Relationship between rapid urbanization, sanitation, and water source pollution
HAMIDOU HASSANE Adamou, KY AIDA Rolande, SAWADOGO W. Thiery Omar, SEREKI Ihsann
JURY MEMBERS :
Dr. Maïmouna Bologo/Traoré, Dr. Malicki Zorom, Dr. Yohan Richardson and Mr. Sina Thiam
Abstract
This study analyzes how rapid urbanization in Sub-Saharan Africa influences access to sanitation, the pollution of water sources, and health risks. Based on a sample of 11 countries and statistical analyses (PCA, CAH, and regressions), the results show that urbanization generally improves access to sanitation services and safe drinking water. However, it is accompanied by strong urban–rural inequalities and persistent deficits in rural and informal areas.
Mortality linked to waterborne diseases is only weakly correlated with sanitation levels, indicating the influence of other socio-economic and environmental factors. Three country profiles emerge: poorly equipped countries, transitional countries with strong disparities, and better-equipped countries. Overall, the findings highlight an ambivalent urbanization that requires more inclusive planning, improved wastewater management, and strengthened governance to reduce health risks.
Introduction
Sub-Saharan Africa has experienced one of the fastest urbanizations in the world for several decades. This dynamic, driven by population growth, rural exodus and the spontaneous extension of agglomerations, is often characterized by an unplanned expansion of urban spaces [1], [2]. Projections indicate that by 2030, nearly half of the region’s population will reside in cities, with a significant proportion in informal areas without essential infrastructure [1]. While this urban transition represents potential in terms of economic opportunities and socio-spatial transformations, it is nevertheless accompanied by significant challenges related to access to water and sanitation services, as well as the preservation of the quality of water sources. Indeed, growing urbanization far exceeds the capacity of public services to adapt, particularly in terms of sanitation. In many African cities, infrastructure remains insufficient, both in terms of coverage and quality, to meet the needs of a growing urban population [2], [3]. Access to improved sanitation remains low: on average, only 32.4% of urban dwellers have adequate facilities, with levels as high as 8.2% depending on urban contexts [1]. In some areas of Nigeria, the proportion of users of modern toilets drops to 6.2%, while open defecation can be as high as 67% [4]. Similarly, in Nairobi, just 15% of households in the Mathare slum have private toilets, which can lead to up to 85 households sharing a single facility [5]. This structural sanitation deficit leads to inadequate management of wastewater and domestic discharges, which are often discharged directly into the environment. This situation exacerbates microbiological and chemical pollution of rivers and groundwater [6]. Studies in Yaoundé, for example, show nitrate concentrations of up to 93.37 mg/L — sometimes above 500 mg/L — as well as high levels of faecal coliforms, exceeding WHO standards [7]. Lapworth et al. (2017) [8] also point out that the proximity of latrines to wells is a major factor in groundwater contamination. More broadly, the massive inputs of pollutants from urbanization are rapidly degrading the quality of urban waterways [9], altering ecosystems and threatening the health of populations. These environmental pressures have a direct impact on public health. One of the most pronounced consequences is the prevalence of waterborne diseases such as diarrhoea. In some areas of Yaoundé, it affects up to 70% of children under the age of five [7], while in Mathare (Nairobi), it is estimated at 31% [5]. The poor are the most vulnerable, and women are particularly at risk: 68% of them report experiencing violence related to access to sanitation facilities in Nairobi’s slums [5]. Such realities reveal persistent socio-spatial inequalities in access to sanitation services and clean water, compounded by rapid urbanization [10], [11]. The literature highlights the inadequacy of urban governance as one of the structural obstacles to improving the situation [12]. Institutional limitations, lack of investment and lack of effective regulation contribute to the maintenance of large deficits. Although some participatory initiatives, such as the MTUMBA approach in Tanzania, have improved access to local infrastructure, responses remain fragmented and insufficient. At the same time, the emergence of innovative solutions, including nanomaterials and mixed processing techniques [13], [14], offers promising prospects for reducing water pollution and improving sanitation. In this context, the present study is part of the theme: “Relationship between rapid urbanization, sanitation and pollution of water sources”. It aims to examine the underlying dynamics between urban sprawl, access to sanitation and the quality of water resources, with particular attention to health implications. The central issue is: To what extent does rapid urbanization in sub-Saharan Africa exacerbate sanitation deficits and contribute to the pollution of water sources, with repercussions for public health? To answer this, the following specific questions are explored:
- What is the effect of urban growth on changes in access to basic and improved sanitation services?
- How are the gaps in access to sanitation between urban and rural areas changing with increasing urbanization?
- Is there a relationship between sanitation coverage and waterborne disease mortality in expanding urban areas?
- Which country in sub-Saharan Africa has the largest gap between rapid urbanization and the development of sanitation infrastructure?
Through these questions, the study intends to contribute to a better understanding of the systemic relationships between urbanization, sanitation, pollution and public health, in order to shed light on policy choices and intervention strategies in the African context.
LITERATURE REVIEW
1.Introduction
2.Rapid urbanization and pressures on sanitation services
Urban growth in sub-Saharan Africa is one of the fastest in the world, with an urban population projected to reach 50% by 2030, nearly half of whom will live in slums lacking adequate infrastructure [1]. In cities such as Bamako, Yaoundé and Libreville, strong population growth is putting intense pressure on water resources and sanitation systems, far exceeding local capacities [2], [3]. De Mello et al. (2024)[15] show that beyond certain urbanization thresholds, the deterioration of surface water quality becomes particularly marked.
