Accessibility to WASH and waste management services in African urban informal settlements: A comparative analysis

Access to adequate water, sanitation, and hygiene (WASH) facilities and services is crucial for promoting public health and overall well-being. However, urban informal settlements face significant challenges in providing these essential resources. Urban informal settlements, often referred to as slums or shantytowns, are characterized by unplanned and densely populated areas that lack formal infrastructure and basic services (Kohli et al. 2019; Agarwal et al. 2020). These settlements are prevalent in urban areas of low- and middle-income countries, accommodating a significant proportion of the urban population (Dodman et al. 2019; Jenkins et al. 2021). The inadequate provision of WASH facilities in these settlements exacerbates health risks, leading to the spread of waterborne diseases, such as diarrhea and cholera, and contributing to a cycle of poverty and deprivation (Satterthwaite et al. 2018; Biran et al. 2021).

The comparative analysis involves selecting multiple territories from diverse geographical locations, considering regional diversity, population size, and socioeconomic characteristics. By comparing these settlements, common challenges and unique contextual factors influencing the availability and accessibility of WASH facilities can be identified (Fisher et al. 2017; Raj et al. 2020). Access to WASH facilities and services in urban informal settlements is a pressing issue in numerous African countries. Moreover, the literature carried out the challenges and opportunities surrounding WASH in African urban informal settlements, drawing on relevant journal papers and studies. In many African countries, urban informal settlements, commonly known as slums, are characterized by overcrowding, inadequate infrastructure, and limited access to essential services (Amegah et al. 2017; Ezeh et al. 2020a, 2020b). These settlements often lack proper WASH facilities, leading to numerous health and environmental risks. Limited access to clean water sources is a crucial challenge, as many residents rely on contaminated or untreated water (Ahmed et al. 2020a, 2020b). This poses significant health risks, as waterborne diseases such as diarrhea and cholera are prevalent (Rheingans et al. 2019a, 2019b).

Sanitation is another critical aspect of WASH in African urban informal settlements. Inadequate sanitation facilities, such as a lack of toilets or latrines, result in open defecation and poor waste management practices (Yegbemey et al. 2017a, 2017b). This contributes to the contamination of water sources and the spread of diseases (Ansa-Asare et al. 2020a, 2020b). Access to functional and hygienic sanitation facilities is essential to mitigate health risks and promote safe sanitation practices (Orebiyi et al. 2018). Proper hygiene practices are crucial for improving WASH outcomes in African urban informal settlements. Effective hygiene interventions should target behavior change and emphasize the importance of handwashing, particularly before meals and after using sanitation facilities (Bisung et al. 2018). Access to handwashing facilities, such as clean water and soap, is essential for good hygiene (Mara 2017). Hygiene education programs that engage communities and address cultural practices and beliefs have shown promising results in improving hygiene behaviors (Amegah et al. 2017; Clasen et al. 2019). Addressing the challenges of WASH in African urban informal settlements requires a multifaceted approach. Effective governance and policy frameworks are crucial in ensuring sustainable WASH services (Foster et al. 2019). Government commitment and investment are vital to improving infrastructure and service delivery (Bisung et al. 2018). Collaborations between governments, non-governmental organizations, and community-based organizations are essential for implementing WASH initiatives and promoting community ownership (Bisung et al. 2018; Asamane et al. 2020). Furthermore, innovative approaches can help overcome the unique challenges of WASH in African urban informal settlements. For example, community-led total sanitation (CLTS) techniques have shown promise in promoting sustainable sanitation practices and reducing open defecation (Ansa-Asare et al. 2020a, 2020b). In addition, mobile technologies and geographic information systems (GIS) can aid in mapping WASH infrastructure, identifying service gaps, and monitoring progress (Kedir et al. 2020).

