Spatio-temporal trends and patterns of unmet basic sanitation service needs in Ethiopia from 2011 to 2019 Open Access

EDHS

Ethiopian Demographic and Health Survey

EPHC

Ethiopian Population and Housing Census

CLTS

Community-Led Total Sanitation

CSA

Central Statistics Agency

HH

household

LLR

likelihood ratio

RR

relative risk

SDG

sustainable development goals

SNNPR

Southern Nations, Nationalities, and Peoples' Region

WHO

World Health Organization

Access to basic sanitation service is needed for the improvement of the health of the population as well as the attainment of the sustainable development goals (SDGs) with focus on SDG 6 which targets to ensure adequate and sustainable management of water and sanitation for all by 2030. Despite the global improvement, Sub-Saharan Africa including Ethiopia still has one of the lowest accesses to sanitation services, where a large part of the population has no access to basic sanitation services (Ohwo & Agusomu 2018; Bishoge 2021; Zerbo et al. 2021; Okesanya et al. 2024). This has a number of negative impacts on public health including a high incidence of sanitation-related diseases and under-five mortality (Prüss et al. 2002; Fewtrell et al. 2005; Prüss-Ustün et al. 2019; WHO 2020; UNICEF WHO 2021).

Lack of access to basic sanitation services is still a major worldwide concern particularly in the developing nations (Moe & Rheingans 2006). As of 2020, 3.6 billion people around the world did not have access to safely managed sanitation and the problem is most acute in Sub-Saharan Africa including Ethiopia (UNICEF, WHO 2021). The previous findings of the studies indicated that access to basic sanitation services is not homogeneous within and between countries as well as over different periods (Heijnen et al. 2014; Prüss-Ustün et al. 2014; UNICEF, WHO 2021). The studies conducted on geospatial variations and inequalities in Sub-Saharan Africa revealed that there were significant differences in the geography of access to sanitation services and needs for specific strategies (Azage et al. 2020; Pullan et al. 2014; Yu et al. 2014).

Evidence from the 2016 Ethiopian Demographic and Health Survey (EDHS) and the Multiple Indicator Cluster Surveys in Vietnam (2000–2011) showed that the lack of improved sanitation facilities tends to be spatially clustered and was closely linked to various socio-economic and environmental factors (Tuyet-Hanh et al. 2016; Azage et al. 2020). In Ethiopia, research using spatial modeling revealed that regions with lower access to sanitation services were also hotspots for waterborne diseases such as diarrhea (Belay & Andualem 2022; Demsash et al. 2023).

Research conducted in different regions of Ethiopia indicates that the lack of basic sanitation services exhibits substantial variability across study settings and over time. Socio-economic disparities, urban-rural differences, and environmental conditions are key factors driving these patterns (Alemu et al. 2023a; Demsash et al. 2023). A study in Ethiopia revealed that regions with higher poverty rates and limited access to water supply infrastructure were more likely to experience a lack of sanitation services (Alemu et al. 2024; Keleb et al. 2024; Mekonnen et al. 2024). Similarly, environmental and climatic factors also play a role in significant role in access to basic sanitation across the country (Abrams et al. 2021).

In Ethiopia, several initiatives have been implemented to improve access to basic sanitation services and the health consequences of sanitation deficiencies. For example, one of the major initiatives is the Health Extension Program, which began in 2004. This program aims to improve the sanitary condition of households by providing health extension services to reducing sanitation-associated diseases such as diarrhea (Workie & Ramana 2013; Alemu et al. 2023b; Girma et al. 2024). Despite these efforts, lack of access to basic sanitation services remains a significant public health challenge, contributing to preventable diseases and mortality, especially among vulnerable populations (Mills & Cumming 2016; Gessese et al. 2023; Girma et al. 2024; Sahiledengle et al. 2024).

As a result, this study aims to answer the following research questions: (1) What are the spatiotemporal trends in unmet sanitation services needs in Ethiopia from 2011 to 2019? (2) What regional disparities exist, and how have they evolved over time? The study's findings are significant because they can help inform targeted interventions and design evidence-based strategies to improve public and environmental health outcomes. Furthermore, these findings can inform policy decisions aimed at promoting healthier communities, achieving the SDGs, and closing gaps in access to basic sanitation services.

