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Members of the jury

 Dr Maïmouna BOLOGO/TRAORE  Dr. Malicki ZOROM  Dr Yohan RICHARDSON  Mr Sina THIAM

General Summary

This project focuses on the disparities in access to drinking water in West Africa, a region facing major challenges related to the availability, quality and accessibility of the resource. Using data from reliable international databases, the study aims to understand the factors that explain the differences observed between countries, as well as between urban and rural areas. The project is based on a central issue related to inequalities in access to drinking water and formulates several research questions to examine the demographic, socio-economic and territorial dimensions associated with these disparities. The overall objective is to produce a scientific analysis to identify the main determinants of access to drinking water and to propose relevant courses of action for decision-makers. The work includes the construction of an adapted database, the selection of relevant variables, the review of the literature on water issues in West Africa, as well as the implementation of a rigorous methodological approach to answer the research questions formulated. At the end of the project, recommendations will be proposed to contribute to the sustainable improvement of access to drinking water in the region.

I. INTRODUCTION

Access to safe drinking water remains a major challenge in West Africa, where strong inequalities persist between countries and between urban and rural areas. These disparities can be explained by socio-economic, demographic and environmental factors that limit the availability and quality of water service for the population.

This work aims to analyze these inequalities using reliable data from several countries in the region, in order to better understand the factors that influence access to drinking water and to propose ways for improvement for decision-makers.

1.1 General context of the study

Drinking water occupies an important place in human life. It is involved in all the fundamental aspects of development, including public health, agriculture, education, economic activities and the preservation of ecosystems. Access to quality water is also one of the Sustainable Development Goals (SDGs), in particular SDG 6, which aims to “ensure access to drinking water and sanitation for all” by 2030. Yet, despite its vital importance, equitable and sustainable access to safe drinking water remains a major challenge for many parts of the world, particularly in sub-Saharan Africa.
However, in West Africa, the situation is particularly worrying due to a combination of structural, demographic, climatic and socio-economic constraints. The region is experiencing one of the highest population growth rates in the world, which is increasing the pressure on the already inadequate water infrastructure. Rapid, often unplanned, urbanization further complicates the ability of states to provide safe drinking water services to urban populations, while rural areas remain largely disadvantaged. In addition, the effects of climate change are altering the availability of water resources, exacerbating droughts, reducing river flows and disrupting the natural recharge of groundwater. The contrast is even more marked between Sahelian countries — such as Burkina Faso, Niger, Mali or Chad — and coastal countries — such as Ghana, Benin, Côte d’Ivoire or Senegal — which generally benefit from a wetter climate and more abundant water resources. However, even in countries with relatively better resources, internal disparities between urban and rural areas persist. This observation fully justifies the scientific study of the disparities in drinking water supply in the region. The choice of the theme “Clean Water” is therefore part of a strategic perspective: to understand the determinants of access to drinking water in West Africa, to identify inequalities, and to propose ways of improving it adapted to the socio-economic and environmental realities of this region.

1.2 Problematic

Countries in the Sahel, faced with water scarcity, climate variability and limited infrastructure, have significantly lower rates of access than coastal countries with more rainfall and more developed water networks. At the same time, poverty, accelerated population growth, insufficient public investment, poor governance of water services and uncontrolled urbanization are amplifying supply difficulties. This situation raises several major questions: what are the real determinants of disparities?; How do they evolve from one country to another? And to what extent do socio-economic, environmental and demographic characteristics explain the observed differences?

1.3 Research questions

Based on these observations, this study is structured around the following research questions:  What are the main factors explaining the levels of access to drinking water in West African countries?  Do Sahelian countries have a significant structural disadvantage compared to coastal countries in terms of access to drinking water?  To what extent do poverty, urbanization, the Human Development Index (HDI) and population growth influence the disparities observed?  Are there profiles or groups of countries sharing similar characteristics of access to drinking water? These questions guide the analytical, statistical and cartographic approach of the study.

1.4 Research Hypotheses

To answer the previous questions, the study is based on three main hypotheses:  H1: Sahelian countries have significantly lower levels of access to drinking water than coastal countries, due to their semi-arid climate and the scarcity of water resources.

 H2: Socio-economic variables such as urbanization, HDI and poverty rate significantly influence access to drinking water.