Effectively managing waste in urban areas presents a significant challenge, particularly in informal settlements with a substantial population (Wilson et al. 2012a, 2012b). This literature review aims to investigate the accessibility of waste management services (WMS) in such territories and provides a comparative analysis of existing studies and approaches. The lack of adequate waste management facilities in these areas leads to environmental pollution and severe health hazards for residents (Sengupta & Chakraborty 2019). Studies have highlighted vital factors that impact waste management accessibility in informal settlements, including insufficient infrastructure, funding limitations, and lack of governmental support (Ramaswami et al. 2016a, 2016b; Parvez 2020). Moreover, socioeconomic disparities further hinder the implementation of sustainable waste management practices (Gutberlet 2018a, 2018b). Despite these challenges, specific innovative solutions, such as community-based waste collection initiatives and public–private partnerships, have shown promise in enhancing waste management accessibility (Kamunge & Mathuthu 2017). The evaluation is supported by a rigorous review of existing journal papers, encompassing primary and secondary data sources, including surveys, interviews, and reports from governmental and non-governmental organizations. Data collection methods utilize standardized approaches and questionnaires to ensure consistency and reliability across different settlements. Additionally, spatial mapping and GIS techniques are employed to visualize the distribution of WASH facilities and identify areas with the greatest need for improvement (Rufener et al. 2019; Parvez & Islam 2020; Osumanu et al. 2022).

Sanitation facilities, including toilets or latrines, are evaluated in terms of functionality, cleanliness, and suitability for different population groups (Sultana et al. 2020a, 2020b; Gumbo et al. 2021a, 2021b). Moreover, hygiene practices, such as handwashing facilities and educational programs, are examined to understand their effectiveness in promoting hygienic behaviors and reducing disease transmission (Pickering et al. 2019; Biran et al. 2020; Parvez & Rana 2021). By leveraging the findings from a broad range of journal papers, the study aims to identify the underlying factors contributing to these disparities, including governance structures, policy frameworks, and resource allocation mechanisms (Wilbers et al. 2018; Parvez 2020; Wutich et al. 2021). Extensive literature underscores the importance of reliable and clean water sources for fostering public health and well-being within urban informal settlements. Access to potable water results in waterborne diseases and health hazards (Mosler et al. 2021a, 2021b; Cronk et al. 2022a, 2022b). Toilet facilities (sanitation): the literature corroborates the formidable challenges associated with inadequate sanitation facilities, typified by the absence of proper toilets or latrines in urban informal settlements (Yegbemey et al. 2017a, 2017b; Ansa-Asare et al. 2020a, 2020b). This study's attention to pit toilets in communal spaces underscores the urgency of bolstering sanitation alternatives. The pivotal enhancement of access to appropriate sanitation amenities is indispensable for curtailing disease transmission and cultivating a healthier living environment (Sultana et al. 2020a, 2020b; Gumbo et al. 2021a, 2021b). By the literature, this study acknowledges the multifaceted waste management challenges endemic to informal settlements. These areas grapple with insufficient infrastructure and meager governmental support, engendering environmental pollution and jeopardizing public health (Ramaswami et al. 2016a, 2016b; Parvez 2020). The study's observation of disorganized waste dumping site distribution resonates with analogous findings in the previous research. Competent waste management is indispensable for averting contamination and nurturing a hygienic living environment, an urgency that gains further momentum in densely populated urban zones (Wilson et al. 2012a, 2012b; Gutberlet 2018a, 2018b). The literature extols the pivotal role of treated water in forestalling waterborne ailments and augmenting public health. The prevalent dearth of access to treated water sources constitutes a recurring challenge in informal settlements, accentuating the perils associated with ingesting contaminated or untreated water (Rheingans et al. 2019a, 2019b; Ahmed et al. 2020a, 2020b). The scrutiny of water treatment facilities undertaken by this study aligns with the requisite to mitigate disparities in water quality and guarantee equitable access to safe potable water (Wilbers et al. 2018; Wutich et al. 2021).

The study investigates the existing scenario and spatial distribution pattern disparity of service distribution of WASH and WMS in urban informal settlements within the Zaria metropolis. Moreover, from the findings, this study will generate recommendations for the policymakers to improve the existing scenario and spatial distribution pattern disparity of service distribution of WASH and WMS. The study also aims to determine access to the existing scenario of WASH facilities and WMS in African urban informal settlements. Limited access to clean water sources, inadequate sanitation infrastructure, inadequate WMS, and poor hygiene practices contribute to health risks and environmental degradation. Addressing these challenges requires a holistic approach that includes improved governance, targeted interventions, community engagement, and innovative solutions. By addressing the specific contextual factors and leveraging local knowledge, African countries can work toward achieving sustainable and equitable WASH and WMS in urban informal settlements. Ultimately, the manuscript provides evidence-based recommendations for targeted interventions, advocacy, and investment in improving WASH and WMS infrastructure and services in urban informal settlements to enhance their residents' well-being and quality of life. The study will pinpoint the locations currently serviced, those overserved and underserved in terms of service provision, the distribution of public health facilities, and their spatial accessibility. This manuscript aims to comprehensively evaluate WASH facilities and services in urban informal settlements through a comparative analysis, drawing on a diverse range of journal papers as references. This study emphasizes the importance of adopting a comprehensive approach involving stakeholders at various levels to create sustainable and inclusive waste management systems in urban informal settlements. By examining the existing conditions and identifying key factors influencing WASH accessibility, this study seeks to contribute valuable insights for interventions and policy recommendations to improve residents' living conditions and health outcomes in these marginalized communities. This will help policymakers identify the existing gap in the distribution of WASH and WMS and help them plan appropriately for the future development of these services.