A population-based cross-sectional study design was used to investigate and identify spatial trends and patterns of unmet basic sanitation services in Ethiopia. This study used data from 16,702 households in the 2011 EDHS, 16,650 households in the 2016 EDHS, and 8,663 households in the 2019 EDHS, all obtained from the https://www.dhsprogram.com/data/dataset_admin/login_main.cfm website. These surveys are population-based and nationally representative, with large sample sizes collected at different points in time.

The study is conducted in Ethiopia (3°–14°N and 33°–48°E), located at the eastern tip of Africa (Dwivedi et al. 2005). The country covers an area of 1.1 million square kilometers and has remarkable geographical diversity, with elevations ranging from 4,550 m above sea level in the Ethiopian Highlands to 110 m below sea level in the Afar Depression. As of 2021 Ethiopia is administratively divided into two administrative cities (Addis Ababa and Dire Dawa) and eleven regional states: Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Sidama, South West Ethiopia Southern Nations, Nationalities, and Peoples' Region (SNNPR), Gambella, and Harari, which are further subdivided into 68 zones, 817 districts, and 16,253 kebeles (the smallest local administrative units). Ethiopia's population has grown significantly over time, from 53.5 million in the 1994 census to 114,968,588 in 2020, with a fertility rate of 4.3 (Admassu et al. 2013; Genet 2020).

The source population for this study was all households in Ethiopia, while households in the selected enumeration areas (EAs) were the study population.

All EDHS samples were selected using a two-stage stratified cluster sampling procedure. Sampling weights were calculated to adjust survey data to make it representative of the target population. In 2011 EDHS, 624 EAs (Dearden et al. 2017) were selected comprising 187 urban and 437 rural areas (Central Statistics Agency, ICF International Calverton 2012), the 2016 EDHS covered 645 EAs (202 urban and 443 rural) (Central Statistics Agency, ICF International Calverton 2017), and the 2019 EDHS included 305 EAs (93 urban and 212 rural) (Ethiopian Public Health Institute and Federal Ministry of Health 2020). These EAs were chosen using systematic sampling with probability proportional to size.

In the second stage of selection, a fixed number of 30 households per cluster were randomly chosen from a newly created household list.

To measure basic sanitation services, we aligned our indicators/variables collected during EDHS surveys with the WHO/UNICEF Joint Monitoring Program (JMP) definitions which enhances comparability across time and geography (UNICEF, WHO 2021). Specifically, a household was considered to have unmet or lack of access to basic sanitation services, if it did not use unshared flush or pour flush systems, septic tanks, pit latrines, or composting toilets and did not know where excreta is disposed or if the household used any of the following unimproved sanitation facility types including flush somewhere else; pit latrines without slabs; open pits and buckets; hanging toilets; or open field defecation, including no facility, bush, or field, and shared improved sanitation facilities (UNICEF, WHO 2018, 2021).

The data collection for the EDHS was made possible by a collaborative effort involving Ethiopian Public Health Institute investigators, a technical specialist from an Information Consulting Firm, an advisor, and representatives from organizations such as the Central Statistics Agency, the Federal Ministry of Health, the World Bank, and USAID (Dearden et al. 2017). Data on sanitation access was collected at the household level, with respondents (typically heads of households or knowledgeable household members) reporting on the type of sanitation facilities used by household members. The data were self-reported and permission-based observation through trained data collectors and supervisors. This may introduce potential biases such as recall error and social desirability bias especially in cases where respondents may overstate facility use or underreport sharing with other households. Location data, including latitude and longitude coordinates, were also collected from the selected EAs (Central Statistics Agency ICF International Calverton 2012, 2017; Ethiopian Public Health Institute and Federal Ministry of Health 2020).

