1. Introduction: Depicting access to water and sanitation in the United States

A nation with the wealth and development of the United States (U.S.) should have universal access to potable water and sanitation services. And yet, current estimates of the U.S. population lacking access to potable water and sanitation range significantly - from 1.4 million [2], to more than 2 million [3], to potentially tens of millions, when accounting for water quality as well as lack of plumbing [4]. This range of estimates is because the U.S. system lacks the underlying data to accurately account for the scope of the true problem.

In conversations with people outside of this work, the first question is often “where are these people and communities located”? And the honest answer is “no one really knows exactly.” And, while the public has some awareness of these challenges, it is easily perceived that these are temporary problems caused by a broken water main or a major storm event. There is no national-level dataset that comprehensively identifies each community lacking access, therefore making systematic and national-level solutions more difficult.

Existing systems rely on incomplete information through the U.S. Census/American Community Survey (ACS) or a public health worker to report a water-borne disease outbreak or observe a lack of facilities. There are some emerging state-level datasets - including California’s Open Data Initiative SAFER Dashboard [5], New Mexico’s Water Data Initiative (New Mexico Water Data, n.d.), and a recently announced effort in Arizona building a Water Data Portal [6] - to begin to understand access and related issues, but nothing comprehensive that would allow the sector to methodologically identify and address the issue nationally.

In this essay we will provide an overview of the existing dispersed sources of national government data used to estimate water, sanitation, and hygiene (WaSH) access in the U.S. We show how the systems for collecting data on access to plumbing infrastructure, drinking water quality, and water effluent violations are produced by different government agencies and bureaus, with different histories and mandates, all producing an incomplete picture of WaSH insecurity in the U.S. within their silos much less for providing a complete picture of WaSH access, impairing efforts to identify underserved communities to assist them in accessing these most basic services. We then discuss several initiatives to use digital platforms to better depict the U.S. WaSH insecure population. Identifying “where these people are” is key to changing practice and policy toward improving access to WaSH services.

2. From identifying that there’s a problem to systematic measurement of WaSH in the U.S. context: A brief overview

Since the turn of the millennium, the global WaSH community has been engaged in the development of what Molle, et al. [7] (somewhat derisively) refer to as “metrics, indicators, and quantification practices” intended to better depict progress toward meeting first the Millennium Development Goals (MDGs) and then the Sustainable Development Goals (SDGs) [1]. Significant effort has gone into the development of data to indicate progress toward achieving SDG 6 – universal access to potable water and sanitation, specifically in low and middle-income countries [8,9]. While we recognize the potential perils of what Alexius and Vähämäki [10] call “obsessive measurement disorder,” the development of these indicator systems has vastly improved conceptualization of the global WaSH challenge, “beyond the simple classification of a source as improved or unimproved” water access, to assessing water quality and the functionality of sanitation [11, p. 2; 12]. There is growing concern about meeting SDG6 in high income countries [13–15]. In the European Union, for instance, “Eurostat” provides a comprehensive overview of statistics on “sanitation, water quality and water scarcity” [16]. While Roaf and Winkler [17] note minoritized populations such as the Roma people and the unhoused are insufficiently captured in the data, the data provides a baseline that allows for that discussion. The U.S. has no such comprehensive data initiative to track progress toward achieving SDG6 or tracking WaSH access. While the World Health Organization/United Nations Children’s Fund Joint Monitoring Programme tracks U.S. WaSH statistics using a combination of the American Housing Survey (AHS) and the Safe Drinking Water Information System (SDWIS), below we will describe how these sources are problematic [1,18].

In the U.S. while nascent, there is a growing literature about access to water and sanitation. Concerns about water and sanitation access have grown due to high-profile crises including: water shutoffs in Detroit, Michigan [19–21]; lead-tainted water in Flint, Michigan [22,23] and Benton Harbor [24]; water system failures in Jackson, Mississippi [25,26]; pandemic-exacerbated water access challenges in the Colonias and Navajo Nation [27–31]; sanitation failures in Lowndes County, and other counties in Alabama including homes with straight pipes and mismanagement of onsite raw sewage [32–34]; cases of untreated sewage disposal in Appalachia [35], as well as concerns about cesspools in Hawaii and New York, both of which have been linked to water quality concerns [36–38]; and sanitation for the unhoused population [33,39].

