Access to safe drinking water remains a major challenge worldwide. According to the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF), 2.1 billion people worldwide, or one in four, will lack access to safe, monitored drinking water in 2024. In sub-Saharan Africa, women, who are responsible for collecting water, spend more than 30 minutes a day on this task. In Burkina Faso, ensuring safe drinking water is a priority for the authorities. As part of its responsibilities, the Ministry of Environment, Water, and Sanitation (MEEA) is working to ensure sustainable access to this service for the population. The Ministry’s sectoral policy on “Environment, Water and Sanitation” covering the period 2018-2027 incorporates this mission ([17]). The MEEA’s interventions have led to progress in the water sector. The rate of access to drinking water in rural areas has increased from 64.1% in 2014 to 71.3% in 2023 ([16]).

However, this progress remains low compared to the targets set at both national and international levels. Indeed, Sustainable Development Goal (SDG) six aims to achieve “universal and equitable access to water, hygiene and sanitation by 2030, especially for vulnerable populations”. Furthermore, there are socio-economic and regional disparities in terms of access to drinking water in this country. In urban areas, 29.11% of the population has safe managed access, compared to 0.66% in rural areas ([19]). The Central region has the highest proportion of households with safe managed access (44.98%), compared to 0.47% of households in the Sahel ([19]).

Despite investments by the Burkinabe government and partners (WHO, UNICEF, and DANIDA, for example), 16.89% of households still obtain their water from non-potable sources, such as wells, backwaters, surface water, and dams ([19]). Additionally, the average time it takes to reach a drinking water source exceeds the WHO standard of 15 minutes. In fact, this supply time exceeds 15 minutes for 89.54% of households in urban areas and 91.47% of households in rural areas ([19]). In addition, water shortages are also common, with an average of 15.18 days of water supply disruption per year, and a lack of drinking water facilities. Burkina Faso has 58,000 modern water points (PEM), 48,000 boreholes, and 8000 improved wells ([18]) for an estimated population of 20,487,979 ([20]). As a result, 11.73% of the population faces challenges related to the distance (more than 1000 meters) to drinking water supply points and the quality of drinking water ([19]). These issues, combined with the low standard of living of households, particularly in rural areas, may explain the choice of drinking water supply.

Research has analyzed the factors that determine decisions regarding drinking water supply. In this vein, [14] highlighted the role of attributes (factors that characterize demand for drinking water) in households’ choice of water supply. Furthermore, the time required to obtain drinking water is a decisive factor in households’ choice of water supply ([5]). Research has documented the influence of income on the choice of drinking water supply ([2]; [10]; [24]; [26]; [25]). According to studies, the level of education affects household supply decisions ([27]; [29]; [21]). Household size also affects water supply choices ([4]). In addition to the factors mentioned above, other factors determine households’ choice of water sources. This refers to the distance travelled to reach the water source ([6]), cultural and religious values ([21]), and water quality ([23]).

Despite the importance of access to drinking water on household living conditions, very few nationwide studies have focused on the determinants of drinking water supply decisions in Burkina Faso. It is therefore important to analyze the factors likely to affect households’ choice of drinking water supply in this country. This article seeks to answer the following question: What are the main determinants of household drinking water supply choices in Burkina Faso? In other words, it analyses the main determinants of drinking water supply choices among Burkinabe households. The study assumes that: 1) a low household standard of living reduces its chances of accessing an improved water source, 2) a large household size reduces its chances of accessing an improved water source, and 3) a long supply time (or distance) for the household reduces its chances of accessing an improved water source. To explore this topic in depth, the rest of this paper is organized into four parts: 1) a review of the literature, 2) the methodological approach, 3) analysis of the results, and 4) conclusions, followed by proposals for economic policy measures.

Studies have examined the factors that influence decisions regarding drinking water supply. One category of these studies has highlighted the influence of economic factors on water supply decisions. In line with this, the role of income and the costs of accessing drinking water is documented in the literature ([3]; [10]; [24]; [27]; [32]; [22]; [8]). According to this literature, an improvement in income or, overall, in living conditions increases households’ chances of accessing a source of drinking water. However, when the cost of access to water is high, the probability that households will opt for an improved source becomes low. In the municipality of Bantè, for example, [8] found spatial disparities in water infrastructure, with a low water supply rate (41.4%). This disparity is partly due to the financial cost, particularly the payment of compensation for the costs of constructing drinking water facilities. Similarly, wealthier households have greater access to water in both rural and urban areas ([22]). Similarly, the results of [3] revealed a predominance of improved water sources in middle- and high-income residential areas in Lagos (Nigeria). The price of water, the distance between the household and the water source, and the quality of the source are factors in choosing a water source ([10]). In addition, wealthy households and households headed by women are more likely to choose improved public water sources ([10]).