- Sanitation deficits and inadequate wastewater management
Access to improved sanitation remains particularly low: only 32.4% of urban residents have access to it on average, with values that can drop to 8.2% depending on the cities studied[4] In Nigeria, the use of modern toilets can be as low as 6.2%, while open defecation practices reach 67% [4]. In Mathare, Nairobi, only 15 per cent of families have a private toilet, and up to 85 households share a facility [5]. In addition, 83% of households in some African cities do not have a private connection to drinking water, depending on public water points that are often contaminated [10]. The lack of wastewater treatment systems leads to direct discharges into waterways, aggravating microbiological and chemical pollution [6].
- Source water pollution
4.1 Microbiological and chemical pollution
In several cities, groundwater and rivers present alarming levels of contamination. In Yaoundé, nitrate concentrations reach 93.37 mg/L – and sometimes more than 500 mg/L – far exceeding WHO standards, while faecal coliforms reach 280 CFU/100 mL [7] Lapworth et al. (2017) [8] stress that the proximity of latrines to wells is a major factor in groundwater contamination. Omohwovo et al. (2024) [6] also identify domestic and industrial discharges as major sources of pollution.
4.2 Hydrological changes
- Public Health Impacts Header
The health consequences are severe. In some areas of Yaoundé, the prevalence of diarrhoea among children under five years of age is as high as 70% [7]. In Nairobi, prevalence reaches 31% in the Mathare slum [5]. With a life expectancy of only 52.6 years among disadvantaged urban populations in Nigeria, the health impacts are significant [4]. Women are particularly vulnerable: in Nairobi, 68% report experiencing violence related to access to toilets, while 46% suffer from respiratory diseases [5]. The economic cost of these problems is high: deworming expenses can account for up to 10% of family income [7].
- Socio-spatial inequalities
Informal settlements are characterized by high density, precarious infrastructure and a lack of adequate sanitation. In these contexts, the risks of contamination are increased, reinforcing the vicious circle of poverty and health [10], [11]. Inequality in access to safe drinking water and sanitation further widens social, geographical and health disparities [17].
- Institutional Challenges and Governance
The management of water and sanitation services faces major challenges: • Weak institutions, • Limited funding, • Lack of coordination, • Non-existent monitoring [12]. Lapworth et al. (2017) [8] point out that providers are failing to keep up with urban growth, exacerbating service deficits.
- Solutions and innovations
Solutions proposed in the literature include: • the use of nanomaterials for wastewater treatment [13] • combined treatment approaches (biological + physico-chemical), more effective in reducing pollution [14] • green infrastructure in urban areas [15] These approaches offer promising prospects for improving water quality and reducing health risks.
- Conclusion
Rapid urbanization in sub-Saharan Africa is increasing pressure on sanitation services and contributing to the pollution of water sources. This situation, exacerbated by institutional weakness and marked inequalities, has serious health consequences. Innovative solutions exist, but require robust investment and strengthened governance.
PART I:PRESENTATION OF THE STUDY AREA
This study covers a set of 11 countries in sub-Saharan Africa : Burkina Faso (BFA), Côte d’Ivoire (CIV), Democratic Republic of Congo (COD), Ghana (GHA), Kenya (KEN), Nigeria (NGA), Niger (NER), Senegal (SEN) and Uganda (UGA), South Africa (ZAF), Ethiopia (ETH). This region, which is characterized by one of the fastest urbanization dynamics in the world, concentrates major challenges in terms of access to sanitation and sustainable management of water resources. These countries have a high geographical and climatic diversity, ranging from arid Sahelian areas (Niger, Burkina Faso) to humid tropical regions (Côte d’Ivoire, Ghana, DRC), including the highlands of East Africa (Uganda, Kenya). This heterogeneity contributes to contrasting situations in terms of water availability and vulnerability to water pollution. On the socio-demographic level, the capitals and major metropolises — Dakar, Abidjan, Lagos, Nairobi, Accra, Kampala — are experiencing sustained growth, often without adequate planning. This rapid urban expansion encourages the development of underserved informal settlements, generating significant disparities between urban and rural areas. While urban centres benefit from more developed infrastructure, rural areas remain largely devoid of sanitation services, accentuating territorial inequalities. Access to safe drinking water and sanitation rates vary significantly from country to country. Senegal, Côte d’Ivoire, Ghana and Kenya show relatively higher levels of access to basic services, while Niger, DRC and Burkina Faso have the largest deficits. These differences reflect contrasting development trajectories, influenced by economic, institutional and socio-cultural factors. The pollution of water resources remains a cross-cutting issue, fuelled by the untreated discharge of domestic and industrial wastewater, the lack of treatment infrastructure and agricultural pressure. The major rivers — Niger, Congo, Volta — as well as groundwater are particularly exposed, compromising water quality and the health of populations. In terms of health, waterborne diseases such as diarrhoea, cholera and typhoid are still a heavy burden. The countries with the lowest sanitation infrastructure are logically those with the highest rates of water-related mortality, confirming the close relationship between sanitary conditions, water pollution and population vulnerability. Thus, all of these countries constitute a relevant study area for analysing the interactions between urbanisation, sanitation and water pollution. Their diversity, combined with common challenges, offers a fertile ground for understanding regional dynamics and internal contrasts, in coherence with the central issue of this research.