Data cleaning, variable recoding and labeling, weighting, processing and data summary for non-spatial analysis were conducted using STATA version 17 and R version 4.4.2 software. Spatial statistics were analyzed using Geographical Information System (ArcGIS Pro version 2.8) software, while Sat Scan version 10.2.5 was used for spatial scanning and identifying clusters. Descriptive statistics, encompassing frequencies with percentages were reported, and the results were presented with tables and graphs.

Global Moran's I statistic was applied to assess whether unmet basic sanitation service patterns in the study area were dispersed, clustered, or randomly distributed (Cortés et al. 2020; García-Pérez 2022). Moran's I values close to −1 indicate lack of access to basic sanitation services dispersion, while values close to +1 suggest basic sanitation clustering, and values around 0 imply random distribution. A statistically significant Moran's I (p < 0.05) leads to the rejection of the null hypothesis, indicating the presence of spatial autocorrelation (Demsash et al. 2023; Roy 2023; Biswas et al. 2024).

To investigate local-level clustering of unmet basic sanitation services, Anselin Local Moran's I was employed (Song & Kulldorff 2003; Isazade et al. 2023; Gedamu et al. 2024). This measure determines whether clusters of high values (high–high) or low values (low–low) exist, or if there are negatively correlated clusters (high–low or low–high). It also identifies outliers, where a high value is surrounded by predominantly low values, or a low value is surrounded by high values (Zhang et al. 2008; Sánchez-Martín et al. 2019; Wong 2021). A positive value for Moran's I indicates that a case is surrounded by similar values, forming part of a cluster, while a negative value suggests that a case is surrounded by dissimilar values, making it an outlier (Negreiros et al. 2010; Tsui et al. 2022).

Hotspot analysis was carried out to determine how spatial autocorrelation varies across the study area by computing the Gi* statistic at each location (Abdulhafedh 2017). The presence of a statistically significant spatial pattern, warranting further exploration of the underlying causes. Statistical output with a high Gi* indicates a ‘hotspot,’ whereas a low Gi* value signifies a ‘cold spot’ (Anselin et al. 2010; Naish & Tong 2014).

The Spatial Scan statistical method is widely recommended for its effectiveness in detecting local clusters, offering higher power compared to other spatial statistical methods (Li et al. 2011; French et al. 2022). This technique was used to test for the presence of statistically significant spatial hotspots or clusters of unmet basic sanitation services using Kuldorff's SatScan version 10.2.5 software The method utilizes a scanning window that moves across the study area (Block 2007; Coleman et al. 2009). Household with lack of access to basic sanitation services were classified as cases, while those with access to basic sanitation services were considered controls, fitting a Bernoulli model. The number of cases in each location followed a Bernoulli distribution.

The default maximum spatial cluster size of <50% of the population was applied, which allowed for the detection of both small and large clusters while excluding those that exceeded the maximum size. For each potential cluster, a likelihood ratio test statistic was used to assess whether the observed number of cases within the cluster was significantly higher than expected. Primary and secondary clusters were identified, assigned p-values, and ranked based on their likelihood ratio tests, using 999 Monte Carlo replications (Alemu et al. 2014).

The hotspot graphs illustrate the spatial analysis of geographical variations in lack of access to basic sanitation services in Ethiopia for the years 2011, 2016, and 2019. These maps highlight areas where the lack of sanitation access is significantly higher (hotspots) or lower (cold spots) providing critical insights into regional inequalities. In 2011, the hotspots (likely marked in red) reveal regions with severe basic sanitation inaccessibility.

This study finding revealed more widespread and overlapping clusters in 2016, indicating a potential interaction of different risk factors. The primary cluster covered 109 EAs and had a radius of 247.73 km, centered at (11.00 N, 37.00 E), with 4,591 households and RR of 1.08. Secondary clusters within the primary cluster also showed statistically significant risk with RRs of 1.07 and LLR values up to 48.33 (p < 0.001). Another distinct secondary cluster in 2016 covered 13 EAs over a radius of 222.25 km, centered at (5.00 N, 40.00 E), with an RR of 1.07.