 H3: It is possible to group West African countries into homogeneous classes according to profiles of access to drinking water, revealed by multivariate analysis methods (ACP, CAH).

1.5 Research objectives

• General objective To thoroughly analyze the disparities in access to drinking water in West Africa, taking into account the socio-economic, demographic, climatic and environmental factors that influence them.

• Specific objectives

II. LITERATURE REVIEW

2.1 Conceptual framework

 Definitions:

•Drinking water: Drinking water is defined as water that is fit for human consumption, free of pathogenic chemicals, parasites or microorganisms, and meets the quality standards set by the World Health Organization [1].

• Improved sources: Improved water supplies are infrastructure that is protected from external contamination, including pumped boreholes, protected wells, distribution systems, engineered springs and stormwater harvesting systems [2].

• Urbanization in West Africa: West Africa is experiencing rapid urbanization that is putting a lot of pressure on water infrastructure. This urban growth leads to the expansion of unplanned neighbourhoods where access to drinking water services remains limited [3].

• Poverty and access to water: Poverty is a major determinant of access to safe drinking water. Low-income households often live in areas without a network and sometimes pay more for water through informal vendors, often for water of uncertain quality [4] [4].

• Human Development Index (HDI): The HDI reflects the level of human development according to health, education and income. West African countries generally have a low HDI, partly as a result of a lack of access to safe drinking water and adequate hygiene services [5].

❖ Link between human development and access to safe drinking water

The link between human development and access to safe drinking water is particularly strong in the West African region:

Unequal access: Many rural areas still rely on unprotected sources, which deteriorates health, reduces productivity and exacerbates social inequalities [6].

Waterborne diseases: The lack of drinking water promotes diseases such as cholera, typhoid or acute diarrhoea, major compromises in children’s health and life expectancy [7].

Time burden: In several Sahelian countries, women and children travel several kilometres every day to collect water, which limits schooling and economic activities [8].

Impoverishment: The lack of drinking water leads to additional expenditure on purchased water or medical care, reinforcing structural poverty [9].

Impact on HDI: Countries with the lowest rates of access to water also have low HDIs, demonstrating a direct link between access to water, health, education and income [5].

2.2 Previous studies on access to water

The literature shows that access to safe drinking water is influenced by a combination of physical, economic, social and institutional factors.

According to the World Bank (2022), inequalities in water distribution in sub-Saharan Africa can be explained by inadequate infrastructure, rapid population growth, poverty, and the effects of climate change [10].

The work of Bartram and Cairncross (2010) and Hunter et al. (2010) has shown that improving access to safe drinking water drastically reduces waterborne diseases [11]. For its part, UN-Water (2021) emphasizes the role of governance and integrated water resources management (IWRM) in reducing regional disparities [12].

In West Africa:

Soro et al. (2018) show that unequal investment between cities and rural areas accentuates access gaps [13].

Kinda and Sanou (2020) link water scarcity in Sahelian countries to climate variability and inadequate infrastructure [14].

This work converges: Access to water is as much a socio-economic issue as it is a question of the physical availability of the resource.

World Bank data show that more than 80% of urban dwellers have basic water service, compared to less than 60% of rural dwellers, confirming the depth of geographical inequalities.

There are also significant differences between coastal countries (Côte d’Ivoire, Ghana, Senegal) and Sahelian countries (Burkina Faso, Mali, Niger), where climatic conditions and economic constraints reinforce access difficulties [15].

2.3. Geographical and climatic context of West Africa

West Africa is structured around two major climatic groups:

• Sahelian zone (Burkina Faso, Mali, Niger) This area is characterized by: a semi-arid climate, low rainfall (200–600 mm/year), strong evaporation, recurrent droughts.

These conditions limit surface water resources and make people dependent on groundwater that is difficult to access [16].

• Coastal zone (Côte d’Ivoire, Ghana, Benin, Togo, Guinea, southern Nigeria)

This area benefits from higher rainfall (> 1,000 mm/year). However:  rapid urbanization,  resource pollution,  aging networks,  spontaneous neighbourhoods,

limit access to drinking water despite the abundance of the resource.

III. METHODOLOGY

3.1. Type and approach of research

Quantitative approach at the multi-country scale. Use of statistical and spatial methods for analysis.