PART II: MATERIALS AND METHODS
- Methodological framework
1.1. Variable Selection
The variables selected were chosen according to their ability to shed light on the issue of the articulation between rapid urbanization, sanitation, pollution of water resources and health impacts. They cover three essential dimensions:
- Urbanization
2.Sanitation and water
• Ass_base : rate of access to at least basic sanitation (total population); • Ass_am : rate of access to at least improved sanitation (total population); • Ass_Base_U : rate of access to at least basic sanitation in urban areas; • Ass_Base_R : rate of access to at least basic sanitation in rural areas; • Ecart_UR : difference between the rate of access to at least basic sanitation in urban and rural areas; • T_EauP : Rate of access to drinking water These indicators measure the quality and availability of essential services. In the sense of these variables, the following definitions apply: - Basic sanitation, the use of improved sanitation facilities not shared with other households. In other words, the rate measures the proportion of the population using improved sanitation facilities that are not shared with other households. These are facilities such as: Sewer-connected flush latrines, septic tank or improved latrine, Enhanced ventilated pit (VIP) latrines, Slab latrines, Composting toilets.
- Improved sanitation, any facility designed to hygienically separate human feces from human contact. These are the types of facilities that safely prevent human exposure to feces. These are: Flush toilets connected to a sewerage system, septic tank or latrine, Enhanced ventilated latrines (VIP), Slab latrines, Composting toilets.
- Public health
- Contextual variables (not included in the calculation of axes)
• GDP: Gross Domestic Product per capital • Population: the number of inhabitants of a country • Density: The ratio of the population size of a geographic area to the area of that area These indicators do not intervene directly in statistical analyses but allow us to better describe the results. All these indicators constitute a relevant and sufficient set to answer questions relating to the evolution of sanitation services, territorial inequalities, and the health effects linked to water pollution.
1.2. Data source
The data used comes from the international platform Our World in Data (OWID). This database aggregates validated indicators from the WHO, JMP (UNICEF/WHO), the World Bank and UN-Habitat. The data were used as annual averages by country over the period 2000–2019, in order to: • Smooth out interannual variability, • Making countries comparable with each other, • Identify structural trends. The use of OWID ensures methodological harmonization and sufficient reliability for benchmarking.
1.3. Sampling Method
The reference population is made up of all sub-Saharan African countries. Given the heterogeneity in the availability of data, purposive (non-probabilistic) sampling was chosen. Countries were selected according to the criterion of full availability of the key variables identified. Thus, only countries with a complete dataset were selected, forming a final sample of 11 states. This choice is reinforced by the analytical approach according to which each country is considered as a “typical case”, i.e. a unit representative of a particular configuration of urbanization and health development. Each country selected can therefore be interpreted as a proxy for regional areas with similar characteristics. This sampling plan ensures: • Statistical consistency, • Inter-country comparability, • The diversity of the profiles studied (advanced, intermediate, fragile).
1.4. Analytical methods
The analysis is based on three complementary statistical approaches whose objectives converge towards the answer to our research questions:
- Principal Component Analysis (PCA)
- Explore correlations between variables,
- Reduce the size of the dataset,
- Identify the major gradients structuring the national profiles.
- Hierarchical ascending classification (CAH)
- Group countries into homogeneous classes,
- Establish a typology based on their WASH and urbanization characteristics.
- Linear regressions
- Testing the links between rapid urbanization, sanitation and water-related mortality,
- Respond quantitatively to research questions. The ACP → CAH sequence → regressions makes it possible to identify first the global structures, then the groupings, and finally to statistically validate the observed relationships.
1.5. Potential collection tools (if no OWID data)
In the absence of reliable secondary data, it would have been necessary to design context-appropriate primary collection tools. These tools would have made it possible to document practices, infrastructure, governance and water quality. Each tool below is presented with:→ its target→ its relevance→ its general structure Each tool is presented in the appendix
- Household questionnaire
Target: urban, peri-urban and rural households Relevance: collection of direct information on actual access to water/sanitation, hygiene practices and waterborne morbidity. General structuring: - Identification - Access to water - Sanitation - Hygiene - Health (waterborne diseases) - Perceptions / Priorities
- Interview guide (institutional actors)
Target: municipalities, water and sanitation authorities, NGOs Relevance: understanding of governance, financing, planning and operational constraints. General structuring: - Institutional context - Available infrastructure - Management and organization - Constraints and challenges - Policies and Perspectives
- Field observation grid
Target: urban neighbourhoods, informal settlements and peri-urban areas Relevance: visual validation of the existence and condition of infrastructure and environments at risk. General structuring: - Site identification - Observed health infrastructure - Wastewater management - Immediate surroundings - Visible risk points The methodology used combines: • A relevant selection of variables, • Principled sampling based on national test cases, • Multivariate analyses (PCA, CAH) supplemented by linear regressions. In the event of unavailability of secondary data, a robust primary collection system, mobilizing several complementary tools targeting households, institutions and facilities. This integrated framework makes it possible to address the problem in its demographic, infrastructural, environmental and health dimensions, while ensuring the scientific rigour necessary for the analysis.
- Material
As part of this study, several IT tools were used for data processing, analysis, visualization and management. They are presented below.
2.1. RStudio
Description :
RStudio is an integrated development environment (IDE) dedicated to the R programming language. It allows for script execution, statistical processing, graphical visualization, and rigorous replication of analyses. Extensions / Libraries usedSeveral packages have been used depending on the analytical needs:
- READR : Importing and Managing Data
- FactoMineR : Principal Component Analysis (PCA)
- factoextra : visualization of PCR and classification results
- corrplot : graphical representation of correlations between variables
- GGREPEL : Annotation of Graphs
- Viridis : Optimized Graphics Palettes
- Factochyny : Interactive interface for exploring factor results Use in the
RStudio study was used to:
- Import, structure, and clean datasets.