The 2019 clusters showed similar patterns, but with higher relative risks, indicating that situations in certain places were worsened. The primary cluster encompassed 121 EAs with a radius of 468.85 km, centered at (7.00 N, 35.00 E). This cluster includes 4,004 households, with 3,766 lacking basic sanitation access and RR of 1.09, indicating a 9% greater risk. In 2019, secondary clusters varied from 9 to 53 EAs, with radii of 108.70–398.59 km and RRs of 1.07–1.09 (Table 1).

Each interpolated map depicts areas with varied level of predicted risk, with green representing low-risk regions and red representing high-risk zones. In 2011(left map), the spatial interpolation demonstrated Gambella and SNNP regions as major high-risk areas with concentrated red zones indicating serious concerns with basic sanitation access.

The Somali region showed notable fluctuations in basic sanitation needs over time. This might be due to migration, drought effects, or data irregularities, and note the limitations in interpolation accuracy from sparse data points in some areas.

This study investigated the spatiotemporal variations in unmet basic sanitation services in Ethiopia from 2011 to 2019, focusing on urban-rural disparities, regional inequalities, and temporal trends.

Rural regions in Ethiopia indicated stagnation, with a significant level of lack of access to basic sanitation services (93.98% in 2019). Rural sanitation improvements are hampered by persistent systemic barriers such as a lack of financing, weak institutional competence, and socio-cultural factors (Akoteyon 2019; Sinharoy et al. 2019; Hlongwa et al. 2024). Community-led total sanitation (CLTS) and other water sanitation and hygiene initiatives frequently achieve short-term success but fail to have a long-term impact (Harter et al. 2018; Brown et al. 2019). Integrating sanitation programs into larger rural development projects, such as agriculture or education, may increase basic sanitation services in rural areas (Ejigu & Yeshitela 2023; Li et al. 2024). Ethiopia's experience is similar to those of other low-income nations, emphasizing the importance of innovative and context-specific solutions for addressing rural sanitation difficulties (Ohwo & Agusomu 2018; Brown et al. 2019; Zerfu et al. 2023; Mamo & Novotný 2024).

Significant regional variations in basic sanitation access were evident that urban regions exhibited consistent progress between 2011 and 2019 in Ethiopia. However, less-developed regions such as Gambella, Somali, and Benishangul-Gumuz experienced worsening conditions or stagnation. Unmet basic sanitation services in Gambella increased from 89.79% in 2011 to 97.11% in 2019, might be due to geographic isolation, socio-political dynamics, and chronic underfunding (Akoteyon 2019; Admassie & Abebaw 2014; Yenesew et al. 2020). Similarly, regions such as Afar and Somali, characterized by nomadic lifestyles and harsh climates, require innovative and adaptive sanitation solutions (Lumborg et al. 2021). The limited progress in Tigray and SNNPR can be attributed to persistent structural challenges such as lower investment in sanitation infrastructure, higher population densities that strain existing services, and diverse socio-cultural practices.

Based on the three EDHS dataset, Global Moran's I, Getis-Ord Gi* statistic, SatScan analysis and Kriging interpolation significant variations on unmet basic sanitation services among regions in Ethiopia were identified. In the 2011 SatScan map, high-risk primary cluster was identified in regions of SNNPs, South West Ethiopia, Sidama, Gambella, West and South Oromia, and Western Somali (RR = 1.06, LLR = 91.77, P < 0.001) where mostly rural or underserved areas. The clustering patterns appear more localized compared to later years, and the difference might be due to systemic barriers such as infrastructure deficiencies and socio-economic disparities. Cold spots (marked in blue), representing areas with relatively better access, are also indicating regions that may have benefited from better investments or policies (Yenesew et al. 2020; Demsash et al. 2023; Hlongwa et al. 2024; Mekonnen et al. 2024).