As of 2021, Nigeria's population was estimated to be around 206 million. The annual growth rate of the population was approximately 2.6%. This substantial growth was reflected in the population density, about 226.6 people per square kilometer (UN 2021).

Sabon Gari Local Government Area comprises six districts and 11 wards. The area has a more diversified population since it is made up mostly of settlers and non-indigenous people who moved to Zaria for various reasons, as well as because the city has many government facilities and services. The local government has several post-secondary institutions and research institutes, including the military college, barracks, Ahmadu Bello University, Zaria, School of Aviation, and Leather Research Institute (Akinola et al. 2013). Sabon Gari is located near the border of Kaduna State, with a total area of 273,779 km² (NPC 2020). Zaria is a bustling city in Kaduna State, Nigeria, and is a significant economic and cultural center in the region. Positioned at approximately 11.1°N latitude and 7.7°E longitude, Zaria spans an area of roughly 259 km² and falls within the ecological zone of Guinea Savanna (Salami 2016). The city experiences a tropical climate characterized by distinct wet and dry seasons; the rainy season typically extends from May to October, while the dry season lasts from November to April (Iliya et al. 2018). As of the latest population estimate conducted in 2021, Zaria's population is around 1.5 million, making it one of Nigeria's most densely populated cities (National Population Commission 2021).

To identify the service facility and the areas served, the authors conducted three key informant interviews (KII) with the WASH experts of the local area. Moreover, three KII were done with the city authorities and waste management experts, giving us valuable information on the facilities and the communities. From the KII and FGD sections at the field level, these four facilities (WASH and WMS) are identified to be more vulnerable in that study area. In addition, some literature is given to justify using these four facilities.

To identify the nearest walking distance as well as the service facility accessibility, the authors conducted three focus group discussions (FGD) with the local community people. This KII and FGD help to delineate the served, underserved, and overserved areas of the service facilities for water supply source points, public toilet points, waste dumping points, and water treatment plant points. Population data were collected from secondary sources (NPC 2020), and disease data were collected from the National Primary Health Care Development Agency (NPHCDA). After collecting the GPS points, data were cleaned and then analyzed through the ArcGIS software. The FGD and KII findings were incorporated into the GIS data, and finally, the accessibility of WASH and WMS in urban informal settlements was carried out.

The average nearest neighbor (ANN) measures the separation between the centroids of each spatial feature and those of its closest neighbors. Then, an average of all these distances is calculated and contrasted with an imagined random distribution. The spatial arrangement of the features under analysis (the observed) is said to be clustered if the mean distances of an observed distribution are lower than the average of a fictitious random (expected distribution). In this situation, the ANN ratio is below 1. On the other hand, the spatial pattern is regarded as scattered if the middle distance is higher than the predicted distribution.

In this instance, the ANN ratio is more than one (ESRI 2015). The ANN analysis is a widely used spatial statistic in GIS to assess spatial clustering or dispersion of point features. This analytical method calculates the average distance between each point and its nearest neighbor, comparing it with the expected average distance under complete spatial randomness (CSR) (Getis & Ord 2010). The ANN index offers valuable insights into spatial patterns, helping to determine whether point features exhibit clustering or random distribution across the study area. A value less than one indicates clustering, while a greater than one suggests dispersion. Researchers in various fields, including ecology, urban planning, and epidemiology, have applied this analysis to identify spatial trends and inform decision-making processes (Wang et al. 2017). By utilizing the ANN analysis in GIS, professionals can better understand the spatial arrangement of point features, enabling informed decisions to address spatial patterns and optimize resource allocation.