While these cases have begun to capture the public imagination, the true breadth and depth of the U.S. water crisis is unknown due to a lack of data. Current estimates from the literature of the U.S. population lacking access to potable water and sanitation range significantly - from 463,649 occupied households or 1.4 million people [2], to more than 2 million by adding the unhoused population and those in the territories [3], to potentially tens of millions [4] as the U.S. system lacks the underlying data to accurately account for the scope of the problem . Alarmingly, Meehan, et al. [40] find evidence that the population lacking access to complete plumbing increased in cities from 2008 to present. It is clear from the analysis that has been done that the geographic scope of the problem spans the entire country - not just those places that hit the headlines [2,4,41].

The estimates above vary because the data on access to water and sanitation in the U.S. are housed in multiple agencies, each of which provide only partial indicators of the number and location of those whose conditions do not meet the SDG6 standard of sustainable “access to safe water, sanitation and hygiene” [42]. This is compounded by there being indicators of SDG6, such as water and wastewater rate affordability, the quality of self-supply water and sanitation, and data on the unhoused population without water and sanitation, which are either uncounted by the federal government or highly inaccurately counted [33,43,44].

The problem is partly the decentralized nature of the U. S. water and sanitation landscape. While 90% of U.S. residents receive water through public water systems (PWS), this leaves approximately 13 million people receiving their drinking water through self-supply [45]. There are approximately 140,000 PWS in the U.S., about 50,000 of which are community water systems (CWS) that serve at least 15 year-round connections and at least 25 people year-round [46]. As of 2023, the EPA estimated that 28% of PWS and 43% of CWS had at least one violation of Safe Drinking Water standards, and 4% of PWS and 7% of CWS had at least one health-based violation [47]. Between 15% and 25% percent of households (up to 32 million people) are not connected to public sewer systems [33]. There are neither rigorous and comprehensive estimates of onsite drinking water quality nor of the functionality of onsite wastewater treatment systems [48,49], though impairment of water quality in general can be assessed through violations of the Clean Water Act [45].

Attempts to comprehensively estimate WaSH access in the U.S. have utilized four sources of data: The American Housing Survey (AHS); The U.S. Census American Community Survey (ACS); The EPA Environmental Community Health Online (ECHO); and the U.S. Geological Survey (USGS) National Water Quality Assessment (NAWQA). Table 1, below, is a description of these data sources and a sampling of where they have been used.

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Table 1. datasets that record information about WaSH in the U.S.

https://doi.org/10.1371/journal.pwat.0000498.t001

Each of these data sources depicts a part of the problem for WaSH in the U.S., but all have important weaknesses. In all cases, there are limitations in the coverage, the accuracy of data, and the difficulty of combining the different datasets. Below are descriptions of the data sources summarizing their history, what they measure, and ways these measures are incomplete.

The AHS dates to the “Annual Housing Survey” developed in 1939 to track U.S. government programs to improve housing as part of the “New Deal” – economic development initiatives launched by the Franklin Delano Roosevelt administration that were intended to spur recovery from “the Great Depression” of the 1930s. In 1970, the U.S. Department of Housing and Urban Development (HUD) took over the survey, changing the name to the American Housing Survey (AHS), to be conducted biannually by the Census Bureau to assess the state of the U.S. housing stock [62]. The AHS attempts to be able to characterize housing conditions across the U.S. through using a geographically representative “integrated national sample” of survey recipients. The actual sample size varies over time, but in 2023 (the most recent year), at the time of this writing, the Census created for AHS an “integrated national sample” from which they distributed 96,951 surveys, receiving on 59% response rate of a total of 55,669 responses. They additionally surveyed 3,000 housing units involved in longitudinal studies in the 10 municipalities, totaling 32,000 additional responses, for a total of 87,669 responses [63]. The survey specifically asks about access to plumbing facilities, including asking if households have hot and cold running water, a bath and/or shower, and a toilet. The AHS concentrates its survey in metropolitan areas, though it does contain estimates for rural localities. The sample, however, is too small to be reliable for localities across the U.S. [63]. Table 2, below shows the water and sanitation questions on the AHS.