The 2016 SatScan map showed a noticeable increase in the extent and intensity of clustering patterns. Multiple clusters were identified, with varying sizes and p-values. Larger circles represent primary clusters including major parts of Amhara and South Oromia and Western Somali region with more severe basic sanitation challenges (RR = 1.08, LLR = 192.23, P < 0.001), while smaller circles point to localized problems. This spread of clusters suggested that disparities in basic sanitation access may worsened or persisted over time. This intensification is likely driven by factors such as population growth, rapid urbanization without proportional improvements in infrastructure, stagnation in sanitation programs or other socio-economic factors. While cold spots remain, their extent appears reduced, suggesting that progress in improving basic sanitation access may not have been uniform across the country (Adugna 2023; Alemu et al. 2023a, 2024; Keleb et al. 2024).

By 2019, the map showed some improvement in the intensity and spread of clusters compared to 2016, although significant primary clusters still remain (RR = 1.09, LLR = 74.39, P < 0.001). The clusters are more localized, suggesting that efforts to improve sanitation access may have had some positive impacts in certain areas. However, the persistence of significant primary cluster was found at SNNPs, South West Ethiopia, Sidama, West Oromia, Gambella, and Benishangul-Gumuz regions (RR = 1.09, LLR = 74.39, P < 0.001) and the secondary cluster with 53 EAs was at major parts of Somali and Southwest Oromia (RR = 1.09, LLR = 74.39, P < 0.001) indicated that challenges remain, particularly in rural or pastoralist communities where systemic inequalities are harder to overcome.

The findings align with broader patterns observed in several Sub-Saharan African countries, revealing both shared challenges and divergent trajectories where urban areas benefit from concentrated resources, focused programs, and infrastructure investments (Armah et al. 2018; Okesanya et al. 2024).

Consistent improvement in urban basic sanitation access was observed in Ethiopia, where unmet needs declined from 81.3% in 2011 to 58.69% in 2019, particularly in cities such as Addis Ababa, Dire Dawa, and Harari. These improvements are attributed to targeted investments, higher institutional capacity, increased public awareness, and more effective governance structures.

Comparable urban improvements have been reported in countries such as Kenya particularly Nairobi and Mombasa, benefited from pro-poor sanitation programs and public–private partnerships, contributing to a steady decline in unmet needs (Munguti & McGranahan 2001; Mugo 2006; Mwango 2013; Auerbach 2016; Muchangi et al. 2018). Urban sanitation access improved through multi-sectoral initiatives such as the Greater Accra Metropolitan Area (GAMA) Sanitation and Water Project in Ghana, emphasizing decentralized solutions and behavior change (Salifu & Darko-Mensah 2008; Knutson 2014; Hueso 2016). These similarities suggest that focused urban programming and investment in governance and infrastructure are key drivers of sanitation improvements across urban Sub-Saharan Africa.

Despite progress in central urban zones, both Ethiopia and its regional peers face significant challenges access to basic sanitation services in peri-urban and informal settlements (Bishoge 2021; Mezgebo 2021; Zerbo et al. 2021; Hlongwa et al. 2024; Maket et al. 2024). In Ethiopia, the pace of urbanization has often exceeded the capacity of local infrastructure, leading to service backlogs in rapidly expanding areas surrounding major cities.

Likewise, in Uganda, studies have shown that informal settlements in Kampala remain underserved in access to basic sanitation services despite overall urban improvements, due to land tenure issues and limited planning (O'Keefe et al. 2015; Dickson-Gomez et al. 2023). In Tanzania, Dar es Salaam's peri-urban zones face similar constraints, with infrastructure lagging behind population growth (Yap et al. 2023). Ethiopia's experience reflects this broader pattern, where unregulated expansion and informal housing undermine progress, indicating a regional need for inclusive urban sanitation strategies.

Rural areas in Ethiopia showed minimal change over the study period, with unmet basic sanitation service needs remaining high (94.03% in 2011 to 93.98% in 2019). This stagnation mirrors rural sanitation trends in Niger and Chad, where access has remained critically low due to limited funding, inadequate infrastructure, and weaker institutional support (Alagidede & Alagidede 2016; Roche et al. 2017; Borja-Vega et al. 2022; Atangana & Oberholster 2023). In Malawi, where rural sanitation has progressed only modestly, relying heavily on CLTS approaches with mixed outcomes (Cole 2015; Panulo et al. 2024). These comparisons highlight a persistent rural–urban divide across the region and underscore the necessity of tailored, culturally sensitive rural sanitation policies.

