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Background <p>Access to safe drinking water remains a major challenge in sub-Saharan Africa, where reliance on unimproved water sources exposes millions to waterborne diseases and undermines progress toward Sustainable Development Goal 6 (SDG 6). Understanding spatial patterns and determinants of unimproved water use is essential for targeting WASH interventions.</p> Method <p>We analyzed data from 500,845 households across 20,492 clusters in 34 sub-Saharan African countries using Demographic and Health Surveys (2012–2024). Data was processed using Microsoft Excel and STATA version 17. Prevalence estimates accounted for the DHS complex sampling design. Spatial analyses (Global Moran’s I, Getis-Ord Gi*, SaTScan™, Anselin Local Moran’s I) and Geographically Weighted Regression (GWR) were conducted to identify clusters and key predictors.</p> Result <p>Overall, 58% (95% CI: 51%–65%) of households relied on unimproved drinking water sources. This indicates that approximately three in five households utilize unimproved water source. Significant spatial clustering was detected (Global Moran’s I = 0.2415, <i>p</i> &lt; 0.001), with major hotspots in Madagascar, Uganda, Rwanda, Mozambique, Malawi, Chad, Nigeria, Togo, Burkina Faso, Liberia, Sierra Leone, Mali, Ethiopia, parts of Angola, the Congo Republic, Zambia, and Zimbabwe. SaTScan™ identified 109 significant clusters, and Local Moran’s I revealed mixed high- and low-risk zones. GWR (adjusted R² = 0.917) highlighted key predictors: rural residence, female-headed households, older household heads (50 + years), poverty, limited media exposure, lack of electricity, and poor water access.</p> Conclusion <p>Unimproved water use remains widespread and spatially concentrated across sub-Saharan Africa. The determinants identified by GWR poverty, rural residence, limited infrastructure access, and low household media exposure highlight critical inequities driving this burden. Addressing these disparities requires localized, data-driven WASH planning that prioritizes hotspot regions, expands access to affordable improved water systems, strengthens electricity and media outreach infrastructure, and supports vulnerable households. Implementing these targeted and multi-sectoral strategies is essential for accelerating equitable progress toward SDG 6 and improving public health resilience across the region.</p>

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Mapping inequities in safe water access: a spatial and geographically weighted regression analysis of unimproved water source use in sub-Saharan Africa

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月14日

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  • Gelila Yitageasu,
  • Alemayehu Kasu Gebrehana,
  • Angwach Abrham Asnake,
  • Bizunesh Fantahun Kase,
  • Mitkie Tigabie,
  • Lidetu Demoze

摘要

Background

Access to safe drinking water remains a major challenge in sub-Saharan Africa, where reliance on unimproved water sources exposes millions to waterborne diseases and undermines progress toward Sustainable Development Goal 6 (SDG 6). Understanding spatial patterns and determinants of unimproved water use is essential for targeting WASH interventions.

Method

We analyzed data from 500,845 households across 20,492 clusters in 34 sub-Saharan African countries using Demographic and Health Surveys (2012–2024). Data was processed using Microsoft Excel and STATA version 17. Prevalence estimates accounted for the DHS complex sampling design. Spatial analyses (Global Moran’s I, Getis-Ord Gi*, SaTScan™, Anselin Local Moran’s I) and Geographically Weighted Regression (GWR) were conducted to identify clusters and key predictors.

Result

Overall, 58% (95% CI: 51%–65%) of households relied on unimproved drinking water sources. This indicates that approximately three in five households utilize unimproved water source. Significant spatial clustering was detected (Global Moran’s I = 0.2415, p < 0.001), with major hotspots in Madagascar, Uganda, Rwanda, Mozambique, Malawi, Chad, Nigeria, Togo, Burkina Faso, Liberia, Sierra Leone, Mali, Ethiopia, parts of Angola, the Congo Republic, Zambia, and Zimbabwe. SaTScan™ identified 109 significant clusters, and Local Moran’s I revealed mixed high- and low-risk zones. GWR (adjusted R² = 0.917) highlighted key predictors: rural residence, female-headed households, older household heads (50 + years), poverty, limited media exposure, lack of electricity, and poor water access.

Conclusion

Unimproved water use remains widespread and spatially concentrated across sub-Saharan Africa. The determinants identified by GWR poverty, rural residence, limited infrastructure access, and low household media exposure highlight critical inequities driving this burden. Addressing these disparities requires localized, data-driven WASH planning that prioritizes hotspot regions, expands access to affordable improved water systems, strengthens electricity and media outreach infrastructure, and supports vulnerable households. Implementing these targeted and multi-sectoral strategies is essential for accelerating equitable progress toward SDG 6 and improving public health resilience across the region.