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Table 2. American Housing Survey on Water and Sewer Access (The AHS questions on water and sewer are not located on one page, so this table compiled the questions from the 2023 American Housing Survey Instrument Items, https://www2.census.gov/programs-surveys/ahs/2023/2023__AHS_Items_Booklet.pdf).

https://doi.org/10.1371/journal.pwat.0000498.t002

Most U.S. analysts accounting for the population lacking access to potable water and sanitation have turned to the ACS. Using available data tools, the ACS can provide estimates at multiple geographic units – from national estimates to state, region, county, Census tract, block group and place [64]. Given that the estimate is based on a sample of roughly 3 percent of U.S. households, the margins of error can be significant. The ACS strengthens the estimates using 1 year, 3 year, and 5 year rolling averages – the latter giving the most accurate estimate. While the ACS calculates estimates of occupied households lacking “complete plumbing facilities” down to the Census “block group” level (a level that estimates the rough size and population of a city block, but geographically dispersed across the United States), the accuracy of the estimate, especially in rural geographies, is questionable. At the block group, the estimated error is almost always greater than the actual estimated figure at the block group level (The error term is so great as to make the statistics at the Block Group level suspect. The error term is more acceptable at the ZCTA level (a rough estimate for Zip Code), Census Tract, County levels, and “Public Use Microdata Areas” (PUMAs). PUMAs “are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each”). Various scholars have used Census Tracts [3], County [65], and PUMAs [2,41].

The different units of analysis (1 year, 3 year, and 5 year rolling averages) can provide different kinds of findings with regard to WaSH access. For instance, using Census Tracts, or Zip Codes, researchers can report on access to complete plumbing at a more localized scale, noting differences within counties (which is important especially in Western U.S. states where counties can be very large). The problem is that ACS only contains data on access to plumbing and demographics. To do the kind of analysis that would get at potable water and functional sanitation would require integrating data from the ECHO and USGS data (see below), and the county is the common unit of analysis across these data sets.

All of these previously mentioned measures are also likely to contribute to the current misrepresentations of actual populations which are lacking access to water and sanitation. There are several reasons for this. First, as Maxcy-Brown et al. [33] have noted, the ACS questionnaire only goes to households, which means that unhoused people are not counted in the access to plumbing facilities question (The population of unhoused in the U.S. is estimated through an annual census based on a “point in time count” and a “household inventory count” of unhoused people and access to housing taken on a January day in places across the United States, supervised by the Department of Housing and Urban who are receiving government services are counted in the ACS, because of small sample sizes to use this data to estimate water and sanitation services for this population [66]). While unhoused people who are receiving government services are counted in the ACS, because of small sample sizes it is impossible to use this data to estimate WaSH services for this population [66,67]. The census of homelessness does not specifically ask about access to water and sanitation facilities. For instance, what should the person answer if they live in Appalachia in a house with (1) a sink in the kitchen, (2) a bathtub and shower, and (3) a hot water heater so they could have hot and cold water , but what comes out of those taps is so contaminated that they can’t use the water safely for bathing, much less drinking and cooking?). Due to the need for anonymity of relatively small sample statistics, we have no way to know which communities are being surveyed at a given time. Second, the set of plumbing questions asked by the Census ACS is hard to interpret – especially if we are interested in access to potable water and functional sanitation, and not just whether people have the plumbing infrastructure that would theoretically deliver water (For instance, what should the person answer if they live in Appalachia in a house with (1) a sink in the kitchen, (2) a bathtub and shower, and (3) a hot water heater so they could have hot and cold water,- but what comes out of those taps is so contaminated that they can’t use the water safely for bathing, much less drinking and cooking?).

From 2016-2024, the Census (at the request of Congress) further obfuscated data on household access by eliminating the questions from the ACS about whether people had a flush toilet or other forms of sanitation. The 2025 survey includes questions about whether an occupied house has hot and cold running water, a bathtub or shower, a sink with a faucet, and connectivity to a public sewer [3,4,53,68,69] (See, Fig 1).