- Perform Principal Component Analysis (PCA);
- apply the Hierarchical Ascending Classification (CAH);
- build linear regression models;
- produce visualizations (biplots, dendrograms, point clouds);
- generate descriptive tables.
All of these operations allowed for a complete and reproducible statistical analysis, which is essential to answer the research questions.
2.2. QGIS (Quantum GIS)
Description: QGIS is an open source Geographic Information System (GIS) software for the management, analysis and representation of spatial data. It offers a wide range of mapping and spatial analysis features.
Use in the studyQGIS was mobilized to:
- spatially represent indicators related to urbanization, sanitation and health;
- produce thematic maps illustrating territorial disparities;
- Visualize the typology of countries resulting from the CAH on a regional map. These operations have allowed a better understanding of the spatial dynamics associated with the phenomena studied.
2.3. Zotero
Description : Zotero is an open-source bibliographic management software. It makes it possible to efficiently collect, organize and cite references from various sources (scientific articles, reports, books, websites, etc.).
Use in the studyZotero was used to:
- group and classify documentary sources;
- ensure the follow-up of the references mobilized in the theoretical framework and the state of the art;
- automatically generate citations and bibliography according to the required standards (APA). This tool ensured the rigor and consistency of the bibliographic treatment throughout the work.
2.4. Potential Field Collection Material
In a situation where secondary data would not have been available, primary collection would have required the use of specific equipment adapted to the context of field surveys. The main equipment that could be mobilized would have been the following:
2.4.1. Collection media
- Paper questionnaires or digital tablets (Kobocollect)
- Use : Administration of household surveys to collect information on access to water, sanitation, hygiene practices and health status.
- Advantage : The digital format allows direct entry, reducing errors and facilitating storage.
- Semi-structured interview guides
- Use : Conducting interviews with local institutions (municipalities, sanitation services, NGOs, health services).
2.4.2. Localization Instruments
- Portable GPS or built-in GPS (phone/tablet)
- Use : geolocation of surveyed households, infrastructure (water points, latrines) and observation sites.
- Interest : allows the cross-referencing of the data collected with GIS analyses.
2.4.3. Observation equipment
- Camera/Camera
- Use : visual documentation of infrastructure (latrines, networks, wastewater depots), risk areas (water stagnation, waste).
- Interest : Provides contextual evidence and analytical support.
- Observation sheets
- Use : systematic recording of information visible in the field (condition of installations, discharges, proximity to homes, etc.).
2.4.4. Logistics equipment
• Field notebooks • Pens, markers • Cooler bags for sample storage • Vehicles or motorcycles for travel in rural areas
PART III:RESULTS AND DISCUSSION
In this section, the aim is to present, analyse and discuss the main results obtained from the various statistical analyses used. These findings aim to shed light on the relationship between rapid urbanization, sanitation and water pollution in sub-Saharan Africa. More specifically, the study seeks to answer the following questions:
- What is the effect of urban growth on changes in access to basic and improved sanitation services?
- How are the gaps in access to sanitation between urban and rural areas changing with increasing urbanization?
- Is there a relationship between sanitation coverage and waterborne disease mortality in expanding urban areas?
- Which countries in sub-Saharan Africa have the largest gap between rapid urbanization and the development of sanitation infrastructure? To answer these questions, an analytical approach in three complementary steps was implemented:
- A Principal Component Analysis (PCA), in order to explore the structure of the relationships between the different socio-health and environmental variables;
- A Hierarchical Ascending Classification (CAH), aimed at grouping countries according to their development profiles in terms of urbanization and sanitation;
- Linear regressions, intended to quantitatively test the hypothetical relationships between urbanization, sanitation and mortality, and to verify the form (linear or not) of these relationships.
These different analyses thus make it possible to draw up a global diagnosis of the health and environmental dynamics related to urbanization in sub-Saharan Africa, while providing concrete answers to the research hypotheses formulated.
- Factor analysis: overall structure of relationships
1.1. Data Submission and PCA Preparation
The Principal Component Analysis (PCA) was carried out using a data set covering 11 countries in sub-Saharan Africa, based on 11 quantitative variables, including 3 additional explanatory variables. The data cover key indicators related to urbanization, sanitation and public health. The following table presents the means for each of the variables over the study period. library(readxl)
library(readxl)## Warning: package 'readxl' was built under R version 4.3.3ACP <- read_excel("C:/Users/HP/Desktop/Projet/Données/Données épurés/RTI2/ACP.xlsx")
ACP## # A tibble: 10 × 12
## Pays Ass_base `Ass_Base-R` Ass_Base_U Ecart_UR T_Mort_H T_Urba T_EauP Ass_am
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 BFA 16.9 8.15 45.2 37.1 5.26 24.2 53.6 6.25
## 2 CIV 27.4 13.0 43.5 30.4 2.7 47.1 71.6 12.9
## 3 COD 19.8 17.8 22.6 4.74 4.14 39.9 36.8 17.7
## 4 ETH 5.72 3.13 17.9 14.8 6.54 17.5 33.1 4.43
## 5 GHA 14.8 9.14 20.3 11.1 2.9 17.5 75.1 8.57
## 6 KEN 31.6 30.8 34.0 3.20 4.11 23.5 54.3 27.6
## 7 NER 10.2 5.27 35.5 30.2 9.87 16.3 43.0 5.23
## 8 NGA 34.7 30.3 39.8 9.44 6.68 43.0 59.3 24.8
## 9 SEN 46.9 33.2 64.9 31.7 4.14 43.7 71.2 17.7
## 10 UGA 18.4 15.9 28.8 12.8 3.27 19.3 39.8 15.8
## # ℹ 3 more variables: Densité_P <dbl>, PIB <dbl>, POP <dbl>This data was compiled from the Our World in data databases. They aim to explore the structure of the relationships between urban development, sanitation and sanitary conditions. A first exploratory PCA highlighted the presence of an atypical individual (the country South Africa), whose extreme values exerted a disproportionate influence on the first factor axis.