Another category of research has placed greater emphasis on the influence of socio-demographic factors in household drinking water supply decisions ([13]; [12]; [30]; [1]; [7]; [28]; [2]; [27]; [22]; [29]; [8]; [21]; [6]; [4]). These factors include household size, neighbourhood/area of residence, household status (IDP household or not), household culture, level of education, gender, age, and marital status of the head of household. According to this literature, urban households, those in subdivided areas, those headed by women or educated individuals, and those headed by adults are more likely to obtain drinking water from a safe source. However, large households are less likely to obtain drinking water from a safe source. Indeed, household size and composition, access to water sources, wealth, and time spent collecting water are important determinants of water use ([4]). Similarly, female-headed households, households whose head has at least secondary education, urban households, and non-poor households been more likely to have access to improved drinking water sources ([2]). According to the findings of [28], households headed by individuals aged 35 to 54 and 55 were less likely to have access to improved drinking water sources than those headed by younger individuals. In addition, an increase in the number of household members is negatively associated with access to improved drinking water sources ([28]). Furthermore, households in urban areas are more likely to have access to improved drinking water sources than those in rural areas ([28]). The findings of [1] in the context of Punjab also reveal that factors such as the level of education and ethnicity of the head of household determine households’ access to drinking water. [30] concluded that household size and water source influence household access to water and payment for water services. Using survey data from India, [12] found that large urban households belonging to affluent groups, whose head of household is married and uneducated, are more likely to have access to improved drinking water. The findings of [13] also reveal that households residing in urban areas, small households, and female-headed households are strongly associated with better access to improved drinking water. However, IDP households have less access to drinking water. Indeed, insecurity and associated population displacement limit some households’ access to this service. In Burkina Faso, the massive influx of internally displaced persons (IDPs) is putting pressure on existing water points, which were already failing before the crisis ([31]). Similarly, targeted attacks on water points reduce water availability in areas affected by insecurity ([31]). When displaced populations leave their localities, they are no longer equipped to meet their basic water needs ([9]). In addition, climate change is negatively impacting water resources in this country, and the drying up of water sources is reducing water availability, increasing the risk of social tensions ([31]).

Furthermore, studies have focused more on the role of service delivery conditions and household constraints in households’ decision of drinking water supply ([11]; [15]; [28]; [24]; [6]). These governance factors include the distance and/or time required for households to obtain water, the availability of drinking water facilities, and the quality, taste, and smell of the water. Since households must balance the time spent on productive activities with that allocated to domestic work, the time required to collect water can influence their decisions regarding drinking water supply. According to [6], certain household characteristics and distance to water sources influence the choice of water source. In rural areas of Kazakhstan, households use alternative sources due to residents’ doubts about the quality of tap water, habitual use of other sources, and the availability of cheaper or free water sources ([24]). In addition, households have a poor perception of the quality and reliability of water from wells, open sources, and cisterns ([24]). Among urban households in north-western Ethiopia, factors such as the availability of additional facilities, cleanliness, water scarcity, and family size significantly explain households’ access to safe drinking water ([11]).

As part of this study, we estimate a logistic model. The categorical nature of the dependent variable clearly justifies this choice. We used the database from the national survey on water, hygiene, and sanitation in Burkina Faso ([19]). In this section, we document the model specification, model variables, data sources, and statistical results. The model variables are described in Section 3.2 (see Table 1 below).

Despite initiatives undertaken in Burkina Faso to provide drinking water to the entire population, households still have difficulty accessing safe drinking water. This research aimed to highlight the key factors influencing households’ choice of water supply in this country. By estimating a logit model using data collected from a representative sample of Burkinabe households (11,348 households), the study yielded the following main results: socio-economic conditions, socio-demographic factors, and service delivery conditions explain household access to drinking water in this country. Considering these results, the study suggests combining policies to improve people’s incomes, reducing the time spent collecting drinking water, improving water quality, and reducing social inequalities. It is therefore important, among other things, to: 1) Strengthen service provision by constructing additional sustainable drinking water facilities to reduce the distances travelled and the time spent collecting drinking water. 2) Establish a mechanism for targeting interventions in the area of drinking water, giving priority to rural households, poor households, and IDP households, with a view to reducing inequalities. 3) Introduce a tariff policy that is more favorable to rural areas and disadvantaged populations.

a. Summary of estimation results

***p < .01, **p < .05, * p < .1.

b. The ROC Curve

c. The confusion matrix

d. The link test