3.2 Tools and software used

R for statistical analyses:

− FactoMineR and factoextra for Principal Component Analysis (PCA) − ggplot2 for visualizing relationships between variables; − corrplot for the correlation matrix; − dendextend for hierarchical classification (dendrogram).

• Excel for data preprocessing • QGIS for mapping and spatializing results • Zotero for bibliographic reference management • KoboToolBox for Questionnaire Generation

These tools made it possible to represent disparities in access to drinking water and to highlight the groupings of countries according to their characteristics.

3.3. Selection and description of variables and mapping of results

Target population

The target population of this study is households living in West African countries, both urban and rural. This choice can be explained by the fact that households represent the most relevant unit for analysing the real conditions of access to drinking water, since they are directly confronted with constraints related to the availability, quality, cost and continuity of the service. Disparities in access are observed primarily at the level of families, who are the first users and beneficiaries — or victims — of water supply policies. The choice to include both urban and rural areas is also based on the large differences observed between these two environments. Urban areas often benefit from more developed infrastructure, while rural areas remain heavily dependent on unimproved or remote sources, exacerbating internal inequalities within countries. The study of this diversity allows us to fully grasp the dynamics of inequality and to better understand the factors that influence access to drinking water. Thus, by targeting households in West African countries, the study adopts an end-user-centric approach, ensuring better relevance of the results and recommendations made to improve equitable access to drinking water in the region. The quantitative variables used come from the Our World in Data database and the World Bank website, and they concern several dimensions: demographic, economic and water. The sample consists of the 15 countries of West Africa. This choice is based on an exhaustive regional sampling, i.e. all the countries in the area have been included in order to obtain a global and representative view of the disparities. This approach makes it possible to compare two main sets:

 Sahelian countries (Burkina Faso, Mali, Niger);  Coastal countries (Côte d’Ivoire, Ghana, Togo, Benin, Liberia, Sierra Leone, etc.).

 Demographic variables

These variables measure the population dynamics that put pressure on infrastructure and define the context of the study (rural/urban).

 Economic and Development Variables

These variables serve as proxies for wealth, well-being, and the ability of states to provide sustainable public services.

 Water Access Variables

These variables are at the heart of the study. They measure the level and nature of access, as well as the extent of exclusion.

 Outcome mapping

• Human Development Index (HDI) in West Africa

The HDI is a composite indicator measuring health, education and living standards. The map reveals a strong disparity, with a North-South gradient:

• Population growth rate in West Africa

Population growth is a key factor in development and the pressure on resources.

• Populations Without Improved Water Source

This map highlights gaps in access to clean water. - High lack of access (23.3 - 32%): The most critical situation (in blue) is in Niger, Benin, Sierra Leone and also in Guinea Bissau. This indicates that a very large proportion of the population does not have access to a water source that is considered to be improved.

• Populations using a Basic Drinking Water Source

This map is a complement to the previous one, showing the success of access efforts. - Average rate (62 - 75% ): Guinea, Sierra Leone, Liberia, Côte d’Ivoire, Benin and Togo are in the average (in light green).

• Populations Using Improved Water Source in Urban Areas

It focuses solely on the urban environment. - Low rate (58 - 72%): Only Mauritania has the lowest rate for urban areas (in green red).

• Poverty Rates in West Africa This map reflects the economic and social challenges.

• Populations Using an Improved Water Source in Rural Areas

It focuses solely on rural areas. - Low rate (44 - 57%): Nigeria, Niger, Togo, Sierra Leone and Mauritania have the lowest rates for rural areas.

• Urbanization Rates in West Africa

Urbanization is a driver of societal transformation.

In summary, there is a marked contrast between Sahelian countries (North), which generally have lower socio-economic indicators (low HDI, low access to drinking water, high poverty, high population growth), and coastal countries (South), particularly along the Gulf of Guinea, which tend to have more favourable indicators

Data

3.4. Data collection tools (theoretical)

As part of this project, several tools have been mobilized to collect reliable and relevant data:

Link to the questionnaire: https://ee.kobotoolbox.org/i/et2XtZ76, Login ID: lailatou7071 Password:

3.5. Management of missing data

During data collection and analysis, it is common to encounter missing values. These absences may be the result of a refusal to respond, an input error, or an oversight by the interviewer. It is therefore essential to identify and process them correctly in order to ensure the reliability of the results. There are several methods for managing missing data, including: • The method of identification:

Identifying missing data is the process of identifying missing or abnormal values in the data. This can be done manually (by visually browsing through the tables), or automatically using software such as Excel, which can detect empty or invalid cells. The percentage of missing data for each variable can also be calculated to decide how to deal with it.