In order to achieve a more balanced and representative representation of all countries, this individual was removed from the analysis and a second PCA was conducted. Figures 1 and 2 show the initial dispersal of individuals before the removal of the atypical observation (South Africa (ZAF)) and the contribution of the initial individuals to the axes. These 2 figures well the atypical character of the individual.
“C:\2.png”
1.2. Final PCA Results
1.2.1. Choice and interpretation of the main axes
The final PCA retains the first two dimensions, which explain 76.09% of the total variance : -Dimension 1 (Dim1): 51.00% of the variance - Dimension 2 (Dim2): 25.09% of the variance This cumulative share of variance reflects an excellent synthesis of the overall information and justifies the focus of the interpretation on the plane (Dim1 × Dim2).
1.2.2. Interpretation of the first dimension (Dim1)
The first axis, explaining 51% of the total variance, includes strong positive contributions from the variables: Ass_base, Ass_Base-R, T_Urba, Ass_am, Ass_Base-U, and T_EauP. These high correlations reflect a gradient in health development and access to essential services, where the variables of sanitation, drinking water and urbanization evolve together. Individuals (countries) with positive values on Dim1 are distinguished by:
- A high level of urbanization,
- Improved access to sanitation (basic and improved),
- And extensive drinking water coverage,
which reflects a more developed socio-economic level. Conversely, countries with negative scores on Dim1 have:
- Low urbanization,
- Limited access to basic services,
- And an increased dependence on the rural environment.
Thus, the first dimension clearly expresses an axis of health and urban development, opposing well-equipped countries to those lagging behind in infrastructure.
1.2.3. Interpretation of the second dimension (Dim2)
The second axis, representing 25.09% of the variance, highlights internal inequalities* and certain health contrasts. The most contributing variables are Ecart_UR, as well as, to a lesser extent, Ass_Base-U, Ass_am, T_EauP, Ass_Base-R and T_Mort_H. This axis expresses a gradient of territorial disparities : - Countries with positive scores on Dim2 have pronounced urban/rural gaps, illustrating a concentration of services in urban areas. - Negative scores reflect territorial homogeneity, whether in wealth or poverty. The presence of T_Mort_H on this axis indicates that strong spatial inequalities are often accompanied by increased health vulnerability, particularly in countries where rural areas remain under-equipped.
1.2.4. Reading the positions of individuals (countries)
The analysis of the factor coordinates makes it possible to distinguish several coherent profiles of countries according to their situation in terms of sanitation, water and urbanization:
1.2.5. Interpretative synthesis
The ACP highlights two structuring dimensions of country differentiation:
This factor structure
reveals:
- A close correlation between urbanization, sanitation and access to water,
- A second dimension reflecting territorial disparities and health vulnerabilities,
- And an organisation into three country profiles, corresponding to different levels of development and territorial cohesion. Based on the factor coordinates from this PCA, a Hierarchical Ascending Classification (HFC) was carried out in order to group countries with similar health and urban development profiles. This step allows us to structure the typological reading of the observed scatter plot on the factorial level.
1.3. Results of the Hierarchical Ascending Classification (CAH)
The Hierarchical Ascending Classification (HFC) was carried out on the basis of the factor coordinates of the countries on the first two axes of the PCA. This method aims to group individuals with similar profiles in terms of health development, access to water and sanitation, and level of urbanization. The aim is to translate the factor continuity observed in the ACP into a structured typology of countries, allowing for a more synthetic and comparative reading.
1.3.1. Formation of classes and choice of the number of groups
The classification was carried out according to the Ward method, which minimizes within-group variance and maximizes inter-group variance. The analysis of the dendrogram shows a clear break in the aggregation distance at three levels, which justifies the choice of a partition into three classes.
The three groups obtained correspond to distinct profiles of health development, directly consistent with the factor structure highlighted by the CAP.
1.3.2. Description of the identified groups
Cluster 1 – Countries with a low level of health development and equipment Countries concerned: individuals 4, 1 and 7 (Ethiopia, Burkina Faso, Niger)This first group includes countries characterized by: - Low urbanization, - Very low rates of access to basic and improved sanitation, - A marked delay in drinking water coverage, - And significant urban/rural gaps.
These countries are in the negative quadrant on Dim1 and positive on Dim2 of the factorial plan. They illustrate the disadvantaged pole of the development gradient highlighted by the ACP.
This cluster represents countries where sanitation and water deficits are structural, accentuated by urbanization that is still in its infancy.
Cluster 2 – Middle-Developed Countries and High Internal Disparities
Countries concerned: individuals 2 and 9 (Côte d’Ivoire, Senegal)This second group is made up of countries with:
- A medium level of urbanization and access to services,
- But marked inequalities between urban and rural areas. These countries occupy a position centred on Dim1 and positive on Dim2, reflecting a situation of transition : urban progress does not yet benefit the whole territory equitably.
This group illustrates countries in a phase of rapid urban transition, where infrastructures are developed without spatial homogeneity, reinforcing internal contrasts.
