Benchmarking WASH Trajectories in Africa: A Comparative Assessment of Six Country Archetypes (2000–2022)

Benchmarking WASH Trajectories in Africa: A Comparative Assessment of Six Country Archetypes (2000–2022) https://doi.org/10.5281/zenodo.17676132 Zo Rivomanana Rasoanaivo, University of Antananarivo, ORCID: 0009-0003-0725-3764 Abstract Access to safe drinking water and sanitation remains one of the most uneven development trajectories across Africa. While policy debates frequently highlight investment gaps or institutional fragmentation, few studies provide a cross-country comparative analysis grounded in long-term empirical trends. This paper benchmarks six African countries—Senegal, Mozambique, Ghana, Rwanda, Côte d’Ivoire and Madagascar—representing distinct structural and institutional archetypes, and examines their water, sanitation and hygiene (WASH) trajectories from 2000 to 2022. Using harmonised WHO/UNICEF Joint Monitoring Programme (JMP) datasets, the study analyses progress rates, service gaps, rural–urban disparities, and the statistical relationship between economic performance and WASH outcomes. The results reveal four recurrent patterns: (i) large heterogeneity in baseline conditions but converging policy targets; (ii) non-linear progress with stagnation in several contexts; (iii) persistent rural deficits and weak correlation between GDP per capita and WASH performance; and (iv) sanitation trajectories that generally lag behind water, although some countries (notably Senegal and Ghana) display faster relative gains. A summary quadrant highlights where historical progress rates remain insufficient to align with SDG6 trajectories by 2030. These findings provide an evidence-based comparative lens to inform prioritisation, national investment strategies and regional monitoring architectures, while offering a transparent, replicable framework for tracking WASH delivery performance across diverse governance contexts. Keywords WASH; SDG6; Africa; drinking water; sanitation; JMP data; benchmarking; development trajectories; rural–urban gap 1. Introduction Access to safe drinking water and sanitation remains one of the most persistent development challenges in Africa. Although progress has been achieved since 2000, trajectories remain highly heterogeneous, shaped by demographic pressures, institutional fragmentation, fiscal constraints and the historical configuration of service delivery systems (Foster and BriceñoGarmendia, 2010; Mehta, 2014). Existing monitoring frameworks often rely on country-specific analyses and rarely provide structured cross-country comparisons of long-term WASH performance. This study addresses this gap by benchmarking six African countries representing distinct structural archetypes—Senegal, Mozambique, Ghana, Rwanda, Côte d’Ivoire and Madagascar. These countries span a range of governance models, economic conditions and WASH performance profiles, from relatively strong performers (Rwanda, Senegal, Ghana) to structurally constrained systems (Mozambique, Côte d’Ivoire, Madagascar) (Adank et al., 2014; World Bank, 2018). Using harmonised JMP datasets (WHO/UNICEF JMP, 2023), the analysis examines long-term trajectories in drinking water and sanitation, annual progress rates, structural drivers of performance and alignment with SDG6 targets (United Nations, 2015). The contribution is threefold. First, it provides a harmonised comparative dataset for crosscountry benchmarking over more than two decades (Shields et al., 2020). Second, it identifies long-term patterns and quantifies the SDG6 trajectory gap using a transparent, replicable methodology (Hutton and Varughese, 2016). Third, it analyses institutional, demographic and economic drivers shaping WASH progress, drawing on established frameworks of governance and service delivery (Lockwood and Smits, 2011; Andrews et al., 2017; Pritchett, 2020; OECD, 2021). 2. Data and Methods 2.1. Data sources The analysis draws on publicly available datasets from the WHO/UNICEF Joint Monitoring Programme (JMP), using the 2023 harmonised updates for drinking water and sanitation indicators (WHO/UNICEF JMP, 2023). These were complemented by GDP per capita (constant PPP) from the World Development Indicators (World Bank, 2023), demographic and rural–urban population distributions from the UN Department of Economic and Social Affairs (UN DESA, 2022), and selected macro-structural variables relevant for cross-country comparison. The JMP methodology provides globally standardised definitions and statistical procedures, ensuring comparability across countries and over time (Bain and others, 2014; WHO/UNICEF JMP, 2023). 