• (a)
  The average distance between two neighbors (MANSOUR 2016):

  

  (1)

Here, N is the number of opinions while d_i is the adjacent neighbor remoteness for point i.

• (b)
  The predicted value of the distance between the closest neighbors in a random pattern (MANSOUR 2016):

  

  (2)

A is the study area's size, and B is the study area's perimeter length.

• (c)
  The variance (MANSOUR 2016):

  

  (3)

The square root of the sum of the squares of the differences between the corresponding values must be calculated to use this method to get the distance between two places. In a GIS context, the Euclidean distance is computed from the source cell's center to the centers of each cell around it. The result is a raster layer that includes the measured distances in projection units, such as feet or meters, from each cell to the closest source.

Service facility assessment using the ‘served,’ ‘underserved,’ and ‘overserved’ approach is a standard method employed in GIS to analyze the spatial distribution of service facilities and evaluate their accessibility. In this approach, the population or demand areas are divided into three categories: ‘served’ areas, where the service facility adequately meets the demand; ‘underserved’ areas, where the service facility does not fully meet the demand and results in unmet needs; and ‘overserved’ areas, where the service facility exceeds the market, potentially leading to inefficient resource allocation (Higgs et al. 2015). From the FGD and KII, it was found that for the water supply point, the service area served is, on average, 500 m, where the same distance is suited for the public toilets and waste dumping sites. However, the water treatment facilities' coverage area varies by 6–8 km per point. Based on FGD and KII findings, the authors determined the service coverage area per point at 7 km. These findings created a 500 m buffer zone for water supply points, public toilets, and waste dumping sites. On the other hand, the 7-km buffer is designed for the water treatment points. After that, a dissolved buffer is created at the same length, and then an intersect between the undissolved and devolved pad. The overserved area and the dissolved buffer are calculated as the served area. Then, the total operated and overserved area was calculated using the identity feature. Finally, using intersect, the underserved area was calculated among the dissolved ward boundary and with total served and overserved space. At last, the total percentage has been calculated from the filled, underserved, and overserved areas with the help of MS Excel.

Table 1 provides an overview of various water sources, classified by their construction status and maintenance condition. Among the different sources, boreholes have the highest representation in both poorly maintained (43.15%) and well maintained (30.62%) categories, with a minor percentage (0.50%) being newly constructed. Surprisingly, dams, tube wells, and rainwater harvesting sources have no representation in the well-maintained category, indicating possible issues with their upkeep. Pipe-borne water and protected dug wells show relatively better maintenance, with 4.81 and 3.98% being well maintained, respectively. However, it is concerning to note that unprotected dug wells have a significantly higher percentage (9.63%) in the poorly maintained group. Overall, the data highlight the pressing need to address the maintenance and preservation of water sources to ensure a sustainable and reliable water supply for communities. Efforts should improve the maintenance practices of various origins, particularly boreholes and dug wells, to alleviate water scarcity challenges and promote the population's well-being.

On the other hand, the ‘water treatment plant’ constitutes 28.57% of the total and is solely attributed to public facilities, indicating that these plants are owned and managed by government authorities or public entities. The total reflects that the private sector largely dominates the water treatment industry with a share of 71.43%, while public water treatment facilities control the remaining 28.57%. The data highlight the presence of private and public stakeholders in the water treatment sector, working together to ensure safe and clean water availability for communities and industries.

Table 2 provides information on the distribution of two types of toilets, namely pit toilets and water closets, categorized into private and public facilities. Among the private bathrooms, pit toilets account for 3.11%, while there are no water closets in this category, indicating that pit toilets are more common in privately owned properties. In contrast, pit toilets constitute the majority of public facilities at 55.11%, while water closets comprise 41.78% of the public toilet options, totaling 96.89% for all public restrooms. The overall representation of pit toilets is 58.22%, and water closets comprise 41.78% of the total toilet options. These statistics demonstrate that pit toilets are more prevalent overall, especially in public areas, while water closets are more commonly found in private spaces.

Table 3 presents data on waste dumping sites, categorized into communal, personal, and public facilities, along with their corresponding percentages. Communal waste dumping sites, constituting 17.60% of the total, are collectively managed and used by communities, typically situated in shared areas for residents' access. On the other hand, private waste dumping sites account for 13.07% and are owned and operated by individual entities or private organizations, often found on private properties like industrial or commercial establishments. Public waste dumping sites represent the majority at 69.33% and are owned and managed by government authorities or municipal bodies, serving as official disposal locations for the general waste dumping sites.

