The importance of disaggregated data to inform action and understand inequalities in WASH

Water quality testing in Solomon Islands

Monitoring safely managed water and sanitation services

By Freya Mills and Prof. Juliet Willetts, University of Technology Sydney Institute for Sustainable Futures

Water for Women’s recent webinar on monitoring safely managed water and sanitation services highlighted the importance of using monitoring to understand and reduce inequalities. Inequalities and inclusion are a central focus of Water for Women and of the United Nations Sustainable Development Goals (SDGs).

The SDG agenda commits to ‘leave no one behind’, with SDG 6.1 targeting equitable access to safe and affordable drinking water for all. SDG 6.2 also specifically pays special attention to the needs of women and girls and those in vulnerable situations. Tracking these is therefore critical to achieve universal access and ensure progressive realisation of the rights to water and sanitation.

The below brings together insights from Water for Women case studies and webinar discussions on the approaches and challenges to monitoring inequalities in access to safely managed services.


Inequalities monitored through household surveys

Household surveys are a valuable source to monitor inequalities as they can permit disaggregation across multiple dimensions of potential disadvantage. For instance, disaggregation is usually possible based on wealth, gender (e.g., female-headed households, women’s and girls’ access), specific groups (e.g., people with disability, ethnicity, other locally specific considerations) or geographic context (e.g., informal settlements, urban or rural areas). Through this disaggregation of data, we can often better understand who is missing out on safely managed services and where improvement efforts should be targeted.

For example, monitoring by SNV in Lao PDR (Figure 1) showed significantly lower access to safely managed toilet facilities for the poorest two wealth quintiles. This data also showed, counter-intuitively, that highest access was by the middle quintile, not the upper quintile as might have been expected.

Figure 1. Access to safely managed toilet facilities in Lao PDR disaggregated by wealth quintile (SNV 2020)
Figure 1. Access to safely managed toilet facilities in Lao PDR disaggregated by wealth quintile (SNV 2020).

Disaggregation of data on safely managed water in the latest Joint Monitoring Programme progress report highlighted the variations in inequalities, as some countries faced major gaps in accessibility while for others, the inequality was most evident in the water quality.

Various other case studies also highlighted that expanded indicators may be necessary to better understand inequalities. For example, inequalities were more evident when seasonal aspects of drinking water availability were assessed by the International WaterCentre at Griffith University in  Solomon Islands.  Similarly, recent Indonesian water quality survey data presented by Nur Aisyah Nasution from Indonesia’s National Development Planning Agency (Bappenas) in the webinar showed that female-headed households were less likely to have hand pumps than male-headed households.


Limited data on inequalities for some aspects of safely managed services

While assessing inequalities can be achieved through household data, many aspects of safely managed services are informed by non-household data sources. For example, data on water quality, excreta management in on-site systems and wastewater treatment come from different administrative data sources such as service providers, authorities or regulators. Often such data cannot be disaggregated in the way household data can, and inequalities may remain invisible. Further work is needed to support the integration of these data sources with household data to improve monitoring inequalities.  


Geographic disaggregation is important to inform action

Disaggregating safely managed data on a geographical basis is typically possible for both household and non-household sources and shows the variation in access between regions or inequalities based on geography (e.g., urban and rural, informal settlements, remote island, etc.). In the webinar, various partners stated that sub-national data were particularly valuable to inform action as they provide context specific data to those making decisions and acting at a local level.


Aligning wealth measures

Within household surveys, aligning monitoring of water and sanitation services with other existing in-country monitoring systems was important to enable disaggregation of safely managed service data, and this was particularly true in relation to measures of wealth.

The WaterAid case study in Papua New Guinea (PNG) noted that countries often have differing indicators or means to measure wealth. WaterAid therefore partnered with Metrics for Management, an organisation specialising in statistics, using Equitytool to identify the questions most relevant to assessing wealth for the PNG context, which were then integrated in their RapidWASH monitoring system.

SNV uses the asset-based index developed by the Demographic and Health Survey’s (DHS) Program and for accessibility. They also use the Washington Group Short Question, supplemented by focus group discussions and individual surveys to understand disability. Both were chosen because these measures are already commonly applied in the sector, and wealth quintiles are used by JMP and within national level surveys.

In Indonesia, Nur Aisyah Nasution from Bappenas noted during the webinar that they collaborated with the Bureau of Statistics to design the national water quality survey so that it used the same survey units and blocks, enabling it to be combined with larger scale household survey data and be disaggregated to assess inequalities.

Both SNV and WaterAid noted that the analysis of wealth and disaggregation of data was complex, and while other monitoring aspects were easily adopted by their government partners, this analysis was difficult and often required external support. WaterAid also noted that many countries (particularly in Southeast Asia) are undergoing rapid economic growth, which mean indicators of wealth are dynamic and questions around wealth need to consider that people may change wealth quintiles between survey rounds. 


Use of inequality data

Disaggregated data proved to be valuable to make inequalities visible to the decision-makers. In Wewak district in PNG, WaterAid’s baseline data was presented to local government officers to show that the ward’s poorest households practiced open defecation. Having this data enabled the highest priority areas to be invested in and ensured poorer households were included in community engagement and awareness programs.

In Indonesia, data on inequalities has been used to develop micro-credit and grant programs and policies for household-level services and where national, local or donor funds should be targeted. Nur Aisyah Nasution from Bappenas  highlighted that their data currently is only disaggregated for basic access and further data and research is needed to understand the inequalities in access to safely managed services to better inform investment.


Using complementary methods

Where service provider or administrative data does not capture inequalities, other methods can be used to supplement this data – such as interviews or focus group discussions.

SNV conducted interviews to better understand intra-household inequalities. Interviews with elderly, people with a disability or with organisations that work with vulnerable populations were used to compliment household surveys to provide qualitative evidence of intra-household inequalities. CFAR engaged community volunteers to conducts surveys within their slums, as informal communities are often excluded from formal data collection efforts.

There remain challenges in monitoring safely managed services in hard-to-reach communities, such as remote Pacific islands or rural hill communities, particularly given water quality testing and assessment of on-site containment requires in-field assessment by trained enumerators and therefore cannot be done remotely. Winnie Sagiu from East Sepik Provincial Health Authority in PNG noted in the webinar that when monitoring occurred in rural and remote communities, this often raised expectations that WASH services would be provided. Careful explanation of the monitoring objective and managing expectations in infrequently monitored areas was important.


Looking forward

While it is important to increase data on inequalities in access to safely managed services, Rick Johnston from the WHO and UNICEF JMP suggested that given that many countries don’t yet have national estimates, our priority should first be to establish national estimates. From there, there is opportunity to take forward the different approaches to monitoring inequalities described above and ensure these inform decisions to progress safely managed services for all.


Photo credit: Regina Souter, International WaterCentre.

Water for Women acknowledges Freya Mills and Professor Juliet Willetts of the University of Technology Sydney, Institute for Sustainable Futures for their leadership of this collaborative Learning Agenda initiative and the development and collation of the reports. We also gratefully acknowledge the contribution of Avni Kumar, and the following partners which made extensive contributions to this initiative: SNV Netherlands Development Organisation, the International WaterCentre of Griffith University, WaterAid, iDE, the Centre for Advocacy and Research, India, Habitat for Humanity, Thrive Networks East Meets West, and the University of Technology Sydney Institute for Sustainable Futures.


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