar]
- Hasan KZ, Briend A, Aziz KM, Hoque BA, Patwary MY, Huttly SR. Lack of impact of a water and sanitation intervention on the nutritional status of children in rural Bangladesh. European Journal of Clinical Nutrition 1989;43(12):837‐43. [PubMed] [Google Scholar]
- Henry FJ, Huttly SR, Patwary Y, Aziz KM. Environmental sanitation, food and water contamination and diarrhoea in rural Bangladesh. Epidemiology and Infection 1990;104(2):253‐9. [PMC free article] [PubMed] [Google Scholar]
Azurin 1974 {published data only}
- Azurin JC, Alvero M. Field evaluation of environmental sanitation measures against cholera. Bulletin of the World Health Organization 1974;51(1):19‐26. [PMC free article] [PubMed] [Google Scholar]
Bahl 1976 {published data only}
- Bahl MR. Impact of piped water supply on the incidence of typhoid fever and diarrhoeal diseases in Lusaka. Medical Journal of Zambia 1976;10(4):98‐9. [PubMed] [Google Scholar]
Bajer 2012 {published data only}
- Bajer A, Toczylowska B, Bednarska M, Sinski, E. Effectiveness of water treatment for the removal of Cryptosporidium and Giardia spp. Epidemiology and Infection 2012;140(11):2014‐22. [PubMed] [Google Scholar]
Barreto 2007 {published data only}
- Barreto ML, Genser B, Strina A, Teixeira MG, Assis AMO, Rego RF, et al. Effect of city‐wide sanitation programme on reduction in rate of childhood diarrhoea in northeast Brazil: assessment by two cohort studies. Lancet 2007;370(9599):1622‐8. [PMC free article] [PubMed] [Google Scholar]
Barzilay 2011 {published data only}
- Barzilay EJ, Aghoghovbia TS, Blanton EM, Akinpelumi AA, Coldiron ME, Akinfolayan O, et al. Diarrhea prevention in people living with HIV: an evaluation of a point‐of‐use water quality intervention in Lagos, Nigeria. AIDS Care 2011;23(3):330‐9. [PubMed] [Google Scholar]
Bersh 1985 {published data only}
- Bersh D, Osorio MM. Studies of diarrhoea in Quindio (Colombia): problems related to water treatment. Social Science & Medicine 1985;21(1):31‐9. [PubMed] [Google Scholar]
Boubacar 2014 {published data only}
- Boubacar Maïnassara H, Tohon Z. Assessing the health impact of the following measures in schools in Maradi (Niger): construction of latrines, clean water supply, establishment of hand washing stations, and health education. Journal of Parasitology Research 2014;2014:190451. [PMC free article] [PubMed] [Google Scholar]
Brown 2012a {published data only}
- Brown J, Clasen T. High adherence is necessary to realize health gains from water quality interventions. PLoS One 2012;7(5):e36735. [PMC free article] [PubMed] [Google Scholar]
Capuno 2011 {published data only}
- Capuno JJ, Tan CAR Jr, Fabella VM. Do piped water and flush toilets prevent child diarrhea in rural Philippines?. Asia‐Pacific Journal of Public Health 2011;December:1‐11. [PubMed] [Google Scholar]
Cavallaro 2011 {published data only}
- Cavallaro EC, Harris JR, Goia MS, dos Santos Barrado JC, Alves da Nóbrega A, Carvalho de Alvarenga Júnior I, et al. Evaluation of pot‐chlorination of wells during a cholera outbreak, Bissau, Guinea‐Bissau, 2008. Journal of Water and Health 2011;9(2):394‐402. [PubMed] [Google Scholar]
Chang 2012 {published data only}
- Chang WK, Ryu J, Yi Y, Lee W‐C, Lee C‐W, Kang D, et al. Improved water quality in response to pollution control measures at Masan Bay, Korea. Marine Pollution Bulletin 2012;64(2):427‐35. [PubMed] [Google Scholar]
Chongsuvivatwong 1994 {published data only}
- Chongsuvivatwong V, Mo‐suwan L, Chompikul J, Vitsupakorn K, McNeil D. Effects of piped water supply on the incidence of diarrhoeal diseases in children in southern Thailand. Southeast Asian Journal of Tropical Medicine and Public Health 1994;25(4):628‐32. [PubMed] [Google Scholar]
Christen 2011 {published data only}
- Christen A, Duran Pancheco G, Hattendorf J, Arnold BF, Cevallos M, Indergand S, et al. Factors associated with compliance among users of solar water disinfection in rural Bolivia. BMC Public Health 2011;11:210. [PMC free article] [PubMed] [Google Scholar]
Clasen 2012 {published data only}
- Clasen T, Boisson S, Routray P, Cumming O, Jenkins M, Ensink JHJ, et al. The effect of improved rural sanitation on diarrhoea and helminth infection: design of a cluster‐randomized trial in Orissa, India. Emerging Themes in Epidemiology 2012;9:7. [PMC free article] [PubMed] [Google Scholar]
Colford 2005 {published data only}
- Colford JM Jr, Wade TJ, Sandhu SK, Wright CC, Lee S, Shaw S, et al. A randomized, controlled trial of in‐home drinking water intervention to reduce gastrointestinal illness. American Journal of Epidemiology 2005;161(5):472‐82. [PubMed] [Google Scholar]
Colwell 2003 {published data only}
- Colwell RR, Huq A, Islam MS, Aziz KM, Yunus M, Khan NH, et al. Reduction of cholera in Bangladeshi villages by simple filtration. Proceedings of the National Academy of Sciences of the United States of America 2003;100(3):1051‐5. [PMC free article] [PubMed] [Google Scholar]
Conroy 2001 {published data only}
- Conroy RM, Meegan ME, Joyce T, McGuigan K, Barnes J. Solar disinfection of drinking water protects against cholera in children under 6 years of age. Archives of Disease in Childhood 2001;85(4):293‐5. [PMC free article] [PubMed] [Google Scholar]