Table 4 provides insights into the distribution of water treatment plant types, classified as private and public facilities, with their respective percentages. Most water treatment plants fall under the ‘light industrial water treatment plant,’ representing 71.43%. These facilities are predominantly privately owned and operated, indicating private entities' significant role in water treatment services, particularly in light industrial settings.

On the other hand, the ‘water treatment plant’ constitutes 28.57% of the total and is solely attributed to public facilities, indicating that these plants are exclusively owned and managed by government authorities or public entities. The total reflects that the private sector largely dominates the water treatment industry with a share of 71.43%, while public water treatment facilities control the remaining 28.57%. The data highlight the presence of private and public stakeholders in the water treatment sector, working together to ensure safe and clean water availability for communities and industries.

For diarrhea new cases < 5 years old 2022: Gyellesu stands out with the highest percentage of diarrhea cases among children below five years in 2022, accounting for 7.85% of the total cases, followed by Kwarbai A with 25.14%, and Tukur Tukur with 10.92%. Wuciciri, Kwarbai B, and Dogarawa also display notable diarrhea incidences ranging from 6.54 to 9.45%. Some wards like Angwar Fatika, Chikaji Ward, and Unguwar Gabas report lower or no new diarrhea cases among children below five years in 2022. For cholera 2021: Wuciciri exhibits the highest percentage of cholera cases in 2021 with 19.41%, closely followed by Gyellesu with 21.76% and Kufena with 11.18%. Dutsen Abba and Dogarawa also show noteworthy cholera incidences, each contributing around 13.53 and 11.18%, respectively. Some wards, such as Angwar Fatika, Chikaji Ward, Limancin Kona, Tudun Wada, and Tukur Tukur, report either no cholera cases or relatively lower percentages.

The Z-score was 42.95 (p = 0.001), and the average closest-neighbor ratio was 0.353 (p < 0.001). As a result, the null hypothesis that there is no geographical pattern among Zaria's water supply stations was rejected. The possibility that this clustered pattern resulted from chance was less than 1% due to the high Z-score.

The average closest-neighbor ratio for toilets in public places was 0.484 (p < 0.001), and the Z-score was 14.76 (p < 0.001). As a result, the null hypothesis that there is no spatial pattern among the locations of public toilets in the Zaria metropolis was rejected. The possibility that this clustered pattern resulted from chance was less than 1% due to the high Z-score.

The average closest-neighbor ratio for waste disposal locations was 0.002 (p < 0.001), and the Z-score was 36.21 (p = 0.001). As a result, the null hypothesis that there is no spatial pattern among waste disposal locations in the Zaria metropolis was rejected. The possibility that this clustered pattern resulted from random chance was less than 1% due to the high Z-score.

However, the average closest-neighbor ratio for the water treatment plant facilities was 1.29 (p = 0.001), and the Z-score was 1.49 (p = 0.001). A substantial p-value of less than 0.001 and the average closest-neighbor ratio of 1.29 show that the distribution of water treatment plant facilities in the study region is random. The observed value of 1.29 suggests a propensity toward clustering, while a value of 1 would imply a perfectly random distribution. This discovery is further supported by the Z-score of 1.49, which is inside the crucial zone of the standard normal distribution and has a p-value of less than 0.001. The Z-score measures how far the observed value deviates from the predicted mean under the randomization assumption. The average closest-neighbor ratio analysis's result is supported by the positive Z-score, which denotes the presence of a clustering pattern.

In general, the research areas in the middle of the governorate tend to have the concentration of three spatial patterns (water supply points, public restrooms, and waste duping locations). However, the analysis's discovered spatial pattern (clustered) suggested that these were distributed inefficiently and disorganized. On the other hand, the research areas in the governorate's center tend to have a concentrated spatial pattern of water treatment plant locations. However, the analysis's determined spatial pattern (random) suggested that these were distributed erratically and ineffectively.