Cluster 3 – Countries with a good level of infrastructure and advanced urbanization
Countries concerned: individuals 6, 8, 3, 5 and 10 (Kenya, Nigeria, Democratic Republic of Congo, Ghana, Uganda)This third group is on the positive side of Dim1 and includes countries with:
- A high level of urbanization,
- Good sanitation coverage (basic and improved),
- Widespread access to drinking water,
- And smaller territorial disparities.
These countries represent the most advanced pole in the health and urban development gradient. Their profile reflects controlled urbanization and a better distribution of infrastructure, particularly in urban areas.
This cluster is the reference pole for health and urban development in sub-Saharan Africa.
1.3.3. Visualization and Coherence of Groups in the Factorial Scheme
The projection of the groups on the factorial level (Dim1–Dim2) confirms the internal coherence of each cluster: - Cluster 1 is located in the negative zone of the first axis, corresponding to countries lagging behind in terms of infrastructure, - Cluster 2 occupies a central to positive position on Dim2, associated with strong internal disparities, - While cluster 3 is grouped on the positive side of Dim1, forming the pole of the best-equipped countries.
This graphic coherence confirms the complementarity between PCA and HFA : the typology obtained faithfully reflects the underlying factor structure.
1.3.4. General interpretation
The CAH allows us to identify a hierarchical reading of the health and urban development of the countries studied:
This typology highlights:
- The existence of a gradient in health development consistent with that observed in PCA;
- The correlation between urbanization and improved sanitation ;
- But also the persistence of territorial inequalities in countries in transition.
Thus, the ACP-CAH combination makes it possible to articulate the continuous vision of development (factorial axis) and the discrete vision of national profiles (typological groups).
Following this factorial and hierarchical typology, linear regression analyses were performed to empirically test the relationships identified :(1) the effect of urbanization on sanitation, (2) the impact of urbanization on spatial inequalities, and (3) the relationship between sanitation, urbanization and mortality. These models aim to verify the statistical validity of the gradients interpreted previously.
- Econometric analysis: validation of hypotheses
Following factor analyses and hierarchical classification, linear regressions were performed to empirically test the relationships highlighted in the previous sections. These models quantify the effect of urbanization on access to sanitation, assess the influence of urbanization on urban/rural inequalities, and examine the relationship between sanitation, urbanization, and mortality. Regressions were performed from the average values per country, and linearity tests confirmed that the relationships studied could be modelled linearly.
2.1. Effect of urbanisation on access to sanitation
The first model examines the relationship between the urbanization rate (T_Urba) and access to basic sanitation (Ass_base):
Ass_base = b₀ + b₁ × T_Urba + e
The results indicate a positive and significant coefficient of β₁ = +0.7274 (p = 0.015), with an R² = 0.54. The overall model is significant (F = 9.50; p = 0.015), and the linearity test confirms that a linear relationship is sufficient (p_quad = 0.44). This equation suggests that a one-percentage-point increase in the urbanization rate leads to an average 0.73-point increase in the rate of access to basic sanitation. In other words, the more urbanized a country is, the better the population has health coverage.
This model shows a direct and proportional link between urban development and sanitation infrastructure.
It reflects the driving role of urbanization in improving sanitary conditions and confirms the first research hypothesis.
2.2. Urbanization and urban/rural disparities
The second model analyses the influence of urbanisation on the gaps in access to sanitation between urban and rural areas (Ecart_UR):
Ecart_UR = b₀ + b₁ × T_Urba + e
The coefficient obtained (β₁ = +0.1125; p = 0.75) is not significant, and the model has an R² almost zero (0.01). The quadratic model does not provide any improvement (p = 0.42), which confirms a linear but not explanatory relationship.
These results show that the level of urbanization is not sufficient to explain the spatial disparities in access to sanitation. More urbanized countries do not necessarily have smaller (or larger) urban-rural gaps.
Urbanization, when it is rapid but unplanned, does not guarantee territorial homogeneity of services. Planning policies, rural investment and local governance are likely to be key drivers of these disparities.
2.3. Sanitation, urbanization and mortality
The third model aims to understand the relationship between levels of sanitation and urbanization on the one hand, and mortality due to polluted water sources (T_Mort_H) on the other. The estimated multiple model is of the form:
T_Mort_H = β₀ + β₁ × Ass_Base_U + β₂ × T_Urba + β₃ × T_EauP + ε
The results show that: - β₁ (Ass_Base_U) = +0,07 (p = 0,34) - β₂ (T_Urba) = –0.056 (p = 0.46) -β₃ (T_EauP) = –0.079 (p = 0.21) - R² = 0.33, but the overall model is not significant (p = 0.45).
Although not significant, the negative coefficients of T_Urba and T_EauP indicate a logical trend : countries with the most urbanized and better drinking water supplies tend to have lower mortality rates. However, the low statistical significance is explained by:
- Limited sample size (10 countries),
- Significant structural differences between countries,
- And the multifactorial complexity of the determinants of mortality.
2.4. Synthesis of regression results
2.5. Interpretative discussion
These results complement and confirm the findings of the ACP and the CAH:
Urbanization is a major lever for improving access to sanitation (Model 1), which corresponds to the main gradient (Dim1) identified in the PCA.
However, this urbanization does not ensure a reduction in territorial disparities (model 2), which is in line with the second dimension (Dim2) of internal inequalities. Finally, although mortality tends to decrease with better water and sanitation coverage, the relationship remains statistically fragile (Model 3), suggesting the need to include other contextual variables (income, health, education).