Coulliette 2013 {published data only}
- Coulliette AD, Enger KS, Weir MH, Rose JB. Risk reduction assessment of waterborne Salmonella and Vibrio by a chlorine contact disinfectant point‐of‐use device. International Journal of Hygiene and Environmental Health 2013;216(3):355‐61. [PubMed] [Google Scholar]
Crump 2007 {published data only}
- Crump JA, Mendoza CE, Priest JW, Glass RI, Monroe SS, Dauphin LA, et al. Comparing serologic response against enteric pathogens with reported diarrhea to assess the impact of improved household drinking water quality. American Journal of Tropical Medicine and Hygiene 2007;77(1):136‐41. [PubMed] [Google Scholar]
Davis 2011 {published data only}
- Davis J, Pickering AJ, Rogers K, Mamuya S, Boehm AB. The effects of informational interventions on household water management, hygiene behaviors, stored drinking water quality, and hand contamination in peri‐urban Tanzania. American Journal of Tropical Medicine and Hygiene 2011;84(2):184‐91. [PMC free article] [PubMed] [Google Scholar]
Deb 1986 {published data only}
- Deb BC, Sircar BK, Sengupta PG, De SP, Mondal SK, Gupta DN, et al. Studies on interventions to prevent eltor cholera transmission in urban slums. Bulletin of the World Health Organization 1986;64(1):127‐31. [PMC free article] [PubMed] [Google Scholar]
Denslow 2010 {published data only}
- Denslow SA, Edwards J, Horney J, Peña R, Wurzelmann D, Morgan D. Improvements to water purification and sanitation infrastructure may reduce the diarrheal burden in a marginalized and flood prone population in remote Nicaragua. BMC International Health and Human Rights 2010;10:30. [PMC free article] [PubMed] [Google Scholar]
Devoto 2011 {published data only}
- Devoto F, Duflo E, Dupas P, Pariente W, Pons V. Happiness on Tap: Piped Water Adoption in Urban Morocco. National Bureau of Economic Research 2011;Working paper: 16933:1‐39. [Google Scholar]
Dorevitch 2011 {published data only}
- Dorevitch S, Doi M, Hsu FC, Lin KT, Roberts JD, Liu LC, et al. A comparison of rapid and conventional measures of indicator bacteria as predictors of waterborne protozoan pathogen presence and density. Journal of Environmental Monitoring 2011;13(9):2427‐35. [PubMed] [Google Scholar]
Dreibelbis 2014a KEN {published data only}
- Dreibelbis R, Freeman MC, Greene LE, Saboori S, Rheingans R. The impact of school water, sanitation, and hygiene interventions on the health of younger siblings of pupils: a cluster‐randomized trial in Kenya. American Journal of Public Health 2014;104(1):e91‐7. [PMC free article] [PubMed] [Google Scholar]
Dreibelbis 2014b KEN {published data only}
- Dreibelbis R, Freeman MC, Greene LE, Saboori S, Rheingans R. The impact of school water, sanitation, and hygiene interventions on the health of younger siblings of pupils: a cluster‐randomized trial in Kenya. American Journal of Public Health 2014;104(1):e91‐7. [PMC free article] [PubMed] [Google Scholar]
Dreibelbis 2014c KEN {published data only}
- Dreibelbis R, Freeman MC, Greene LE, Saboori S, Rheingans R. The impact of school water, sanitation, and hygiene interventions on the health of younger siblings of pupils: a cluster‐randomized trial in Kenya. American Journal of Public Health 2014;104(1):e91‐7. [PMC free article] [PubMed] [Google Scholar]
du Preez 2012 {published data only}
- du Preez M, Conroy RM, McGuigan KG. Response to comment on "A randomized intervention study of solar disinfection of drinking water (SODIS) in the prevention of dysentery in Kenyan children aged under 5 years". Environmental Science and Technology 2012;46(5):3036‐7. [PubMed] [Google Scholar]
Eisenberg 2006 {published data only}
- Eisenberg JNS, Hubbard A, Wade TJ, Sylvester MD, LeChevallier MW, Levy DA, et al. Inferences drawn from a risk assessment compared directly with a randomized trial of a home drinking water intervention. Environmental Health Perspectives 2006;114(8):1199‐204. [PMC free article] [PubMed] [Google Scholar]
Enger 2012 {published data only}
- Enger KS, Nelson KL, Clasen T, Rose JB, Eisenberg JNS. Linking quantitative microbial risk assessment and epidemiological data: informing safe drinking water trials in developing countries. Environmental Science and Technology 2012;46(9):5160‐7. [PubMed] [Google Scholar]
Esrey 1988 {published data only}
- Esrey SA, Habicht JJP, Latham MC, Sisler DG, Casella G. Drinking water source, diarrhoeal morbidity, and child growth in villages with both traditional and improved water supplies in rural Lesotho, southern Africa. American Journal of Public Health 1988;78(11):1451‐5. [PMC free article] [PubMed] [Google Scholar]
Fewtrell 1994 {published data only}
- Fewtrell L, Kay D, Dunlop J, O'Neill G, Wyer M. Infectious diseases and water‐supply disconnections. Lancet 1994;343(8909):1370. [PubMed] [Google Scholar]
Fewtrell 1997 {published data only}
- Fewtrell L, Kay D, Wyer M, O'Neill G. An investigation into the possible links between shigellosis and hepatitis A and public water supply disconnections. Public Health 1997;111(3):179‐81. [PubMed] [Google Scholar]
Firth 2010 {published data only}