Table 5 provides an in-depth analysis of service coverage in various wards, explicitly focusing on the percentages of underserved, overserved, and served areas for public water supply points. The ‘served area’ represents the percentage of land in each ward that benefits from sufficient access to essential services, such as healthcare facilities, educational institutions, public utilities, and transportation networks. Communities such as Basawa (served area: 0.37%), Bomo (served area: 0.79%), and Chikaji (served area: 0.08%) have relatively lower served areas, indicating limited access to essential water services for a significant portion of their population. On the other hand, wards like Dutsen Abba (served area: 3.48%) and Wuciciri (served area: 1.92%) demonstrate higher served areas, suggesting relatively better water service coverage for their residents. The ‘underserved area’ is the most critical aspect of the analysis, representing the percentage of land in each ward that lacks adequate access to essential services. Communities with substantial underserved areas, such as Dambo (underserved area: 6.16%), Dogarawa (underserved area: 4.06%), and Shika (underserved area: 12.26%), signal significant challenges faced by their residents in accessing crucial water services. ‘Overserved area’ is essential in understanding resource allocation efficiency. Wards with higher percentages in this category, such as Dambo (overserved area: 1.09%), Dogarawa (overserved area: 1.09%), and Wuciciri (overserved area: 1.32%), may indicate potential concentrations of water supply points beyond what is immediately required.

Table 6 provides an in-depth analysis of service coverage in various wards, explicitly focusing on the percentages of underserved, overserved, and served areas for public toilet points. Communities like Dutsen Abba (underserved: 24.87%), Shika (underserved: 9.37%), and Wuciciri (underserved: 12.87%) stand out as areas where access to essential services is limited and requires immediate attention and intervention. On the other hand, the table reveals some wards with overserved areas. Examples include communities like Dogarawa (overserved: 0.20%), Dambo (overserved: 0.37%), and Gyellesu (overserved: 1.04%). Identifying such wards is crucial for optimizing resource allocation and ensuring efficient service delivery. While the percentages in this category are relatively lower compared to the underserved areas, they are still essential for providing amenities to the population. Examples include wards like Chikaji (served: 0.03%), Kufena (served: 0.26%), and Samaru (served: 0.26%). Overall, the table's ‘grand total’ indicates that a significant 78.12% of the region's land falls under the underserved category, emphasizing the pressing need to address these areas to improve service accessibility and enhance the quality of life for residents. Meanwhile, 13.54% of the land is categorized as overserved, suggesting opportunities for optimizing resource distribution. The served areas constitute 8.34%, showcasing the portions with adequate service coverage.

Table 5 provides an in-depth analysis of service coverage in various wards, explicitly focusing on the percentages of underserved, overserved, and served areas for water treatment service points. For overserved areas, certain wards, such as Dambo (overserved: 7.87%), Zabi (overserved: 5.46%), and Dogarawa (overserved: 1.42%), exhibit higher percentages in this category. These regions have excess resources or services beyond what is immediately required. Identifying and addressing overserved areas can help optimize resource allocation and enhance efficiency in service delivery. Served areas, for example, include Basawa (served: 1.80%), Gyellesu (served: 1.22%), and Samaru (served: 1.46%). While the percentages in this category are lower compared to overserved areas, it is crucial to maintain and improve service provisions in these regions to ensure the population's well-being. For unserved areas, the most critical aspect of the analysis lies in the unserved areas. These are regions where access to essential services is limited or entirely lacking. Wards like Dutsen Abba (unserved: 24.45%), Shika (unserved: 13.78%), and Wuciciri (unserved: 8.43%) have a significant portion of their land classified as unserved. Addressing the needs of these areas is a priority for local authorities to bridge the gaps in service accessibility and ensure equitable and inclusive development. The ‘grand total’ of the table indicates that a substantial 53.89% of the region's land falls under the unserved category, underlining the urgent need for targeted interventions and resource allocation to improve service accessibility in these critical sectors. Meanwhile, 31.15% of the land is categorized as overserved, suggesting opportunities for optimizing resource distribution. The served areas constitute 14.96%, showcasing the portions with adequate service coverage.

The percentages in this category are relatively low for overserved areas, with most wards showing less than 1% for waste dumping sites in overserved areas (Table 7). The highest rate is found in Dambo (overserved: 0.68%), followed by Kufena (overserved: 0.93%) and Shika (overserved: 0.33%). These areas have slightly more resources or services than are immediately required. For served areas, in Dutsen Abba (served: 0.15%), Tukur Tukur (served: 0.16%), and Samaru (served: 0.52%). These wards have satisfactory access to essential services. For underserved areas, Wards like Wuciciri (underserved: 12.87%), Shika (underserved: 13.63%), and Dutsen Abba (underserved: 24.96%) have a significant portion of their land classified as underserved. This highlights the pressing need for targeted interventions and resource allocation to improve service accessibility in these critical sectors. The ‘grand total’ indicates that 88.35% of the region's land falls under the underserved category. Addressing the needs of these areas is crucial to bridging the gaps in service accessibility and ensuring equitable and inclusive development. The percentages for the overserved and served categories are 8.16 and 3.49%, respectively.