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Fig 1. U.S. Census American Community Survey Plumbing Questions (Pulled from The American Community Survey – Informational Copy (2025),https://www2.census.gov/programs-surveys/acs/methodology/questionnaires/2025/quest25.pdf).

https://doi.org/10.1371/journal.pwat.0000498.g001

Water Quality Violations: The Enforcement and Compliance History Online (ECHO) database [70] was developed by EPA in 2002 to “provide a place for members of the public to search for facilities in their community and review the facility’s compliance with environmental regulations” [71]. The ECHO data reports on violations of water quality but only measures the quality of drinking water and wastewater in utilities, while millions in the U.S. drink from private wells and have onsite wastewater systems. ECHO can be used to investigate a range of environmental compliance issues including air quality, hazardous waste, water quality, and drinking water system compliance with regulations. The ECHO database can be used to identify communities where wastewater and water utilities are persistently out of compliance with regulations. These regulations fall under two categories --those developed as part of the Clean Water Act (CWA) of 1972 and those that fall under the Safe Drinking Water Act of 1974.

The Clean Water Act of 1972 sought to address badly impaired water quality in the U.S. in the early 1970s, by which time waterways were so impaired that fish kills, harmful algae blooms and severe contamination were chronic. The famous Cuyahoga River fire of 1969, an event that was amplified by the media, shocked the nation, but was neither unique to the Cuyahoga nor other U.S. rivers in the mid-century industrial boom years [72]. The U.S. Congress established an office in the U.S. Environmental Protection Agency (EPA) (established just two years before in 1970) charged with implementing the CWA, and making the waters of the U.S. “swimmable, fishable, and drinkable.” The mechanism to do this was through requiring permits under the National Pollution Discharge Elimination System (NPDES) from all entities that were discharging into waterways. This included wastewater facilities and industry. NPDES violations are now reported through ECHO, including a marker of significant non-compliance for facilities that have repeatedly failed to comply with NPDES standards [73]. Mueller and Gasteyer [4] and Fedinick, et al. [56] used the listing of NPDES violations to indicate communities exposed to inadequate water quality. ECHO data on NPDES violations, however, currently do not specify which violations contaminate drinking water, especially for people on self-supply wells [74].

Noting that the CWA neither addressed drinking water from water utilities nor groundwater contamination, activists pushed through the Safe Drinking Water and Groundwater Act of 1974, shortened to the Safe Drinking Water Act (SDWA). The SDWA developed regulatory standards for public drinking water systems (e.g., those serving more than one household) [75]. The 1996 amendments to the SDWA expanded the list of regulated contaminants and established mechanisms of informing the public about the state of drinking water delivered through public water systems (PWS). A PWS is classified as a water system that serves more than 25 people. In response, EPA established the “Safe Drinking Water Information System” (SDWIS), a database that compiles reports from the state agencies on water systems and their compliance with regulations, which have been folded into ECHO. The system tracks PWS regulatory compliance [76]. Compliance is now ranked in the SDWIS on ECHO ranging from least worrisome (a one-time failure to report) to most worrisome (repeated violations of “maximum contaminant levels” that may affect public health) [57].

Some researchers [53,77] have noted that neither the SDWA nor the CWA data adequately characterize the risk of water quality impairment, especially for the estimated 43 million U.S. residents on self-supply drinking water and onsite wastewater treatment.

The U.S. Geological Survey (USGS) National Water Quality Assessment (NAWQA) provides a composite estimate of the population on self-supply by state, and an estimate of potential contaminants to groundwater and surface water by state and region. NAWQA “integrates publicly available water-quality data from [..] USGS, the […] EPA, and over 400 state, federal, tribal, and local agencies” [78] into a website from which one can search data to estimate the risk of exposure for those on self-supply [78]. While this may serve as a proxy measure of risk, the coverage is limited to where USGS or partners are sampling [80].