- Firth J, Balraj V, Muliyil J, Roy S, Rani LM, Chandresekhar R, et al. Point‐of‐use interventions to decrease contamination of drinking water: a randomized, controlled pilot study on efficacy, effectiveness, and acceptability of closed containers, Moringa oleifera, and In‐home chlorination in rural South India. American Journal of Tropical Medicine and Hygiene 2010;82(5):759‐65. [PMC free article] [PubMed] [Google Scholar]
Fisher 2011 {published data only}
- Fisher S, Kabir B, Lahiff E, MacLachlan M. Knowledge, attitudes, practices and implications of safe water management and good hygiene in rural Bangladesh: assessing the impact and scope of the BRAC WASH programme. Journal of Water and Health 2011;9(1):80‐93. [PubMed] [Google Scholar]
Freeman 2012 {published data only}
- Freeman MC, Greene LE, Dreibelbis R, Saboori S, Muga R, Brumback B, et al. Assessing the impact of a school‐based water treatment, hygiene and sanitation programme on pupil absence in Nyanza Province, Kenya: a cluster‐randomized trial. Tropical Medicine & International Health 2012;17(3):380‐91. [PubMed] [Google Scholar]
Freeman 2014a KEN {published data only}
- Freeman MC, Clasen T, Dreibelbis R, Saboori S, Greene L, Brumback B, et al. The impact of a school‐based water supply and treatment, hygiene, and sanitation programme on pupil diarrhoea: a cluster‐randomized trial. Epidemiology and Infection 2014;142(2):340‐51. [PMC free article] [PubMed] [Google Scholar]
Freeman 2014b KEN {published data only}
- Freeman MC, Clasen T, Dreibelbis R, Saboori S, Greene L, Brumback B, et al. The impact of a school‐based water supply and treatment, hygiene, and sanitation programme on pupil diarrhoea: a cluster‐randomized trial. Epidemiology and Infection 2014;142(2):340‐51. [PMC free article] [PubMed] [Google Scholar]
Freeman 2014c KEN {published data only}
- Freeman MC, Clasen T, Dreibelbis R, Saboori S, Greene L, Brumback B, et al. The impact of a school‐based water supply and treatment, hygiene, and sanitation programme on pupil diarrhoea: a cluster‐randomized trial. Epidemiology and Infection 2014;142(2):340‐51. [PMC free article] [PubMed] [Google Scholar]
Fry 2010 {published data only}
- Fry LM, Cowden JR, Watkins DW Jr, Clasen T, Mihelcic JR. Quantifying health improvements from water quantity enhancement: an engineering perspective applied to rainwater harvesting in West Africa. Environmental Science and Technology 2010;44(24):9535‐41. [PubMed] [Google Scholar]
Galiani 2009 {published data only}
- Galiani S, Gonzalez‐Rozada M, Schargrodsky E. Water expansions in shantytowns: health and savings. Economica 2009;76(104):607‐22. [Google Scholar]
Garrett 2008 KEN {published data only}
- Garrett V, Ogutu P, Mabonga P, Ombeki S, Mwaki A, Aluoch G, et al. Diarrhoea prevention in a high‐risk rural Kenyan population through point‐of‐use chlorination, safe water storage, sanitation, and rainwater harvesting. Epidemiology and Infection 2008;136(11):1463‐71. [PMC free article] [PubMed] [Google Scholar]
Ghannoum 1981 {published data only}
- Ghannoum MA, Moore KE, Al‐Dulaimi M, Nasr M. The incidence of water‐related diseases in the Brak area, Libya from 1977 to 1979, before and after the installation of water treatment plants. Zentralblatt für Bakteriologie, Mikrobiologie und Hygiene. 1. Abt. Originale B, Hygiene 1981;173(6):501‐8. [PubMed] [Google Scholar]
Gómez‐Couso 2012 {published data only}
- Gómez‐Couso H, Fontán‐Sainza M, Navntoft C, Fernández‐Ibáñez P, Ares‐Mazás E. Comparison of different solar reactors for household disinfection of drinking water in developing countries: evaluation of their efficacy in relation to the waterborne enteropathogen Cryptosporidium parvum. Transactions of the Royal Society of Tropical Medicine and Hygiene 2012;106(11):645‐52. [PubMed] [Google Scholar]
Gorelick 2011 {published data only}
- Gorelick MH, McLellan SL, Wagner D, Klein J. Water use and acute diarrhoeal illness in children in a United States metropolitan area. Epidemiology & Infection 2011;139(2):295‐301. [PubMed] [Google Scholar]
Greene 2012 {published data only}
- Greene LE, Freeman MC, Akoko D, Saboori S, Moe C, Rheingans R. Impact of a school‐based hygiene promotion and sanitation intervention on pupil hand contamination in Western Kenya: a cluster randomized trial. American Journal of Tropical Medicine and Hygiene 2012;87(3):385‐93. [PMC free article] [PubMed] [Google Scholar]
Habib 2013 {published data only}
- Habib MA, Soofi S, Sadiq K, Samejo T, Hussain M, Mirani M, et al. A study to evaluate the acceptability, feasibility and impact of packaged interventions ("Diarrhea Pack") for prevention and treatment of childhood diarrhea in rural Pakistan. BMC Public Health 2013;13:922. [PMC free article] [PubMed] [Google Scholar]
Harris 2009 {published data only}
- Harris JR, Greene SK, Thomas TK, Ndivo R, Okanda J, Masaba R, et al. Effect of a point‐of‐use water treatment and safe water storage intervention on diarrhea in infants of HIV‐infected mothers. Journal of Infectious Diseases 2009;200(8):1186‐93. [PubMed] [Google Scholar]
Harshfield 2012 {published data only}
- Harshfield E, Lantagne D, Turbes A, Null C. Evaluating the sustained health impact of household chlorination of drinking water in rural Haiti. American Journal of Tropical Medicine and Hygiene 2012;87(5):786‐95. [PMC free article] [PubMed] [Google Scholar]
Hartinger 2011 {published data only}