In sum, regression analyses confirm that rapid urbanization has a positive effect on health facilities, but does not eliminate internal inequalities or guarantee an automatic improvement in public health. These dynamics reflect the complexity of urban development trajectories in sub-Saharan Africa.
- Integrated discussion
3.1. Global perspective
The results obtained through all statistical analyses – ACP, CAH and linear regressions – offer a structured view of the interrelationships between urbanization, sanitation and health vulnerabilities in sub-Saharan Africa. The ACP reveals two major dimensions:(1) a socio-health development gradient dominated by access to sanitation, drinking water and the level of urbanization ;(2) a gradient revealing internal disparities between urban and rural areas.
This reading is in line with the conclusions of Dagno, Cissé & Koné (2025) [2] and Armah et al. (2018) [10], for whom urbanisation generally accompanies the improvement of WASH infrastructure, while reinforcing territorial inequalities when facilities remain concentrated in urban centres to the detriment of peripheral areas.
The typology resulting from the CAH transforms this continuity into three groups of countries:
- Weakly developed countries with low health coverage;
- Intermediate countries, marked by rapid but uneven urbanization;
- Better equipped countries, characterized by advanced urbanization and high health coverage.
This typology reflects the trajectories highlighted in the work of Zerbo, Castro Delgado & Arcos González (2021) [18] and Mombo & Edou (2007), [3] which show that urban development can support access to sanitation, but also generates access imbalances affecting water quality and health.
Linear regressions confirm the positive effect of urbanization on access to sanitation, but also point to the absence of a significant effect on the reduction of territorial inequalities. These results support the idea that urban growth is a driver of improved health infrastructure, but does not guarantee equitable delivery of services (Armah et al., 2018) [10].
Finally, the relationship between sanitation, urbanization and water mortality remains weak, revealing the multiplicity of determinants of health (Kuitcha et al., 2016) [19]. Thus, the effects of urbanization are ambivalent: it stimulates health modernization, but also contributes to new vulnerabilities when waste water treatment systems remain inadequate.
3.2. Answering the research questions
has. Urbanization and access to sanitationThe analyses demonstrate a positive and significant relationship between urbanization and access to sanitation. The most urbanized countries have the best access rates, confirming the findings of Armah et al. (2018) and Dagno et al. (2025) [2], [10]. This dynamic reflects the cumulative effect of urban investment and the concentration of services. However, this progress primarily benefits formal and central areas, as observed by Mombo & Edou (2007) [3].
b. Urbanization and urban–rural disparitiesThe link between urbanization and the reduction of urban–rural disparities is not significant. Rural areas remain under-equipped, confirming the observations of Zerbo et al. (2021) [20]. Thus, urbanization appears to be a driver of urban development rather than a means of territorial convergence.
c. Sanitation, urbanization and water mortalityDespite a negative trend between sanitation and water mortality, the relationship is not statistically significant. This observation confirms that sanitation is a necessary but insufficient condition for reducing mortality, which also depends on socio-economic factors, access to care, education and pollution [6], [19].
d. Identification of lagging countriesThe CAH makes it possible to identify countries characterized by rapid urbanization but insufficient infrastructure. This configuration overlaps with the countries of the intermediate group and refers to the trajectories described by Mombo & Edou (2007) [3] as well as environmental and social tensions related to unplanned growth
3.3. Thematic interpretation
All the results reveal the dual nature of urbanization : - a driver of health modernization; - potential factor of inequalities and environmental pressures. Urbanized countries benefit from better sanitation and drinking water coverage, consistent with the analyses of Armah et al. (2018). However, rural and peri-urban areas remain marginalized, reproducing spatial inequalities.
The clusters identified show that the most problematic configuration is that of countries in rapid urban transition, where demographic pressure is not absorbed by sufficient infrastructure capacity [18]. This imbalance promotes the discharge of untreated wastewater into natural environments, increasing pollution and limiting the positive health impact of WASH systems [21].
Ultimately, urban growth can produce dynamic spaces, but also very vulnerable spaces when environmental consideration is insufficient. The results suggest that health progress cannot be assessed solely by access to services, but must include ecological wastewater management.
3.4. Health and environmental implications
The results highlight a strong relationship between sanitation, environmental quality and public health. Better sanitation tends to reduce water mortality, but the lack of adequate wastewater treatment partially counteracts this effect [6], [19].
Accelerated urbanization is increasing the volumes of domestic and industrial effluents, while treatment capacities remain limited [21]. This imbalance leads to increasing microbiological and chemical pollution, creating a high health risk.
The most vulnerable populations are those living in informal and peri-urban areas, where spatial and social precariousness is combined with environmental exposure. These findings call for an integrated approach to urban management that combines:
- equitable sanitation coverage;
- systematic wastewater treatment;
- WASH policies adapted to local socio-economic realities;
- Strengthened environmental governance.
3.5. Scope and limitations
This study has a high analytical robustness, thanks to the coherent articulation between PCA, HFC and regressions. This triangulation reinforces the credibility of the interpretations, by showing the convergence between the descriptive and explanatory dimensions.
Nevertheless, several limitations must be highlighted:
the small sample reduces the statistical power of the regressions;
the use of national averages masks infra-territorial dynamics;
the absence of direct environmental data limits the analysis of the link between pollution and urbanization;
Socio-institutional factors (income, governance, financing) were not included. These limits open up perspectives:
analyses longitudinales des trajectoires WASH ;
integration of environmental data (physico-chemical parameters);
multi-level models to articulate local/national scales.