3. How this data has been used in WaSH assessments

Throughout the 2000s, scholars and advocates have used various government data sets to document the spatial, socio-economic, and racial characteristics of communities where people continued to lack access to potable water and functional sanitation in the United States. For instance, RCAP [81] and Westcoat, et al. [52] used the 2000 Census “Long Form” to document the approximately 640,000 households (approximately 1.6 million people) lacking access to complete plumbing facilities by county, state, race, ethnicity, and social class (e.g., income and poverty). More recent studies have shown a decrease in the number of households lacking access to plumbing. Using a 5-year rolling average of ACS data, [54] estimated 540,000 occupied households in the 2010–2014 dataset, Dietz and Meehan (2019) estimated 468,000 using the 2012–2016 ACS, DigDeep and U.S. Water Alliance report [3] added the population lacking plumbing in Puerto Rico and the unhoused population to estimates that approximately 2,000,000 people lacked access to complete plumbing facilities, and Meehan, et al. [2] used the 2013–2017 ACS to estimate 471,000 households or 1.12 million people as water insecure.

Gasteyer and Mueller [4] added to the estimation of those lacking complete plumbing, the population living in communities with water systems designated as “serious violators” (systems persistently in violation of Safe Drinking Water Act regulations) and “significant non-compliers” (wastewater systems persistently in violation of Clean Water Act regulations). Using this as an estimate, the population lacking access to potable water and sanitation is potentially much larger, possibly in the tens of millions.

The literature on access to complete plumbing has focused on significant racial effects, specifically noting that American Indians and Alaska Natives are 19 times as likely, and African Americans and Hispanic/Latinxs are two times as likely as White Americans to lack complete plumbing [3,82]. Even as the existing data can highlight inequities, the available data has significant gaps. For example, Maxcy-Brown, et al. [33] note that neither ACS nor ECHO data highlight the lack of reliable data on sanitation – specifically the extent to which the data fails to account for failing onsite systems and sanitation for the unhoused population.

Recent scholarship focused specifically on drinking water quality violations. Allaire, et al. [59] found that small, rural, municipal, community systems were more likely to repeat violators of regulations. Scanlon, et al. [57] used analysis of NAWQA and SDWA data and found significant spatiotemporal variability in the type of water violations – likely due to geophysical or other conditions exogenous from the water system itself. Teodoro and Switzer [58] and MacDonald and Jones [83] found race and income affected the odds of living in a community with initial and repeat violations.

While these assessments provide some indicator of the U.S. population lacking plumbing, they leave out important issues that practically impair access to water and sanitation. Below we will summarize key areas neglected.

4. Gaps in Government data: Affordability

Through the first two decades of the 21^st century, there were growing concerns among activists and scholars about the affordability of U.S. water and sanitation services. Tariffs (referred to as rates in the U.S.) were rising much faster than other consumer prices and disproportionately burdened those least able to pay [75]. Scholarship has documented that water rates were indeed high especially in poorer, deindustrialized cities, communities of color, smaller, privatized utilities, and that higher rates could result in negative impacts including water shutoffs [79,84–87]. Teodoro and Theile [88] used a survey of utility water rates to demonstrate that rates have increased faster than inflation and that rate policies have become more regressive through the second decade of the century. Recently, both scholars and activists have linked the problem to water infrastructure financing gaps that also gained attention during this period [89,90].

In response, universities and water industry organizations have developed digital tools for rate analysis. For instance, the American Water Works Association (AWWA) updated its Water and Wastewater Rate Survey [91,92] with a new digital platform that contains rate data collected in collaboration with the University of North Carolina Environmental Finance Center (EFC) every 6 months, currently with data from 450 water utilities and 388 wastewater utilities representing size and geography across the 50 states. While the AWWA tool provides overall estimates of water rates, trends and averages, its use to understand localized water and sanitation affordability is limited because of sample size and accessibility, since AWWA membership is needed to access it [93]. Hughes et al. [94] designed the municipal drinking water database (MDWD), using ACS, SDWIS, costs to utilities and to households from 2,000 municipal water districts across the 48 contiguous U.S. states. Their data indicate that rates vary considerably across places, and that community size, water source, climatic conditions, and racial makeup of the community impact cost to households.

The Nicholas Institute at Duke University [95] developed a national dashboard for water affordability based on five metrics: minimum wage hours to pay for water services; household burden of water rates at the 50th and 20th income percentile in the area; percent of income by quintile for water services; poverty prevalence in the community; and the affordability burden for households. This is all calculated by tabulating water rates as posted by community water systems, geographic information on service area, and the Census ACS 5-year rolling average at the ZCTA (Census estimated postal code level) [95]. Teodoro and Saywitz [58] used the affordability dashboard to estimate that water rates averaged 12.4 percent of household income at the 20^th percentile of income. Patterson & Doyle [61] used a combination of datasets on affordability including the water affordability dashboard from the Duke University Nicholas Institute to estimate that between one tenth and one third of households could be working more than one day per month to pay their water bills.