- Hartinger SM, Lanata CF, Hattendorf J, Gil AI, Verastegui H, Ochoa T, et al. A community randomised controlled trial evaluating a home‐based environmental intervention package of improved stoves, solar water disinfection and kitchen sinks in rural Peru: rationale, trial design and baseline findings. Contemporary Clinical Trials 2011;32(6):864‐73. [PubMed] [Google Scholar]
Hartinger 2012 {published data only}
- Hartinger SM, Lanata CF, Gil AI, Hattendorf J, Verastegui H, Mäusezahl D. Combining interventions: improved chimney stoves, kitchen sinks and solar disinfection of drinking water and kitchen clothes to improve home hygiene in rural Peru. Journal of Field Actions 2012;6:1‐10. [Google Scholar]
Hellard 2001 {published data only}
- Hellard ME, Sinclair MI, Forbes AB, Fairley CK. A randomized, blinded, controlled trial investigating the gastrointestinal health effects of drinking water quality. Environmental Health Perspectives 2001;109(8):773‐8. [PMC free article] [PubMed] [Google Scholar]
Hoque 1996 {published data only}
- Hoque BA, Juncker T, Sack RB, Ali M, Aziz KM. Sustainability of a water, sanitation and hygiene education project in rural Bangladesh: a 5‐year follow‐up. Bulletin of the World Health Organization 1996;74(4):431‐7. [PMC free article] [PubMed] [Google Scholar]
Huda 2012 {published data only}
- Huda TMN, Unicomb L, Johnston RB, Halder AK, Yushuf Sharker MA, Luby SP. Interim evaluation of a large scale sanitation, hygiene and water improvement programme on childhood diarrhea and respiratory disease in rural Bangladesh. Social Science and Medicine 2012;75(4):604‐11. [PubMed] [Google Scholar]
Hunter 2010 {published data only}
- Hunter PR, Ramírez Toro GI, Minnigh HA. Impact on diarrhoeal illness of a community educational intervention to improve drinking water quality in rural communities in Puerto Rico. BMC Public Health 2010;10:219. [PMC free article] [PubMed] [Google Scholar]
Iijima 2001 {published data only}
- Iijima Y, Karama M, Oundo JO, Honda T. Prevention of bacterial diarrhea by pasteurization of drinking water in Kenya. Microbiology and Immunology 2001;45(6):413‐6. [PubMed] [Google Scholar]
Islam 2011 {published data only}
- Islam MS, Mahmud ZH, Uddin MH, Islam K, Yunus M, Islam MS, et al. Purification of household water using a novel mixture reduces diarrhoeal disease in Matlab, Bangladesh. Transactions of the Royal Society of Tropical Medicine & Hygiene 2011;105(6):341‐5. [PubMed] [Google Scholar]
Jensen 2002 {published data only}
- Jensen PK, Ensink JH, Jayasinghe G, Hoek W, Cairncross S, Dalsgaard A. Domestic transmission routes of pathogens: the problem of in‐house contamination of drinking water during storage in developing countries. Tropical Medicine & International Health 2002;7(7):604‐9. [PubMed] [Google Scholar]
Kariuki 2012 {published data only}
- Kariuki JG, Magambo KJ, Njeruh MF, Muchiri EM, Nzioka SM, Kariuki S. Effects of hygiene and sanitation interventions on reducing diarrhoea prevalence among children in resource constrained communities: case study of Turkana District, Kenya. Journal of Community Health 2012;37(6):1178‐84. [PubMed] [Google Scholar]
Karon 2011 {published data only}
- Karon AE, Hanni KD, Mohle‐Boetani JC, Beretti RA, Hill VR, Arrowood M, et al. Giardiasis outbreak at a camp after installation of a slow‐sand filtration water‐treatment system. Epidemiology and Infection 2011;139(5):713‐7. [PubMed] [Google Scholar]
Keraita 2007 {published data only}
- Keraita B, Konradsen F, Drechsel P, Abaidoo RC. Reducing microbial contamination on wastewater‐irrigated lettuce by cessation of irrigation before harvesting. Tropical Medicine & International Health 2007;12(Suppl 2):8‐14. [PubMed] [Google Scholar]
Khan 1984 {published data only}
- Khan MU, Khan MR, Hossan B, Ahmed QS. Alum potash in water to prevent cholera. Lancet 1984;2(8410):1032. [PubMed] [Google Scholar]
Luby 2008 {published data only}
- Luby SP, Gupta SK, Sheikh MA, Johnston RB, Ram PK, Islam MS. Tubewell water quality and predictors of contamination in three flood‐prone areas in Bangladesh. Journal of Applied Microbiology 2008;105(4):1002‐8. [PubMed] [Google Scholar]
Luoto 2011 {published data only}
- Luoto J, Najnin N, Mahmud M, Albert J, Islam MS, Luby SP, et al. What point‐of‐use water treatment products do consumers use? Evidence from a randomized controlled trial among the urban poor in Bangladesh. PLoS One 2011;6(10):e26132. [PMC free article] [PubMed] [Google Scholar]
Luoto 2012 {published data only}
- Luoto J, Mahmud M, Albert J, Luby SP, Najnin N, Unicomb L, et al. Learning to dislike safe water products: results from a randomized controlled trial of the effects of direct and peer experience on willingness to pay. Environmental Science & Technology 2012;46(11):6244‐51. [PubMed] [Google Scholar]
Macy 1998 {published data only}
- Macy JT, Quick RE. Evaluation of a novel drinking water treatment and storage intervention in Nicaragua. Revista Panamericana de Salud Pública (Pan American Journal of Public Health) 1998;3(2):135‐6. [PubMed] [Google Scholar]
Mäusezahl 2003 {unpublished data only}
- Mäusezahl D, Tanner M, Hobbins M. The SODIS health impact study (as supplied 15 March 2004). Data on file.
