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.

Sustainable Development Goal target 6.2 calls for universal access to adequate and equitable sanitation, setting a more ambitious standard for ‘safely managed sanitation services’. On-site sanitation systems (e.g., septic tanks) are widely used in low- and middle-income countries (LMICs). However, the lack of indicators for assessing fecal exposure risks presents a barrier to monitoring safely managed services. Furthermore, geographic diversity and frequency of disasters require a more nuanced approach to risk-informed decision-making. Taking Indonesia as an example, the purpose of this paper is to provide insights into current status and practices for on-site sanitation services in the contexts of LMICs. Using a dataset from a national socio-economic survey (n = 295,155) coupled with village census (n = 83,931), we assessed (1) household sanitation practices across Indonesia stratified by city-level population density and meteorological factors, (2) factors associated with septic tank emptying practice, and (3) inequalities in potential fecal exposure as measured by population density and WASH access by wealth quintile. We found a high reliance on on-site sanitation facilities (80.0%), almost half of which are assumed to be ‘uncontained’ septic tanks and one in ten facilities discharging untreated waste directly into the environment. The most densely populated areas had the highest rates of septic tank emptying, though emptying rates were just 17.0%, while in the lowest population density group, emptying was rarely reported. Multivariate regression analysis demonstrated an association between flooding and drought occurrence and septic tank emptying practice. Higher groundwater usage for drinking among poorer households suggests unsafe sanitation may disproportionally affect the poor. Our study underscores the urgent need to strengthen the monitoring of on-site sanitation in LMICs by developing contextualized standards. Furthermore, the inequalities in potential fecal exposure require greater attention and tailored support mechanisms to ensure the poorest gain access to safely managed sanitation services.

Background: The Sustainable Development Goals set an ambitious new benchmark for safely managed drinking water services (SMDW), but many countries lack data on the availability and quality of drinking water. Objectives: To quantify the availability and microbiological quality of drinking water, monitor SMDW and examine risk factors for E. coli contamination in 20 low-and middle-income countries. Methods: A new water quality module for household surveys was implemented in Multiple Indicator Cluster Surveys. Teams used portable equipment to measure E. coli at the point of collection (PoC, n=48,323) and at the point of use (PoU, n=51,345) and asked respondents about the availability and location of drinking water services. E. coli levels were classified into risk categories and SMDW was calculated at the household- and domain-levels. Modified Poisson regression was used to explore risk factors for contamination. Results: E. coli was commonly detected at PoC (range 16-90%) and was more likely at PoU (range 20-97%). Coverage of SMDW was 56% points lower than improved drinking water with water quality the limiting factor for SMDW in 14 countries. Detection of E. coli at PoC was associated with use of improved water sources (RR=0.64 [0.52-0.78]) located on premises (RR=0.78 [0.67-0.91]) but not with availability (RR=0.94 [0.82-1.06]). Households in the richest quintile (RR=0.67 [0.50-0.90]) and in communities with high (>75%) improved sanitation coverage (RR=0.95 [0.91-0.98]) were less likely to use contaminated water at PoU whereas animal ownership (RR=1.08 [1.03-1.14]) and rural residence (RR=1.11 [1.03-1.19]) increased risk of contamination. Discussion: Water quality data can be reliably collected in household surveys and can be used to assess inequalities in service levels, to track the SDG indicator of SMDW, and to examine risk factors for contamination. There is an urgent need to implement scalable and sustainable interventions to reduce exposure to faecal contamination through drinking water.