Under the Biden administration, the EPA established several dashboards intended to better track water infrastructure financing needs and the water and wastewater rates. These include:

1. the Water Affordability Needs Assessment [96] which provides a meta-analysis of previous studies on the water rates and affordability;
2. 2022 Clean Watersheds Needs Survey (CWNS) [97], an update of the 2012 needs assessment provided “an assessment of the capital investments necessary for states, the District of Columbia, and U.S. Territories to meet the [CWA] water quality goals over the subsequent 20 years.” (p. 1). The survey notably included estimated infrastructure costs for publicly owned wastewater treatment works, stormwater treatment, nonpoint source control, and, for the first time in a survey, decentralized (onsite) wastewater treatment. A dashboard provides estimates of investment needs by category, by state.
3. 7th Drinking Water Infrastructure Needs Survey and Assessment [98], an update of 6^th Drinking Water Needs Survey in 2018, estimated needed investment for public drinking water systems for distribution and transmission, treatment, storage, and source water management and protection. This dataset dashboard provides data by state, need type, and water system size.
4. The Closing America’s Wastewater Access Gap, an initiative through the Infrastructure Investment and Jobs Act to address wastewater needs in low income and disadvantaged communities. The pilot phase of the initiative, starting in 2022, targeted 11 historically marginalized communities in 10 states, providing technical assistance to help them identify resources and financing to address long-standing wastewater problems [45].

All of these dashboards remain live and accessible as of December 2025. While useful in conveying the magnitude of water and wastewater financing issues and concern about affordability, their utility in addressing localized concerns for most communities is limited. The two needs assessments provide data about drinking water and clean water financing only at the state level, and the Closing America’s Wastewater Access Gap only documents conditions in selected pilot projects.

While there has been increasing concern about targeting funding to disadvantaged communities under the Biden administration, there has been a recognition that disadvantaged communities have significant difficulty accessing needed funding, even when the financing is in the system. For example, Miller, et al. [99] found a far lower percentage of Alabama CWA State Revolving Fund expenditures went to disadvantaged communities than was warranted based on estimated need.

5. Data that drives action: efforts to develop data portals to improve WaSH access

Given this concern about access to water and sanitation data, there has also been a growth in papers calling for improvements. The affordability and financing dashboards above, including by the EPA, attempt to provide data to estimate the problem at least to the level of the state and municipal systems. We build on others who want to go further. Josset, et al. [103] called for building a national data portal to fill significant data gaps on potable water supply and sanitation. They assert that WaSH access gaps in the U.S. are in part due to water and sanitation access data being dispersed across agencies and states. While efforts underway to create dashboards to address information gaps are praiseworthy, they fail to address the scope of issues that impair U.S. WaSH access. For many communities lacking access, the issue is a combination of affordability and financing, lacking or deteriorating infrastructure, water quality concerns, issues of accessibility to the expertise and resources to address persistent issues, and the ability to navigate the bureaucratic requirements of upgrading infrastructure. Many excellent dashboards address a piece of this puzzle.

There has been some effort to develop dashboards that can be used to identify water quality concerns. For instance, Ravalli, et al. [104] drew on analysis through the Columbia University Drinking Water Dashboard to estimate radon levels in U.S. drinking water. The Columbia University dashboard combines ECHO data to allow exploration of water contaminant concentrations across space and time [See, also, 105].

The efforts by the U.S. EPA to develop a tool to identify marginalized communities is indicative of the politicization of this issue. Under the Biden administration (2021–2025), U.S. EPA developed EJ Screen to map environmental inequality in the U.S., including data on access to and quality of and access to water and sanitation across the U.S. using both ACS and ECHO data [75]. The subsequent Trump administration scrapped EJ Screen along with much of the Environmental Justice program soon after coming into office.