2.2. Indicators The study focuses on two core service indicators defined by the JMP: • basic drinking water coverage (%), • basic sanitation coverage (%), as per global monitoring standards (WHO/UNICEF JMP, 2023). These indicators provide a consistent and long-term basis for cross-country benchmarking. Annualised progress rates were computed for three sub-periods—2000–2010, 2010–2015 and 2015–2022—to capture changes in momentum over time and identify inflection points relevant for SDG6 alignment, following approaches used in previous longitudinal WASH assessments (Smits and Moriarty, 2012). 2.3. Harmonisation and processing All JMP series were cleaned, validated and harmonised using a reproducible workflow aligned with standard global monitoring protocols (Shields et al., 2020; WHO/UNICEF JMP, 2023). Missing observations were handled through interpolation following JMP/UN guidelines, without additional model-based adjustments. GDP and demographic series were aligned to ensure temporal consistency and comparability across the six countries. No country-level reestimations or post-hoc corrections were applied. Data processing was carried out using opensource statistical software, and the full reproducibility package—including scripts and metadata—is archived in an open-access Zenodo repository. 2.4. Comparative methodology The comparative assessment follows a four-step analytical framework: 1. long-term trajectories: evaluation of 2000–2022 evolution in basic drinking water and sanitation coverage; 2. annualised progress patterns: comparison of progress rates across three sub-periods to detect acceleration, stagnation or reversals (Smits and Moriarty, 2012); 3. SDG6 trajectory gaps: estimation of the difference between projected 2030 access levels (based on historical trends) and SDG6 target thresholds (United Nations, 2015; Hutton and Varughese, 2016); 4. structural drivers: exploration of macro-structural correlates such as rural share, GDP per capita, population density and urbanisation patterns, informed by previous regional diagnostics (Foster and Briceño-Garmendia, 2010; OECD, 2021). The final diagnostic integrates these dimensions into a progress vs residual gap quadrant, which classifies countries according to the alignment of their historical trajectories with SDG6 requirements and highlights where acceleration or system reform is most needed (Smits and Moriarty, 2012; WHO/UNICEF JMP, 2023). 3. Results 3.1. Comparative WASH context The country comparison table shows considerable variation in baseline conditions (Figure 1). Ghana and Senegal enter the 2000–2022 period with relatively high basic drinking water coverage, while Mozambique, Madagascar and Côte d’Ivoire begin with much lower levels. Rwanda displays intermediate coverage yet stands out for its sanitation trajectory. Basic sanitation is the most constrained dimension across the sample, with 2022 values ranging from 14.8% in Madagascar to nearly 74% in Rwanda. These differences help frame the structural pathway each country follows over the period. 3.2. Basic drinking water trajectories The drinking water time series confirms steady progress in all six countries, but with marked differences in pace (Figure 2): • Mozambique has the highest long-term average gain (+1.90 pp/year). • Senegal and Ghana progress at +1.21 and +1.06 pp/year, respectively. • Rwanda’s trajectory remains consistent, though slightly slower (+0.93 pp/year). • Madagascar advances more slowly (+0.76 pp/year). • Côte d’Ivoire records the lowest rate (+0.10 pp/year), reflecting extended stagnation. By 2022, Ghana and Senegal reach levels above 85%, while Madagascar remains below 55%. The slopes suggest that early gains linked to population-dense areas slow down as more dispersed rural populations become the remaining frontier. 3.3. Basic sanitation trajectories Sanitation progress remains modest across most countries (Figure 3): • Rwanda displays the highest slope (+1.35 pp/year). • Mozambique (+1.25), Senegal (+1.07) and Ghana (+1.04) follow. • Côte d’Ivoire (+0.76) and Madagascar (+0.50) advance at slower rates. Despite progress, large sanitation gaps remain, particularly in rural areas. Rwanda is the only case where rural sanitation levels exceed urban levels in 2022, suggesting a long-term emphasis on community-led models. In other contexts, sanitation remains the slowest dimension, reinforcing its role as the key constraint for SDG6 alignment. 3.4. Annual progress patterns Annual WASH progress shows three consistent features (Figure 4): 1. All countries have improved water and sanitation access since 2000. 