To conclude this section, the analyses show that rapid urbanization is an ambivalent process that stimulates access to sanitation, but reinforces territorial inequalities and environmental pressure. Improving sanitation does not guarantee a reduction in water mortality in the absence of effective waste water management and appropriate environmental policies.
This study therefore confirms the need for planned, inclusive and environmentally sustainable urbanization.
PART IV : RECOMMENDATIONS
In view of the results obtained, several priority areas of action can be proposed in order to improve the link between urbanization, sanitation and sustainable water management in sub-Saharan Africa.
- Strengthening integrated urban planning
- Promote master plans for development integrating sanitation and wastewater management.
- Encourage the development of compact cities that limit urban sprawl and facilitate infrastructure access.
- Ensure coordination between public actors, private operators and local communities.
- Expand and upgrade sanitation infrastructure
- Prioritise investment in collective sewerage networks and treatment plants.
- Promote alternative solutions (controlled on-site sanitation, semi-collective systems) adapted to unserved areas.
- Guarantee the regular maintenance of infrastructures to ensure their full efficiency.
- Reduce territorial disparities
- Deploy programs targeting rural, peri-urban and informal areas, where access deficits are most pronounced.
- Subsidize low-cost sanitation solutions for vulnerable households.
- Develop equitable financing mechanisms to reduce inequalities in access.
- Improving wastewater management and treatment
- Implement strict regulations regarding the discharge of domestic and industrial wastewater.
- Invest in treatment technologies adapted to local contexts.
- Encourage initiatives for the reuse of treated wastewater for agricultural or industrial purposes.
- Integrating health issues into water and sanitation policies
- Strengthen the sanitary monitoring of drinking water and surface water.
- Develop awareness campaigns on the risks associated with polluted water.
- Establish rapid response mechanisms in the event of waterborne epidemics.
- Promoting environmental and participatory governance
- Encourage the participation of local communities in the design and management of infrastructure.
- Strengthen transparency and accountability in public water and sanitation policies.
- Establish monitoring and evaluation systems based on clear indicators (water quality, health coverage, mortality, etc.).
- Strengthening data collection and applied research
- Develop national and regional data systems on sanitation, water quality and environmental health.
- Encourage interdisciplinary research linking urbanization, environment and health.
- Facilitate the dissemination of data to institutional and operational actors.
To reap the full benefits of urban growth while preserving health and the environment, sub-Saharan African countries need to invest in adequate sanitation infrastructure, reduce territorial inequalities, and strengthen water governance. Sustainable urbanization cannot be envisaged without integrated water resources management, rooted in equity, citizen participation and ecological resilience.
GENERAL CONCLUSION
The objective of this report was to examine the relationships between rapid urbanization, sanitation and pollution of water sources in sub-Saharan Africa, as well as the resulting socio-health implications. In a context of sustained population growth and accelerated urban expansion, understanding these interactions is crucial to orient public policies towards sustainable, equitable and health-protective development.
All the analyses carried out — Principal Component Analysis (PCA), Hierarchical Ascending Classification (HFA) and linear regressions — have made it possible to identify several major lessons. First, it appears that urbanization is an important driver for improving access to sanitation infrastructure and drinking water. The most urbanized countries appear on average to be better equipped, a sign that the concentration of investment and services in urban centres favours the modernisation of essential facilities.
However, this dynamic comes with significant limitations. Territorial disparities remain very marked: rural and peri-urban areas remain on the margins of health progress, with persistent deficits in access to sanitation. These inequalities are reflected in the results of the ACP and the CAH, which highlighted a structuring of countries around socio-health and spatial gradients. Some countries are characterized by rapid urbanization without commensurate improvements in services, highlighting a risk of desynchronization between urban growth and infrastructure.
The relationship between sanitation, urbanization and mortality related to waterborne diseases appears weak and insignificant, revealing the multifactorial complexity of the determinants of health. While access to sanitation is a necessary condition for health protection, it is not sufficient on its own: other factors, such as the quality of infrastructure, effluent management, the functioning of the health system and socio-economic conditions, play a decisive role. Thus, even when access to services is nominally assured, the lack of wastewater treatment and uncontrolled discharges contribute to the pollution of water resources, perpetuating health risks.
Beyond statistical analysis, this work highlights the need for an integrated approach to urban development. It is not only a question of increasing coverage rates, but of ensuring sustainable and inclusive management of water resources and infrastructure. Unplanned urbanization can exacerbate environmental and social vulnerabilities, while structured territorial governance can transform urban growth into a real lever for sustainability.
However, this report has limitations, in particular the small size of the corpus of countries studied, the use of national average values that mask infra-territorial disparities, and the absence of direct environmental data on the physico-chemical quality of water. These constraints open up future research perspectives, including the integration of longitudinal approaches, finer environmental data and multi-scale models.
Ultimately, this study confirms that the urbanization, sanitation and water pollution triptych is a central issue for sub-Saharan Africa. Improving environmental health and reducing waterborne diseases requires controlled urbanization, equitable expansion of sanitation services, and rigorous waste water management. Only such an approach will ensure a sustainable and resilient urban future that can ensure the health and well-being of people.
ANNEX
1- Collection tools
Household Survey Questionnaire
«https://ee.kobotoolbox.org/x/E74ajZoY»
Interview Guide for Health and Facilities
«https://ee.kobotoolbox.org/x/veYvIS5b»
Expert questionnaire fo Researchers and scientists
«https://ee.kobotoolbox.org/x/c7wELdKa»
Interview for NGOs and Organization
«https://ee.kobotoolbox.org/x/9uxfIxiG»
2- Descriptive maps
3- Analytical maps
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