In a broader initiative, the Internet of Water (IoW) uses an internet platform developed by a “group of organizations working together with federal, state, and local government partners to build foundational water data infrastructure across the U.S. and create a community of people and organizations using water data to make better decisions. The initiative aims to build data infrastructure, empower communities, and build a sustainable network of water data producers, users, and decision-makers … to advance the uptake of modern technologies and improve water management outcomes” [94].

6. Discussion: Is there a need to develop more robust indicators?

We believe an open access dashboard could provide community activists and allies with tools to make a case for intervention in those communities that have been chronically underserved. Right now, activists must do the work of combining data from the multiple existing sites discussed above to comprehensively address access to WaSH in the U.S. Each of the data initiatives above addresses one part of the problem -- water quality, clean water violations, access to plumbing, affordability and financing, etc. Other initiatives are geographically limited in scope, such as California’s SAFER database and New Mexico’s Water Data Initiative, mentioned at the beginning of this essay. The population that is at risk or already lacks access to WaSH in the U.S. goes beyond a handful of states and therefore a more comprehensive data system is needed, but for activists it should be a dashboard that is easy to interpret and one that allows local people to tell their own stories.

We developed a dashboard called (Dis)closing the Water Gap, released in December 2025 [106]. Our dashboard links basic demographic and access to plumbing data from ACS to ECHO data on drinking water and clean water violations at the national, state, and county level (the most localized unit of analysis where these data can be spatially linked). We link to other datasets like existing state datasets. Tools like AI (Artificial Intelligence) could help do some of the cleaning that would be necessary to make regularly updated data to fit into a dashboard format. We are also using it to identify local media that may highlight local access issues, and include community narratives where we have them. This is a beginning, not the solution, as we have good reason to believe that these data sources undercount the communities grappling with chronic water insecurity. We believe that this will complement the growing effort by groups like the Vessel Collective in the U.S. WaSH sector to identify and direct resources toward those communities lacking access [107].

A comprehensive dashboard could indicate on a map places where there are increases in households saying that they lack complete plumbing facilities or have problems with unsafe or inaccessible water. Seeing this on the dashboard could trigger WaSH activists to contact people in the community, who could then be empowered to bring in technicians to address issues. Allowing community members to tell their own stories through narratives can help technical experts understand the problems and think about ways of solving them with the communities in question [108].

Better data collection is needed to really monitor access to WaSH in the U.S. This will also require better engagement from U.S. and State governments. The Trump administration and a conservative legislature poses a challenge. Even if bureaucrats at agencies such as the U.S. EPA and the U.S. Department of Agriculture were constrained by legislative requirements before, they were sympathetic to documenting WaSH access. But the number of Federal employees and the money they have for monitoring WaSH access have been curtailed severely. Congressional efforts to create an inter-agency collaboration to better monitor WaSH [109] stalled in the last congress and show no signs of re-emerging at least until we have a new administration. This is why the robust data efforts at the state level, mentioned at the beginning of this essay, and initiatives by academia and non-governmental organizations are so important.

7. Conclusion

After decades of presuming that WaSH issues were, at worst, a minor issue in the U.S., there is growing recognition that too many in the nation and its territories lack access to potable water and functional wastewater treatment. A first step toward seriously addressing the issue will be better tracking and therefore better understanding the problem. Advocates for WaSH access need to be able to answer the question “where are these communities with people who lack access,” so that we can get to the next step of addressing the myriad reasons that put communities in this condition. Above, we have described some existing efforts, all of which address one part of the problem of access to WaSH. Momentum is building towards a more systematic effort to collect the data on WaSH in the U.S. context. These efforts are important steps to moving beyond intense focus on the recognized and emerging “hotspots” outlined in part two of this essay. The dashboards in the making, described in the later sections of this article, could play an important role in identifying communities where access to WaSH is an ongoing challenge. But these are the beginning of the initiative, not the solution to the problem of access to WaSH. New policy initiatives are needed, though the current climate in U.S. government does not seem amenable to developing more rigorous data collection instruments. In that context, University-NGO collaboration may be an important stopgap. We know 2 million people, and possibly many more, live in conditions that we should see as completely intolerable in one of the world’s wealthiest societies. We must act systematically, rather than addressing each new emerging crisis of access to WaSH.