Robert Bain and colleagues conduct a systematic review and meta-analysis to assess whether water from “improved” sources is less likely to contain fecal contamination than “unimproved” sources and find that access to an “improved source” provides a measure of sanitary protection but does not ensure water is free of fecal contamination. Please see later in the article for the Editors' Summary

ObjectivesTo estimate exposure to faecal contamination through drinking water as indicated by levels of Escherichia coli (E. coli) or thermotolerant coliform (TTC) in water sources.MethodsWe estimated coverage of different types of drinking water source based on household surveys and censuses using multilevel modelling. Coverage data were combined with water quality studies that assessed E. coli or TTC including those identified by a systematic review (n = 345). Predictive models for the presence and level of contamination of drinking water sources were developed using random effects logistic regression and selected covariates. We assessed sensitivity of estimated exposure to study quality, indicator bacteria and separately considered nationally randomised surveys.ResultsWe estimate that 1.8 billion people globally use a source of drinking water which suffers from faecal contamination, of these 1.1 billion drink water that is of at least ‘moderate’ risk (>10 E. coli or TTC per 100 ml). Data from nationally randomised studies suggest that 10% of improved sources may be ‘high’ risk, containing at least 100 E. coli or TTC per 100 ml. Drinking water is found to be more often contaminated in rural areas (41%, CI: 31%–51%) than in urban areas (12%, CI: 8–18%), and contamination is most prevalent in Africa (53%, CI: 42%–63%) and South-East Asia (35%, CI: 24%–45%). Estimates were not sensitive to the exclusion of low quality studies or restriction to studies reporting E. coli.ConclusionsMicrobial contamination is widespread and affects all water source types, including piped supplies. Global burden of disease estimates may have substantially understated the disease burden associated with inadequate water services.

Background Limited data have been available on the global practice of handwashing with soap (HWWS). To better appreciate global HWWS frequency, which plays a role in disease transmission, our objectives were to: (i) quantify the presence of designated handwashing facilities; (ii) assess the association between handwashing facility presence and observed HWWS; and (iii) derive country, regional and global HWWS estimates after potential faecal contact. Methods First, using data from national surveys, we applied multilevel linear modelling to estimate national handwashing facility presence. Second, using multilevel Poisson modelling on datasets including both handwashing facility presence and observed HWWS after potential faecal contact, we estimated HWWS prevalence conditional on handwashing facility presence by region. For high-income countries, we used meta-analysis to pool handwashing prevalence of studies identified through a systematic review. Third, from the modelled handwashing facility presence and estimated HWWS prevalence conditional on the presence of a handwashing facility, we estimated handwashing practice at country, regional and global levels. Results First, approximately one in four persons did not have a designated handwashing facility in 2015, based on 115 data points for 77 countries. Second the prevalence ratio between HWWS when a designated facility was present compared with when it was absent was 1.99 (1.66, 2.39) P <0.001 for low- and middle-income countries, based on nine datasets. Third, we estimate that in 2015, 26.2% (23.1%, 29.6%) of potential faecal contacts were followed by HWWS. Conclusions Many people lack a designated handwashing facility, but even among those with access, HWWS is poorly practised. People with access to designated handwashing facilities are about twice as likely to wash their hands with soap after potential faecal contact as people who lack a facility. Estimates are based on limited data.

The World Health Organization (WHO) and United Nations Children’s Fund (UNICEF), through the Joint Monitoring Programme (JMP), are responsible for global monitoring of the Sustainable Development Goal (SDG) targets for drinking water, sanitation and hygiene (WASH). The SDGs represent a fundamental shift in household WASH monitoring with a new focus on service levels and the incorporation of hygiene. This article reflects on the process of establishing SDG baselines and the methods used to generate national, regional and global estimates for the new household WASH indicators. The JMP 2017 update drew on over 3000 national data sources, primarily household surveys (n = 1443), censuses (n = 309) and administrative data (n = 1494). Whereas most countries could generate estimates for basic drinking water and basic sanitation, fewer countries could report on basic handwashing facilities, water quality and the disposal of waste from onsite sanitation. Based on data for 96 and 84 countries, respectively, the JMP estimates that globally 2.1 billion (29%) people lacked safely managed drinking water services and 4.5 billion (61%) lacked safely managed sanitation services in 2015. The expanded JMP inequalities database also finds substantial disparities by wealth and sub-national regions. The SDG baselines for household WASH reveal the scale of the challenge associated with achieving universal safely managed services and the substantial acceleration needed in many countries to achieve even basic services for everyone by 2030. Many countries have begun to localise the global SDG targets and are investing in data collection to address the SDG data gaps, whether through the integration of new elements in household surveys or strengthening collection and reporting of information through administrative and regulatory systems.