• The treatment method (Imputation by the mean):

Mean imputation consists of replacing a missing value with the average of the valid responses of the same variable.

IV. Introduction to Principal Component Analysis

Principal Component Analysis (PCA) is a statistical method used to reduce the size of a dataset while retaining most of the information. It allows a large number of correlated variables to be transformed into a smaller number of new variables called principal components, which best summarize the variability of the initial data. PCA makes it easier to visualize, interpret, and compare observations.

4.1. Contact details, contribution and quality of representation

4.2. Correlation Circle (PCA)

The correlation circle allows to analyze the contribution and relationships between the variables retained in the Principal Component Analysis (PCA). The first two axes account for 70.8% of the total variance (Dim.1 = 52.7%; Dim.2 = 18.1%), which means that the majority of the information contained in the variables is well represented in this factorial design.

Interpretation of axis 1: a gradient of development and access to drinking water

 Axis 1 clearly opposes two groups of variables.

On the one hand, the variables positively correlated with Dim.1:

• Pop_basic_source: proportion of the population with access to at least one basic source of drinking water; • Pop_improv_rural: access to an improved source in rural areas; • Urbanization: rate of urbanization; • Human_Dev_Indx: Human Development Index.

These variables reflect favourable conditions in terms of access to water services and a better socio-economic level. They direct the axis towards countries that are relatively more developed or have more efficient water infrastructure. On the other hand, variables negatively correlated with Dim.1: • Pop_not_improv_source: proportion of the population using an unimproved water source; • Pop_Growth: population growth. These variables characterize countries where access to drinking water remains limited and where demographic pressure increases access difficulties.

Thus, axis 1 represents a gradient in development and access to drinking water, distinguishing:

• on the right, countries that are more urbanized and better equipped with drinking water infrastructure; • on the left, the most vulnerable countries, with limited access and high population growth.

 Interpretation of axis 2: internal disparities and the burden of poverty

Axis 2 mainly distinguishes the variables:

• Pop_improv_urban (positive correlation), indicating a good performance of improved access to water in urban areas; • Poverty, also strongly positively correlated with Dim.2.

This association suggests that some countries have better access to urban areas despite high levels of poverty, highlighting significant disparities between urban and rural areas. Axis 2 therefore reflects internal contrasts linked to socio-economic inequalities. Thus, axis 2 mainly represents urban-rural disparities as well as the structuring role of poverty in access to drinking water.

 Relationships between variables

The correlation circle also allows us to analyze the proximity between the arrows:

• The variables Pop_basic_source, Pop_improv_rural, Urbanization, and Human_Dev_Indx are grouped together and oriented in the same direction: This shows that better human development and greater urbanization are accompanied by better access to drinking water, even in rural areas.

• Conversely, Pop_not_improv_source is almost the opposite: the least developed or least urbanized countries remain those where the use of unimproved water sources is the highest.

• The Poverty variable, although associated with improved urban access, highlights that some urban infrastructure can perform well even in countries where poverty remains high, highlighting the presence of strong internal inequalities.

The correlation circle analysis reveals that access to drinking water in the countries studied depends mainly on: - The level of human development, - The degree of urbanization, - Disparities between urban and rural areas, - The weight of poverty in the structuring of essential services.

Axis 1 reflects a gradient of development and vulnerability, while axis 2 highlights internal disparities and socio-economic inequalities. These results confirm that the challenges of access to drinking water in West Africa are multidimensional, combining socio-economic, demographic and geographical factors.

4.3. Factor Structure and Selected Axes (Scree Plot and Contributions)

 Percentage of Variance Explained (Scree Plot)

Dim. 1 explains 52.7% of the variance.
Dim. 2 explains 18.1% of the variance.
The factorial design (Sun. 1 and Sun. 2) explains a cumulative total of 70.8% of the information. This percentage is excellent and fully justifies the retention of these two axes for interpretation.