McCabe 1957 {published data only}
- McCabe LJ, Haines TW. Diarrheal disease control by improved human excreta disposal. Public Health Reports 1957;72(10):921‐8. [PMC free article] [PubMed] [Google Scholar]
Mertens 1990 {published data only}
- Mertens TE, Cousens SN, Fernando MA, Kirkwood BR, Merkle F, Korte R, et al. Health impact evaluation of improved water supplies and hygiene practices in Sri Lanka: background and methodology. Tropical Medicine and Parasitology 1990;41(1):79‐88. [PubMed] [Google Scholar]
Messou 1997 {published data only}
- Messou E, Sangaré SV, Josseran R, Corre C, Guélain J. Effect of hygiene measures, water, sanitation and oral rehydration therapy on diarrhoea in children less than five years old in the south of Ivory Coast [Effet de l'observance des mesures d'hygiene, d'approisionnement en eau et de la therapie par voie orale sur les diarrhees chez les enfants de moins de 5 ans dans le sud de la Cote D'Ivoire]. Bulletin de la Société de Pathologie Exotique (1990) 1997;90(1):44‐7. [PubMed] [Google Scholar]
Nanan 2003 {published data only}
- Nanan D, White F, Azam I, Afsar H, Hozhari S. Evaluation of a water, sanitation, and hygiene education intervention on diarrhoea in northern Pakistan. Bulletin of the World Health Organization 2003;81(3):160‐5. [PMC free article] [PubMed] [Google Scholar]
Nerkar 2014 {published data only}
- Nerkar SS, Tamhankar AJ, Khedar SU, Lundborg CS. Quality of water and antibiotic resistance of Escherichia coli from water sources of hilly tribal villages with and without integrated watershed management‐a one year prospective study. International Journal of Environmental Research and Public Health 2014;11(6):6156‐70. [PMC free article] [PubMed] [Google Scholar]
Nnane 2011 {published data only}
- Nnane DE, Ebdon JE, Taylor HD. Integrated analysis of water quality parameters for cost‐effective faecal pollution management in river catchments. Water Research 2011;45(6):2235‐46. [PubMed] [Google Scholar]
Oluyege 2011 {published data only}
- Oluyego JO, Koko AE, Aregbesola OA. Bacteriological and physico‐chemical quality assessment of household drinking water in Ado‐Ekiti, Nigeria. Water Science & Technology: Water Supply 2011;11(1):79‐84. [Google Scholar]
Palit 2012 {published data only}
- Palit A, Batabyal P, Kanungo S, Sur D. In‐house contamination of potable water in urban slum of Kolkata, India: a possible transmission route of diarrhea. Water Science and Technology 2012;66(2):299‐303. [PubMed] [Google Scholar]
Pavlinac 2014 {published data only}
- Pavlinac PB, Naulikha JM, Chaba L, Kimani N, Sangaré LR, Yuhas K, et al. Water filter provision and home‐based filter reinforcement reduce diarrhea in Kenyan HIV‐infected adults and their household members. American Journal of Tropical Medicine and Hygiene 2014;91(2):273‐80. [PMC free article] [PubMed] [Google Scholar]
Payment 1991a {published data only}
- Payment P, Franco E, Richardson L, Siemiatycki J. Gastrointestinal health effects associated with the consumption of drinking water produced by point‐of‐use domestic reverse‐osmosis filtration units. Applied and Environmental Microbiology 1991;57(4):945‐8. [PMC free article] [PubMed] [Google Scholar]
Payment 1991b {published data only}
- Payment P, Richardson L, Siemiatycki J, Dewar R, Edwardes M, Franco E. A randomized trial to evaluate the risk of gastrointestinal disease due to consumption of drinking water meeting current microbiological standards. American Journal of Public Health 1991;81(6):703‐8. [PMC free article] [PubMed] [Google Scholar]
Peletz 2013 {published data only}
- Peletz R, Simuyandi M, Simunyama M, Sarenje K, Kelly P, Clasen T. Follow‐up study to assess the use and performance of household filters in Zambia. American Journal of Tropical Medicine and Hygiene 2013;89(6):1190‐4. [PMC free article] [PubMed] [Google Scholar]
Pinfold 1990 {published data only}
- Pinfold JV. Faecal contamination of water and fingertip‐rinses as a method for evaluating the effect of low‐cost water supply and sanitation activities on faeco‐oral disease transmission. II. A hygiene intervention study in rural north‐east Thailand. Epidemiology and Infection 1990;105(2):377‐89. [PMC free article] [PubMed] [Google Scholar]
Psutka 2012 {published data only}
- Psutka R, Peletz R, Michelo S, Kelly P, Clasen T. Assessing the microbiological performance and potential cost of boiling drinking water in urban Zambia. Environmental Science & Technology 2011;45(14):6095‐101. [PubMed] [Google Scholar]
Rosa 2014 {published data only}
- Rosa G, Majorin F, Boisson S, Barstow C, Johnson M, Kirby M, et al. Assessing the impact of water filters and improved cook stoves on drinking water quality and household air pollution: a randomised controlled trial in Rwanda. PLoS One 2014;9(3):e91011. [PMC free article] [PubMed] [Google Scholar]
Rose 2006 {published data only}
- Rose A, Roy S, Abraham V, Homgren G, George K, Balraj V, et al. Solar disinfection of water for diarrhoeal prevention in Southern India. Archives of Disease in Childhood 2006;91(2):139‐41. [PMC free article] [PubMed] [Google Scholar]
Rubenstein 1969 {published data only}
- Rubenstein A, Boyle J, Odoroff CL, Kunitz SJ. Effect of improved sanitary facilities on infant diarrhea in a Hopi village. Public Health Reports 1969;84(12):1093‐7. [PMC free article] [PubMed] [Google Scholar]
Russo 2012 {published data only}
- Russo ET, Sheth A, Menon M, Wannemuehler K, Weinger M, Kudzala AC, et al. Water treatment and handwashing behaviors among non‐pregnant friends and relatives of participants in an antenatal hygiene promotion program in Malawi. American Journal of Tropical Medicine & Hygiene 2012;86(5):860‐5. [PMC free article] [PubMed] [Google Scholar]
Sathe 1996 {published data only}