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Target 6.2 of the Sustainable Development Goals calls for universal access to sanitation by 2030. The associated indicator is the population using 'safely managed' sanitation services. Shared sanitation is classified as a 'limited' sanitation service and some donors and governments are reluctant to invest in it, as it will not count towards achieving Target 6.2. This could result in poor citizens in dense slums being left out of any sanitation improvements, while efforts are diverted towards better-off areas where achieving 'safely managed' sanitation is easier. There are sound reasons for labelling shared sanitation as 'limited' service, the most important being that it is extremely difficult -for global monitoring purposes -to differentiate between shared toilets that are hygienic, accessible and safe, and the more common ones which are poorly designed and managed. There is no reason to stop investing in shared sanitation. 'Safely managed' represents a standard countries should aspire to.However, the 2030 Agenda and the human rights recognise the need for intermediate steps and for reducing inequalities. This calls for prioritising investments in high-quality shared toilets in dense informal settlements where it is the only viable option (short of rehousing) for improving sanitation services.

BackgroundThe Sustainable Development Goals (SDGs) require household survey programmes such as the UNICEF-supported Multiple Indicator Cluster Surveys (MICS) to enhance data collection to cover new indicators. This study aims to evaluated methods for assessing water quality, water availability, emptying of sanitation facilities, menstrual hygiene management and the acceptability of water quality testing in households which are key to monitoring SDG targets 6.1 and 6.2 on drinking Water, Sanitation and Hygiene (WASH) and emerging issues.MethodsAs part of a MICS field test, we interviewed 429 households and 267 women age 15–49 in Stann Creek, Belize in a split-sample experiment. In a concurrent qualitative component, we conducted focus groups with interviewers and cognitive interviews with respondents during and immediately following questionnaire administration in the field to explore their question comprehension and response processes.FindingsAbout 88% of respondents agreed to water quality testing but also desired test results, given the potential implications for their own health. Escherichia coli was present in 36% of drinking water collected at the source, and in 47% of samples consumed in the household. Both questions on water availability necessitated probing by interviewers. About one quarter of households reported emptying of pit latrines and septic tanks, though one-quarter could not provide an answer to the question. Asking questions on menstrual hygiene was acceptable to respondents, but required some clarification and probing.ConclusionsIn the context of Belize, this study confirmed the feasibility of collecting information on the availability and quality of drinking water, emptying of sanitation facilities and menstrual hygiene in a multi-purpose household survey, indicating specific areas to improve question formulation and field protocols. Improvements have been incorporated into the latest round of MICS surveys which will be a major source of national data for monitoring of SDG targets for drinking water, sanitation and hygiene and emerging issues for WASH sector programming.

Background: The 2030 Sustainable Development Goals (SDGs) set an ambitious new benchmark for safely managed drinking water services (SMDWs), but many countries lack national data on the availability and quality of drinking water. Objectives: We quantified the availability and microbiological quality of drinking water, monitored SMDWs, and examined risk factors for Escherichia coli ( E. coli ) contamination in 27 low-and middle-income countries (LMICs). Methods: A new water quality module for household surveys was implemented in 27 Multiple Indicator Cluster Surveys. Teams used portable equipment to measure E. coli at the point of collection (PoC, ) and at the point of use (PoU, ) and asked respondents about the availability and accessibility of drinking water. Households were classified as having SMDW services if they used an improved water source that was free of E. coli contamination at PoC, accessible on premises, and available when needed. Compliance with individual SMDW criteria was also assessed. Modified Poisson regression was used to explore household and community risk factors for E. coli contamination. Results: E. coli was commonly detected at the PoC (range 16–90%) and was more likely at the PoU (range 19–99%). On average, 84% of households used an improved drinking water source, and 31% met all of the SMDW criteria. E. coli contamination was the primary reason SMDW criteria were not met (15 of 27 countries). The prevalence of E. coli in PoC samples was lower among households using improved water sources [ ; 95% confidence interval (CI): 0.64, 0.85] but not for households with water accessible on premises ( ; 95% CI: 0.94, 1.05) or available when needed ( ; 95% CI: 0.88, 1.02). E. coli contamination of PoU samples was less common for households in the richest vs. poorest wealth quintile ( ; 95% CI: 0.55, 0.88) and in communities with high ( ) improved sanitation coverage ( ; 95% CI: 0.90, 0.97). Livestock ownership ( ; 95% CI: 1.04, 1.13), rural vs. urban residence ( ; 95% CI: 1.04, 1.16), and wet vs. dry season sampling ( ; 95% CI: 1.01, 1.15) were positively associated with contamination at the PoU. Discussion: Cross-sectional water quality data can be collected in household surveys and can be used to assess inequalities in service levels, to track the SDG indicator of SMDWs, and to examine risk factors for contamination. There is an urgent need for better risk management to reduce widespread exposure to fecal contamination through drinking water services in LMICs. ...