 Definition of Axis 1

Axis 1 is the main axis of the ACP, structured by a strong opposition: - Positive Pole (Development): The variables Urbanization (the most contributing, about 20%) and Pop_basic_source, Human_Dev_Indx (HDI).

 Definition of Axis 2

Axis 2 is mainly defined by access to quality water:
- Positive Pole (Quality): The variables Pop_improv_urban (the most contributing, nearly 50%) and Pop_improv_rural are strongly positively correlated with the axis.

4.4. Correlation matrix

The correlation matrix confirms the relationships between variables prior to PCA.

The values of the correlation coefficients range from -1 to 1 with: • 1 which indicates a perfect positive correlation (thus a strong relationship between the variables concerned) • -1 which indicates a perfect negative correlation (a strong inverse relationship between the variables concerned) • 0 which indicates that there is no correlation ( No direct link between variables )

Development Variables (Urbanization, HDI)

 Urbanization

 Human_Dev_Indx (HDI)

Service Access Variables (Pop_basic_source, Pop_improv…)

 Pop_basic_source

 Pop_improv_urban

Deprivation variables (Poverty, Pop_not_improv_source, Pop_Growth)

 Pop_not_improv_source (Population not using an improved source)

4.5. Representation of Individuals

The graph of individuals by color indicates how reliable and well explained a country’s position is by your overall analysis.

 The countries with the clearest and most reliable profiles (red/orange color)

Their characteristics are very different from the others, and this difference is perfectly captured by the graph. - Niger (3): Its position is the most reliable (dark red). This confirms that Niger is the country most strongly and clearly associated with the pole of poverty and low access to services. - Ghana (8) and Gambia (13): Their position is also very reliable (dark red). They represent the opposite pole: that of Development (Urbanization, HDI) and better access to services. - Mauritania (11): His position is very reliable. It is isolated from the others, which confirms that Mauritania is the most atypical country in the sample, with unique specificities.

 Countries with medium or mixed profiles (green/blue)

These countries are in the centre of the graph. Their characteristics compensate for each other, and the two main axes of our analysis are not sufficient to explain all their specificities. Mali (2), Benin (4), Côte d’Ivoire (5), Togo (6), Sierra Leone (7), Nigeria (9), Liberia (14), and Guinea (15): These countries have low reliability (green or blue color) because they are too close to the center (origin). Their profiles are intermediate or moderate. For example, they are neither the poorest nor the most developed.

4.6. Hierarchical Classification on Principal Components

The Dendrogram of countries is the result of an Ascending Hierarchical Classification (CHA) carried out on the coordinates of the countries from the ACP. This graphical representation makes it possible to visualize the process of grouping individuals and to deduce clusters of countries sharing similar statistical profiles.
The vertical axis, denoted Height, represents the distance (or dissimilarity) between the countries or groups formed. The lower the junction height, the more similar the elements are considered; conversely, a high height indicates a strong dissimilarity.

4.7. Linear regression

Linear regression shows a positive relationship between the rate of urbanization and access to a basic water source. The more urbanized a country is, the higher the proportion of its population with access to a basic water source. The most urbanized countries such as Gambia, Ghana and Nigeria are well above average in terms of access to water, while sparsely urbanized countries such as Niger and Burkina Faso have the lowest levels of access.

This trend confirms that urbanization facilitates the expansion and reliability of drinking water infrastructure, although some countries remain slightly below the general trend due to structural challenges.

4.8. Detection of atypical individuals

During the CPA, some countries were identified as atypical individuals, as their statistical behaviour differed greatly from that of others. Their detection is essential to prevent them from disturbing the construction of factor axes and biasing the general interpretation. The possible withdrawal of these observations makes it possible to obtain a more stable factor structure that is more representative of all the countries studied.

During the exploratory analysis of the data, the graphical representation of individuals in the factor space made it possible to identify two countries that clearly stood out from the rest of the sample: Niger and Mauritania. These two countries appear to be atypical individuals, i.e. they have statistical characteristics that are sufficiently far from the regional average to have a significant influence on the construction of the ACP axes.