The gradual improvements in Ethiopia's urban sanitation reflect the cumulative effects of national policies, urban health extension programs, and donor-supported projects. Similar policy-driven progress has been documented in Rwanda (Brinkerhoff et al. 2009; Ekane et al. 2019), where integration of sanitation into national health and development plans helped achieve notable improvements in Senegal, which leveraged performance-based financing and decentralized sanitation planning for more equitable sanitation service delivery (Trémolet et al. 2007; Scott et al. 2019). In Ethiopia, while urban policies have yielded measurable results, the limited progress in rural areas suggests a need for recalibrated strategies that address long-standing equity and infrastructure gaps.

The current study using spatiotemporal trend and pattern analysis provides valuable insights into the geographical and time variations contributing to disparities in access to basic sanitation service. The finding of the study can inform environmental and public health practitioners to design targeted interventions to reduce the gap and improve overall health outcomes. Besides, the results are representative to the source population, since the data is nationwide. Furthermore, since the data is collected across the country, the findings are representative of the source population.

This study has certain limitations, including the fact that it relied on self-reported data, which may be prone to recall bias or social desirability bias. However, efforts were made to reduce these biases via rigorous training of data collectors, pre-testing, thorough data collection processes and regular field supervision. Finally, it is important to note that the study did not explore factors influencing access to basic sanitation services. Future research could consider a more comprehensive approach to examine factors contributing for spatiotemporal variations in access to basic sanitation services.

The study revealed that, despite localized improvements in basic sanitation access in Ethiopia from 2011 to 2019, significant spatiotemporal variation persist, particularly in rural and underserved area. The hotspot analysis revealed persistent yet dynamic patterns of sanitation inequality over time whereas Sat Scan analysis showed shifting significant hotspots of unmet basic sanitation services.

While some regions showed improvement, others remain highly vulnerable in which systemic barriers continue to drive these variations emphasizing the need for targeted, context-specific interventions with continuous monitoring and evaluation. Prioritizing high-risk regions with critically low basic sanitation access is crucial for achieving sustainable and equitable solutions.

Based on the spatiotemporal analysis findings, this study recommends targeted interventions to address regional disparities in basic sanitation access across Ethiopia. Gambella, with worsening trends needs urgent and focused sanitation programs including mobile sanitation services, strengthened institutional WASH capacity, and community-led interventions. Persistent clusters in regions such as SNNPR, Sidama, South West Ethiopia, and West Oromia should be prioritized in the national sanitation agenda, with resource allocation guided by spatial analysis to ensure equitable funding. Newly affected regions such as Amhara and Benishangul-Gumuz need continued support to sustain improvements. Integrated WASH strategies across neighboring regions are essential, given the spatial interconnectedness of sanitation challenges. In rural areas where access remains lowest, scalable low-cost infrastructure and CLTS approaches are recommended. Finally, region-specific monitoring systems should be adopted to track progress and inform responsive actions.

We would like to extend our deepest gratitude to the DHS program for granting us permission to use the data for this study.

There is no specific fund received for this research.

A.K. conceptualized, designed, did software analysis, analyzed, interpreted the data, and drafted, wrote and edited the manuscript. A.E., Y.T., E.T.A., and E.M.G. conceptualized, did software analysis, wrote and edited the manuscript. All authors read and approved the final manuscript. A.E.B. conceptualized, designed, did software analysis, interpreted the data, and edited the manuscript.

The ethical procedures were conducted by the institution conducting the survey. However, we have acquired written permission from the DHS program, which granted authorization for the use of this data set. Before the data collection technique, the materials were reviewed and approved for compliance by the National Research Ethics Review Committee in Ethiopia. Strict confidentiality measures were adhered to ensuring anonymity, and the data were exclusively utilized for the specific purposes outlined in the current study.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.