- Sathe AA, Hinge DV, Watve MG. Water treatment and diarrhoea. Lancet 1996;348(9023):335‐6. [PubMed] [Google Scholar]
Shah 2012 {published data only}
- Shah D, Choudhury P, Gupta P, Mathew JL, Gera T, Gogia S, et al. Promoting appropriate management of diarrhea: a systematic review of literature for advocacy and action: UNICEF‐PHFI series on newborn and child health, India. Indian Pediatrics 2012;49(8):627‐49. [PubMed] [Google Scholar]
Sharan 2011 {published data only}
- Sharan R, Chhibber S, Heed RH. Inactivation and sub‐lethal injury of salmonella typhi, salmonella typhimurium and vibrio cholerae in copper water storage vessels. BMC Infectious Diseases 2011;11:204. [PMC free article] [PubMed] [Google Scholar]
Sheth 2010 {published data only}
- Sheth AN, Russo ET, Menon M, Wannemuehler K, Weinger M, Kudzala AC, et al. Impact of the integration of water treatment and handwashing incentives with antenatal services on hygiene practices of pregnant women in Malawi. American Journal of Tropical Medicine and Hygiene 2010;83(6):1315‐21. [PMC free article] [PubMed] [Google Scholar]
Shiffman 1978 {published data only}
- Shiffman MA, Schneider R, Faigenblum JM, Helms R, Turner A. Field studies on water, sanitation and health education in relation to health status in Central America. Progress in Water Technology 1978;11:143‐50. [Google Scholar]
Shrestha 2006 {published data only}
- Shrestha RK, Marseill E, Kahn JG, Lule JG, Pitter C, Blandford JM, et al. Cost‐effectivness of home‐based chlorination and safe water storage in reducing diarrhea among HIV‐affected households in Uganda. American Journal of Tropical Medicine and Hygiene 2006;74(5):884‐90. [PubMed] [Google Scholar]
Shum 1971 {published data only}
- Shum H, Sum CY, Chan‐Teo CH. Water‐borne dysentery due to Shigella sonnei in Hong Kong. Southeast Asian Journal of Tropical Medicine and Public Health 1971;2(2):180‐5. [PubMed] [Google Scholar]
Sima 2012 {published data only}
- Sima LC, Desai MM, McCarty KM, Elimelech M. Relationship between use of water from community‐scale water treatment refill kiosks and childhood diarrhea in Jakarta. American Journal of Tropical Medicine and Hygiene 2012;87(6):979‐84. [PMC free article] [PubMed] [Google Scholar]
Sorvillo 1994 {published data only}
- Sorvillo FJ, Lieb LE, Nahlen B, Miller J, Mascola L, Ash LR. Municipal drinking water and cryptosporidiosis among persons with AIDS in Los Angeles County. Epidemiology and Infection 1994;113(2):313‐20. [PMC free article] [PubMed] [Google Scholar]
Stauber 2013 {published data only}
- Stauber CE, Walters A, Fabiszewski de Aceituno AM, Sobsey MD. Bacterial contamination on household toys and association with water, sanitation and hygiene conditions in Honduras. International Journal of Environmental Research and Public Health 2013;10(4):1586‐97. [PMC free article] [PubMed] [Google Scholar]
Sutha 2011 {published data only}
- Sutha S. Contaminated drinking water and rural health perspectives in Rajasthan, India: an overview of recent case studies. Environmental Monitoring and Assessment 2011;173(1‐4):837‐49. [PubMed] [Google Scholar]
Tonglet 1992 {published data only}
- Tonglet R, Isu K, Mpese M, Dramaix M, Hennart P. Can improvements in water supply reduce childhood diarrhoea?. Health Policy and Planning 1992;7(3):260‐8. [Google Scholar]
Trivedi 1971 {published data only}
- Trivedi BK, Gandhi HS, Shukla NK. Bacteriological water quality and incidence of water borne diseases in a rural population. Indian Journal of Medical Sciences 1971;25(11):795‐801. [PubMed] [Google Scholar]
VanDerslice 1995 {published data only}
- VanDerslice J, Briscoe J. Environmental interventions in developing countries: interactions and their implications. American Journal of Epidemiology 1995;141(2):135‐44. [PubMed] [Google Scholar]
Varghese 2002 {unpublished data only}
- Varghese A. Point‐of‐use water treatment systems in rural Haiti: human health and water quality impact assessment [dissertation]. Cambridge (MA): Massachusetts Institute of Technology, 2002. [Google Scholar]
Wiedenmann 2006 {published data only}
- Wiedenmann A, Krüger P, Dietz K, López‐Pila JM, Szewzyk R, Botzenhart K. A randomized controlled trial assessing infectious disease risks from bathing in fresh recreational waters in relation to the concentration of Escherichia coli, intestinal Enterococci, Clostridium perfringens, and somatic coliphages. Environmental Health Perspectives 2006;114(2):228‐36. [PMC free article] [PubMed] [Google Scholar]
Wolf 2014 {published data only}
- Wolf J, Prüss‐Ustün A, Cumming O, Bartram J, Bonjour S, Cairncross S, et al. Assessing the impact of drinking water and sanitation on diarrhoeal disease in low‐ and middle‐income settings: systematic review and meta‐regression. Tropical Medicine & International Health 2014;19(8):928‐42. [PubMed] [Google Scholar]
Wood 2012 {published data only}
- Wood S, Foster J, Kols A. Understanding why women adopt and sustain home water treatment: Insights from the Malawi antenatal care program. Social Science Medicine 2012;75(4):634‐42. [PubMed] [Google Scholar]
Wu 2011 {published data only}
- Wu J, Geen A, Ahmed KM, Alam YAJ, Culligan PJ, Escamilla V, et al. Increase in diarrheal disease associated with arsenic mitigation in Bangladesh. PLoS One 2011;6(12):e29593. [PMC free article] [PubMed] [Google Scholar]
References to ongoing studies
Chlorination, Dhaka {published data only}
- Impact of Low‐Cost In‐Line Chlorination Systems in Urban Dhaka on Water Quality and Child Health. Ongoing study Early 2015.
WASH‐B, Bangladesh {published data only}
- WASH Benefits Bangladesh: A Cluster Randomized Controlled Trial of the Benefits of Water, Sanitation, Hygiene Plus Nutrition Interventions on Child Growth. Ongoing study May 2012.
WASH‐B, Kenya {published data only}
- WASH‐Benefits study, Kenya. Ongoing study September 2012.