Table 8 provides percentages of overserved, served, and underserved populations across different locations. Basawa has an overserved population of 0.38%, a served population of 0.09%, and an underserved population of 3.33%, making a grand total of 3.80%. Similar information is presented for other locations such as Bomo, Chikaji, Dambo, Dogarawa, Dutsen Abba, Gyellesu, Hanwa, Jama A, Jushi, Kaura, Kufena, Kwarbai A, Kwarbai B, Limancin Kona, Muchiya, Samaru, Shika, Tudun Wada, Tukur Tukur, Unguwar Fatika, Unguwar Gabas, Unguwar Juma, Wuciciri, and Zabi, . The grand total for overserved, served, and underserved populations across all locations is 8.16, 3.49, and 88.35, respectively.

The research findings reflect a conspicuous contrast in the distribution of water treatment plant facilities between private and public sectors, with a significant predominance of the private sector accounting for 71.43% compared to public facilities at 28.57%. This sharp imbalance brings to light the predominance of pit toilets (55.11%) in public restroom facilities while indicating that water closets (41.78%) are notably more prevalent in privately owned areas (3.11%). In the realm of waste management, the government is primarily responsible for overseeing public waste dumping sites, representing a substantial 69.33% of the total. In contrast, the local community manages communal sites (17.60%), and private sites (13.07%) are under individual ownership. The comprehensive analysis of the accessibility to WASH and WMS in the Zaria metropolis urban informal settlements necessitates a series of strategic recommendations aligned with the study's findings. The urgent need for the rehabilitation of boreholes and unprotected wells, with approximately 57.43% requiring immediate maintenance, supports the recommendation for investing resources and funding into water source rehabilitation. The findings concerning the prevalence of pit toilets in public areas highlight the critical need to enhance sanitation facilities, advocating the replacement of pit toilets with more hygienic alternatives to reduce the considerable health and environmental risks.

Moreover, the research pinpoints specific areas of concern by identifying underserved regions, emphasizing the critical deficiencies in service accessibility: a stark unserved area estimated at around 6.16% for water supply points, an alarming 24.87% for public toilet points, approximately 24.45% for water treatment service points, and 13.63% for waste dumping sites. These statistics pinpoint crucial gaps in access to fundamental amenities and necessitate focused interventions to rectify these disparities in service availability. The findings revealing specific percentages of land with critical service deficiencies in urban informal settlements emphasize the urgency of tailored recommendations to address these identified disparities. A strategic approach is essential to mitigate the existing gaps in essential services. Firstly, there is a pressing need for focused infrastructure development in the areas with unserved or inadequately served water supply points, public toilets, water treatment service points, and waste dumping sites. Investment and resource allocation should prioritize these regions, ensuring residents gain equitable access to these vital services. Secondly, community-centric approaches should be embraced, engaging local communities in the planning, constructing, and maintaining of these facilities to meet the specific needs of each area.

Additionally, advocating for policy interventions and fostering collaboration among governmental bodies, local authorities, and stakeholders are pivotal to promoting service equality. Lastly, utilizing innovative technologies, such as GIS, can enhance the planning and resource allocation process, optimizing the location of services and ensuring efficient delivery in underserved regions. By implementing these recommendations, it is possible to address the significant service accessibility disparities and contribute to sustainable development and the overall well-being of the urban informal settlement population. Finally, the study emphasizes the pressing need to improve maintenance practices of water sources, rehabilitate existing water facilities, enhance public toilet options, and establish proper WMS in urban informal settlements of Zaria metropolis Kaduna, Nigeria. Targeted interventions and strategic planning are essential to address disparities and ensure equitable access to WASH and WMS, promoting the population's well-being and contributing to sustainable and inclusive development in the area. Collaboration between policymakers, local authorities, and relevant stakeholders is vital to implementing these measures for the betterment of the community.

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

The authors declare there is no conflict.