2. Water typically progresses faster than sanitation, with the exception of Rwanda where sanitation surpasses water. 3. The pace recorded across the group (mostly between 0.7 and 1.3 pp/year) remains below the estimated annual gains required to achieve SDG6 by 2030. This pattern is visible in Côte d’Ivoire and Madagascar, which combine slow water progress and limited sanitation gains. 3.5. SDG6 trajectory gap The gap analysis compares historic progress with the pace required to reach universal basic water by 2030 (Figure 5): • Madagascar would need to multiply its historic pace 7.6×. • Côte d’Ivoire requires a multiplication factor of ≥10×. • Mozambique would need 2.4× its historic pace. • Rwanda must reach 4.7× its past rate. • Ghana and Sénégal require ~1.4×. The figures confirm that business-as-usual trends are insufficient in most cases, particularly where rural deficits dominate. 3.6. Wealth vs access The scatter plot comparing GDP per capita and WASH coverage in 2022 shows a weak linear association (Figure 6). Countries with similar income levels display contrasting access outcomes—for instance: • Côte d’Ivoire and Ghana have comparable GDP levels but diverge in coverage. • Rwanda and Sénégal achieve high access levels despite more modest income. • Mozambique and Madagascar cluster at low income and low coverage, yet with different trajectories. The Pearson correlation coefficient is r = 0.41, indicating a weak linear relationship (and not statistically meaningful in such a small sample) between GDP per capita and average basic WASH coverage across this sample. This confirms that income alone does not explain observed performance differences. 3.7. Structural drivers The rural–urban comparison shows that rural deficits remain a defining constraint (Figure 7): • large water gaps in Mozambique, Côte d’Ivoire and Madagascar; • large sanitation gaps in all countries except Rwanda; • Rwanda displays an inverted pattern, with rural sanitation surpassing urban levels. These results indicate that rural settlement patterns, local government capacity and supply chain reliability are key determinants of national outcomes. 3.8. Investment modelling Indicative rural water investment needs in 2022 suggest (Figure 8): • Madagascar (~585 M USD) and Mozambique (~522 M USD) require the largest envelopes; • Côte d’Ivoire (~302 M USD) and Rwanda (~224 M USD) follow; • Ghana (~178 M USD) and Senegal (~103 M USD) require comparatively lower levels. Costing is based on a simple unit-cost model, providing a magnitude estimate rather than a full financial analysis. It highlights that countries with large rural populations and low coverage would need sustained investment to accelerate access. 3.9. Summary quadrant The summary quadrant (Figure 9: historic progress vs 2030 residual gap) positions: • Ghana and Senegal in the “higher progress, lower gap” area; • Rwanda in a similar space, with a moderate remaining gap; • Mozambique shows moderate progress with a sizeable gap; • Madagascar and Côte d’Ivoire in the “low progress, high gap” quadrant. This classification provides a straightforward diagnostic to identify where acceleration is most necessary. 4. Discussion The analysis suggests four stable patterns across the six countries. First, drinking water trajectories show sustained progress but with differing slopes. Mozambique progresses fastest, while Côte d’Ivoire and Madagascar display extended stagnation periods. The shape of the curves suggests that countries exhaust “easy gains” early and encounter structural constraints as the remaining population becomes more dispersed. Second, sanitation progress remains much slower than water in all contexts except Rwanda. The figures show that gains remain incremental and that rural–urban divides persist. Senegal and Ghana achieve more rapid sanitation increases than the rest of the group, possibly reflecting national programmes and targeted policy orientation. Rwanda’s performance in rural sanitation is also noteworthy, with rural coverage levels matching or exceeding urban coverage, which suggests that community-based approaches and performance-oriented governance can reduce disadvantages traditionally associated with rural settings (Rwanda Ministry of Infrastructure, 2016). Rwanda’s sanitation trajectory appears to reflect long-term programme continuity and structured community-level engagement, which distinguishes its rural service delivery model from those of the other countries in the sample (Rwanda Ministry of