Additional references
Arnold 2007
- Arnold BF, Colford JM Jr. 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. American Journal of Tropical Medicine and Hygiene 2007;76(2):354‐64. [PubMed] [Google Scholar]
Austin 1993
- Austin CJ. Investigation of in‐house water chlorination and its effectiveness for rural areas of the Gambia [dissertation]. New Orleans: Tulane University School of Public Health and Tropical Medicine, 1993. [Google Scholar]
Bain 2014
- Bain R, Cronk R, Wright J, Yang H, Slaymaker T, Bartram J. Fecal contamination of drinking‐water in low‐ and middle‐income countries: a systematic review and meta‐analysis. PLoS Medicine 2014;11(5):e1001644. [PMC free article] [PubMed] [Google Scholar]
Brown 2008
- Brown J, Sobsey MD, Loomis D. Local drinking water filters reduce diarrheal disease in Cambodia: a randomized, controlled trial of the ceramic water purifier. American Journal of Tropical Medicine and Hygiene 2008;79(3):394‐400. [PubMed] [Google Scholar]
Brown 2012
- Brown J, Clasen T. High adherence is necessary to realize health gains from water quality interventions. PLoS One 2012;7(5):e36735. [PMC free article] [PubMed] [Google Scholar]
Byers 2001
- Byers KE, Guerrant RL, Farr BM. Fecal‐oral transmission. In: Thomas JC, Webber DJ editor(s). Epidemiologic Methods for the Study of Infectious Diseases. Oxford: Oxford University Press, 2001:228‐48. [Google Scholar]
Cairncross 2010
- Cairncross S, Hunt C, Boisson S, Bostoen K, Curtis V, Fung ICH, et al. Water, sanitation and hygiene for the prevention of diarrhoea. International Journal of Epidemiology 2010;39(Suppl 1):i193‐205. [PMC free article] [PubMed] [Google Scholar]
Crump 2005
- Crump JA, Otieno PO, Slutsker L, Keswick BH, Rosen DH, Hoekstra RM, et al. Household based treatment of drinking water with flocculant‐disinfectant for preventing diarrhoea in areas with turbid source water in rural western Kenya: cluster randomised controlled trial. BMJ 2005;331(7515):478. [PMC free article] [PubMed] [Google Scholar]
Cutler 2005
- Cutler D, Miller G. The role of public health improvements in health advances: the twentieth‐century United States [2005]. Demography 2005;42(1):1‐22. [PubMed] [Google Scholar]
Eisenberg 2007
- Eisenberg JN, Scott JC, Porco T. Integrating disease control strategies: balancing water sanitation and hygiene interventions to reduce diarrheal disease burden. American Journal of Public Health 2007;97(5):846‐52. [PMC free article] [PubMed] [Google Scholar]
Eisenberg 2012
- Eisenberg JN, Trostle J, Sorensen RJ, Shields KF. Toward a systems approach to enteric pathogen transmission: from individual independence to community interdependence. Annual Review of Public Health 2012;33:239‐57. [PMC free article] [PubMed] [Google Scholar]
Engell 2013
- Engell RE, Lim SS. Does clean water matter? An updated meta‐analysis of water supply and sanitation interventions and diarrhoeal diseases. Lancet 2013;381(Supplement 2):S44. [Google Scholar]
Enger 2013
- Enger KS, Nelson KL, Rose JB, Eisenberg JNS. The joint effects of efficacy and compliance: a study of household water treatment effectiveness against childhood diarrhea. Water Research 2013;47(3):1181‐90. [PubMed] [Google Scholar]
Esrey 1986
- Esrey SA, Habicht JP. Epidemiologic evidence for health benefits from improved water and sanitation in developing countries. Epidemiologic Reviews 1986;8:117‐28. [PubMed] [Google Scholar]
Fewtrell 2005
- Fewtrell L, Kaufmann RB, Kay D, Enanoria W, Haller L, Colford JM Jr. Water, sanitation, and hygiene interventions to reduce diarrhoea in less developed countries: a systematic review and meta‐analysis. Lancet Infectious Diseases 2005;5(1):42‐52. [PubMed] [Google Scholar]
Fischer Walker 2012
- Fischer Walker CL, Perin J, Aryee MJ, Boschi‐Pinto C, Black RE. Diarrhea incidence in low‐ and middle‐income countries in 1990 and 2010: a systematic review. BMC Public Health 2012;12:220. [PMC free article] [PubMed] [Google Scholar]
GBD 2015
- GBD 2013 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990‐2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015;S0140‐6736(15):128. [PMC free article] [PubMed] [Google Scholar]
GRADEpro GDT [Computer program]
- McMaster University (developed by Evidence Prime, Inc.). GRADEpro GDT: GRADEpro Guideline Development Tool. McMaster University (developed by Evidence Prime, Inc.), 2015.
Guyatt 2008
- Guyatt GH, Oxman AD, Kunz R, Vist GE, Falck‐Ytter Y, Schünemann HJ, GRADE Working Group. Rating quality of evidence and strength of recommendations: What is "quality of evidence" and why is it important to clinicians?. BMJ 2008;336(7651):995‐8. [PMC free article] [PubMed] [Google Scholar]
Higgins 2005
- Higgins J, Green S, editors. Highly sensitive search strategies for identifying reports of randomized controlled trials in MEDLINE. Cochrane Handbook for Systematic Reviews of Interventions 4.2.5 [updated May 2005]; Appendix 5b (accessed 1 January 2006).
Higgins 2006
- Higgins JPT, Green S, editors. Section 8: Analysing and presenting results. Cochrane Handbook for Systematic Reviews of Interventions 4.2.5 [updated September 2006]. http://community.cochrane.org/sites/default/files/uploads/Handbook4.2.6Sep2006.pdf (accessed 15 November 2014).
Higgins 2011
- Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. Available at http://handbook.cochrane.org/.