Thus, without the atypical individuals, we obtain the following distribution:

In addition, the study area without atypical individuals gives the following representation:

V. CONCLUSION

Access to drinking water remains a major development issue in West Africa, where populations are confronted with strong inequalities in access linked to demographic, socio-economic, infrastructural and climatic factors. The analysis carried out in the framework of this project showed that the disparities are not only the result of the physical availability of the resource, but also of poverty, urbanization, the level of human development and the institutional capacities of States to plan and maintain efficient water infrastructure.

The study revealed a marked contrast between Sahelian countries, characterized by high climate vulnerability and limited access to improved water sources, and coastal countries, which are generally better endowed but where significant urban-rural inequalities persist. Statistical and cartographic analyses have made it possible to identify the most determining factors, to group countries according to their water and socio-economic profiles, and to highlight the existence of atypical countries whose characteristics influence the general structure of the data.

The results obtained converge towards a central conclusion: sustainably improving access to drinking water requires multidimensional interventions, integrating poverty reduction, infrastructure modernization, better governance, and adaptation to climate change. The recommendations of the study are intended to guide decision-makers towards priority actions to reduce internal and regional inequalities, while strengthening the resilience of water systems to future pressures.

Survey

THEME: Disparities in access to drinkink water in West Africa

Section A-General Information

1-Country 2-Region/municipality: 3-Residential setting: 4-Date of the survey:…./…./….. 5-Household Number (Household ID):

Section B- Social Profile Household Demographics

6-Household Size: ☐ 1-3 ☐ 4-6 ☐ 7-10 ☐ >10

7-Gender of the Head of Household:

☐ Masculine ☐ Feminine

8-Level of education of the head of household:

☐ None ☐ Primary ☐ Secondary ☐ Upper 9-Estimated monthly household income:

☐ <50,000 ☐ 50,000 - 100,000 ☐ 100,000 - 200,000 ☐ >200,000

10-Main activities of the head of household:

☐ Agriculture ☐ Commerce ☐ Civil service ☐ Handicraft ☐ Other

C1- Water sources

11-What is your main source of drinking water?

☐ Private Tap at Home ☐ Public faucet ☐ Well protected ☐ Unprotected well ☐ Drilling/Pumping ☐ Surface water (lake, river) ☐ Purchase of water (resellers) ☐ Other

12-Is your main source considered an improved source?

☐ Yes ☐ No ☐ I have no idea

13- Do you have access to a secondary source of water?

☐ Yes ☐ No ☐ If so, what is it?

C2- Availability and continuity

14- Do you have water every day? ☐ Yes ☐ No

15-In the event of a power cut, what is the average duration per day? ☐ < 1 hour ☐ 1 hour - 3 hours ☐ 3 pm – 6 pm ☐ > 6 hours

16-Amount of water available

☐ Sufficient ☐ average ☐ Insufficient

C3- Physical accessibility

17-How far is your water point?

☐ less than 500m ☐ Between 500 m and 1 km ☐ More than 1 km

18- How much time do you spend per day collecting water?

☐ less than 30 min ☐ 30 min to 1 hour ☐ More than 1 hour

19- Who is primarily responsible for water collection?

☐ Adult Woman ☐ Adult Male ☐ Children ☐ Other

C4- Affordability

20-Is there a charge for the water service?

☐ Yes ☐ No ☐ If so, how much do you pay per month?

21- Have you ever reduced your water consumption because of the cost?

☐ Yes ☐ No

Section D - Water Quality and Accessibility

22-Perceived Water Quality

☐ Very good ☐ Good ☐ Acceptable ☐ Bad

23- Have you observed any problems related to water?

☐ Smell ☐ Colour ☐ Taste ☐ Deposits ☐ None

24- Do you treat water before consumption?

☐ Yes ☐ No ☐ Yes, how ?

Section E - Governance and Perception of Service

25-Have you ever reported a water problem to the authorities?

☐ Yes ☐ No

26- Has the problem been solved?

☐ Yes ☐ No

27- General level of satisfaction with the water service

☐ Satisfactory ☐ Unsatisfactory ☐ Unsatisfactory

28- What are the main water-related problems you encounter in your area?

☐ Drinking water source too far away ☐ Cost of access to drinking water too high ☐ Frequent cut-off ☐ Lack of infrastructure ☐ Other

Section F - Household Suggestions

29- What improvements would you like to see in terms of access to water in your locality?

30- Commentary

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