Infrastructure, 2016). Third, economic wealth does not predict WASH outcomes. The GDP–access plot shows considerable dispersion. Similar income levels correspond to different performance profiles, suggesting that governance arrangements, rural settlement patterns, and consistency in service delivery frameworks play a central role. Fourth, rural–urban gaps are the dominant structural driver of underperformance. The bar charts confirm that rural deficits shape national averages in all countries except Rwanda. The magnitude of the required 2030 acceleration correlates closely with the size of these rural gaps. Limitations include reliance on JMP series involving interpolations, absence of subnational disaggregation, and indicative investment modelling that excludes O&M and climate-related costs. Despite these limitations, the framework remains stable and can be replicated across additional countries. 5. Conclusion The updated figures reinforce four consistent findings across the six selected African countries. Drinking water access has improved over the last two decades, but with heterogeneous progress rates. Countries such as Senegal, Ghana and Rwanda show sustained gains, while others—particularly Madagascar and Côte d’Ivoire—record slower improvements. Sanitation remains the most constrained dimension, with persistent rural gaps. Rwanda provides the only example where rural sanitation exceeds urban levels, highlighting the influence of long-term community-based approaches. Economic indicators do not sufficiently explain performance variation. Countries with comparable income levels follow different trajectories, pointing to the role of institutional arrangements, decentralisation frameworks, and service delivery models. Rural–urban disparities determine much of the remaining gap. Countries with large dispersed rural populations require substantial acceleration and sustained financing to progress toward SDG6. The SDG6 gap analysis shows that historical progress rates are insufficient in several contexts, particularly Madagascar, Côte d’Ivoire and Mozambique. Achieving universal basic access by 2030 would require structural adjustments and predictable financing mechanisms. This comparative review provides a consistent and replicable approach for benchmarking WASH trajectories. The method can be expanded to other African countries and to safely managed services, and can incorporate fiscal and climate dimensions in future analyses. References Adank, M., Parker, N., Cronin, A.A., Moriarty, P., 2014. Understanding the WASH system in Ghana: Identifying bottlenecks. IRC. Andrews, M., Pritchett, L., Woolcock, M., 2017. Building State Capability: Evidence, Analysis, Action. Oxford University Press, Oxford. https://doi.org/10.1093/acprof:oso/9780198747482.001.0001 Bain, R., others, 2014. Monitoring progress towards universal access to safely managed drinking water and sanitation. PLOS Medicine 11, e1001645. https://doi.org/10.1371/journal.pmed.1001645 Foster, V., Briceño-Garmendia, C., 2010. 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World Bank, 2023. World Development Indicators – GDP per capita, PPP (constant 2017 international $). World Bank, 2018. Senegal—Water Sector Reform: Lessons from 20 Years of Public–Private Partnership. World Bank. Figures and Captions Figure 1. Comparative WASH Analysis: 6 African Archetypes (2000–2022) Comparative WASH indicators for six African countries in 2022, including area, GDP, population, and basic water/sanitation coverage. Countries are ordered by sanitation performance, the main structural constraint for SDG6 progress. Rwanda and Senegal show stronger institutional trajectories, while Madagascar and Côte d’Ivoire face chronic structural and rural deficits. These baseline contrasts frame the interpretation of long-term WASH trajectories. Figure 8. Indicative Rural Basic Water Investment (2022) Estimated rural basic water investment needs (million USD) to close the 2022 coverage gap to universal access. Madagascar and Mozambique absorb the largest indicative envelopes due to large rural populations and low baseline coverage. These values represent oneoff capital needs and exclude O&M and climate-related costs. Figure 9. Summary Quadrant: Progress vs Residual Gap (Basic Water) Diagnostic quadrant comparing historic progress rates and projected 2030 residual gaps under a business-as-usual trajectory. Madagascar and Côte d’Ivoire combine slow progress and large residual gaps, positioning them as highest-risk cases. Ghana, Senegal and Rwanda cluster in the higher-progress, lower-gap zone.