Hunter 2009
- Hunter PR. Household water treatment in developing countries: comparing different intervention types using meta‐regression. Environmental Science & Technology 2009;43(23):8991‐7. [PubMed] [Google Scholar]
Hutton 2013
- Hutton G. Global costs and benefits of reaching universal coverage of sanitation and drinking‐water supply. Journal of Water and Health 2013;11(1):1‐12. [PubMed] [Google Scholar]
Kotloff 2013
- Kotloff KL, Nataro JP, Blackwelder WC, Nasrin D, Farag TH, Panchalingam S, et al. Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case‐control study. Lancet 2013;382(9888):209‐22. [PubMed] [Google Scholar]
Lanata 2013
- Lanata CF, Fischer‐Walker CL, Olascoaga AC, Torres CX, Aryee MJ, Black RE, Child Health Epidemiology Reference Group of the World Health Organization and UNICEF. Global causes of diarrheal disease mortality in children <5 years of age: a systematic review. PLoS One 2013;8(9):e72788. [PMC free article] [PubMed] [Google Scholar]
Leclerc 2002
- Leclerc H, Schwartzbrod L, Dei‐Cas E. Microbial agents associated with waterborne diseases. Critical Reviews in Microbiology 2002;28(4):371‐409. [PubMed] [Google Scholar]
Lindquist 2014
- Lindquist ED, George CM, Perin J, Neiswender de Calani KJ, Norman WR, Davis TP, et al. A cluster randomized controlled trial to reduce childhood diarrhea using hollow fiber water filter and/or hygiene–sanitation educational interventions. American Journal of Tropical Medicine and Hygiene 2014;91(1):190‐7. [PMC free article] [PubMed] [Google Scholar]
Luby 2004
- Luby SP, Agboatwalla M, Hoekstra RM, Rahbar MH, Billhimer W, Keswick BH. Delayed effectiveness of home‐based interventions in reducing childhood diarrhea, Karachi, Pakistan. American Journal of Tropical Medicine and Hygiene 2004;71(4):420‐7. [PubMed] [Google Scholar]
Luby 2006
- Luby SP, Agboatwalla M, Painter J, Altaf A, Billhimer W, Keswick B, et al. Combining drinking water treatment and hand washing for diarrhoea prevention, a cluster randomised controlled trial. Tropical Medicine & International Health 2006;11(4):479‐89. [PubMed] [Google Scholar]
McNutt 2003
- McNutt LA, Wu C, Xue X, Hafner JP. Estimating the relative risk in cohort studies and clinical trials of common outcomes. American Journal of Epidemiology 2003;157(10):940‐3. [PubMed] [Google Scholar]
Murray 2012
- Murray CJL, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud C, et al. Disability‐adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990‐2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; Vol. 380, issue 9859:2197‐223. [PubMed]
Opryszko 2010
- Opryszko MC, Majeed SW, Hansen PM, Myers JA, Baba D, Thompson RE, et al. Water and hygiene interventions to reduce diarrhoea in rural Afghanistan: a randomized controlled study. Journal of Water Health 2010;8(4):687‐702. [PubMed] [Google Scholar]
Reller 2003
- Reller ME, Mendoza CE, Lopez MB, Alvarez M, Hoekstra AR, Olson CA, et al. A randomized controlled trial of household‐based flocculant‐disinfectant drinking water treatment for diarrhoea prevention in rural Guatemala. American Journal of Tropical Medicine and Hygiene 2003;69(4):411‐9. [PubMed] [Google Scholar]
Review Manager (RevMan) [Computer program]
- The Nordic Cochrane Centre, The Cochrane Collaboration. Review Manager (RevMan). Version 5.3. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014.
Reynolds 2008
- Reynolds KA, Mena KD, Gerba CP. Risk of waterborne illness via drinking water in the United States. In: Whitacre DM editor(s). Reviews of Environmental Contamination and Toxicology. Vol. 192, New York: Springer, 2008:117‐58. [PMC free article] [PubMed] [Google Scholar]
Rosa 2010
- Rosa G, Clasen T. Estimating the scope of household water treatment in low‐ and medium‐income countries. American Journal of Tropical Medicine and Hygiene 2010;82(2):289‐300. [PMC free article] [PubMed] [Google Scholar]
Savović 2012
- Savović J, Jones HE, Altman DG, Harris RJ, Jüni P, Pildal J, et al. Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials. Annals of Internal Medicine 2012;157(6):429‐38. [PubMed] [Google Scholar]
Sobsey 2002
- Sobsey MD. Managing water in the home: accelerated health gains from improved water supply [WHO/SDE/WSH/02.07]. Geneva: World Health Organization, 2002. [Google Scholar]
Sphere Project 2011
- The Sphere Project. Humanitarian Charter and Minimum Standards in Disaster Response. 3rd Edition. Rugby: Practical Action Publishing, 2011. [Google Scholar]
Stelmach 2015
- Stelmach RD, Clasen T. Household water quantity and health: a systematic review. International Journal of Environmental Research and Public Health 2015;12(6):5954‐74. [PMC free article] [PubMed] [Google Scholar]
URL 1995
- Universidad Rafael Landivar. Preventing infant morbidity: artisanal filters and education [Contra la morbilidad infantil: filtros artesanales y education]. Revista de Estudios Sociales 1995;IV(53):1‐66. [Google Scholar]
Waddington 2009
- Waddington H, Snilstveit B, White H, Fewtrell L. Water, sanitation and hygiene interventions to combat childhood diarrhoea in developing countries. http://www.3ieimpact.org/evidence/systematic‐reviews/details/23/. New Delhi, India: 3ie, (accessed 15 November 2014).
Walker 2013
- Walker CL, Rudan I, Liu L, Nair H, Theodoratou E, Bhutta ZA, et al. Global burden of childhood pneumonia and diarrhoea. Lancet 2013;381(9875):1405‐16. [PMC free article] [PubMed] [Google Scholar]
WHO 1993
- World Health Organization. The Management and Prevention of Diarrhoea: Practical Guidelines. 3rd Edition. Geneva: World Health Organization, 1993. [Google Scholar]
WHO 2011
- World Health Organization. Guidelines for drinking‐water quality, 4th edition. http://apps.who.int/iris/bitstream/10665/44584/1/9789241548151_eng.pdf. online: World Health Organization, (accessed 15 November 2014).
WHO 2014
- World Health Organization. The top 10 causes of death. Fact sheet N°310. http://www.who.int/mediacentre/factsheets/fs310/en/. online: World Health Organization, (accessed 15 January 2015).
WHO/UNICEF 2015
- WHO/UNICEF. Progress on drinking water and sanitation: Joint Monitoring Programme update 2015. http://www.wssinfo.org/fileadmin/user_upload/resources/JMP‐Update‐report‐2015_English.pdf. online: WHO/UNICEF, (accessed 2 February 2015):78.
Wood 2008
- Wood L, Egger M, Gluud LL, Schulz KF, Jüni P, Altman DG, et al. Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta‐epidemiological study. BMJ 2008;336(7644):601‐5. [PMC free article] [PubMed] [Google Scholar]
Wright 2004
- Wright J, Gundry S, Conroy R. Household drinking water in developing countries: a systematic review of microbiological contamination between source and point‐of‐use. Tropical Medicine & International Health 2004;9(1):106‐17. [PubMed] [Google Scholar]
Zhang 1998
- Zhang J, Yu KF. What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 1998;280(19):1690‐1. [PubMed] [Google Scholar]
References to other published versions of this review
Clasen 2006
- Clasen T, Roberts IG, Rabie T, Schmidt WP, Cairncross S. Interventions to improve water quality for preventing diarrhoea. Cochrane Database of Systematic Reviews 2006, Issue 3. [DOI: 10.1002/14651858.CD004794.pub2] [PubMed] [CrossRef] [Google Scholar]