Maternal Health Infrastructure Investments in Zambia: Leveraging Geospatial Evidence to Inform Planning and Prioritization

Abstract In many low- and middle-income countries (LMICs), inequities in maternal health outcomes are linked to disparities in spatial access to essential health services. In Zambia, significant portions of the rural population reside beyond 5 kilometers from the nearest health facility. This contributes to the “three delays” of maternal mortality: delay to seek care, delay to reach a health facility, and delay to receive care from a skilled health provider. Consequently, at 187 per 100,000 live births, Zambia’s maternal mortality ratio is above the global target of fewer than 70. This paper describes the application of a geospatial prioritization approach used by the Ministry of Health to guide investments in new maternal health infrastructure (mothers’ waiting homes and maternity annexes) and upgrades to existing facilities. Using cross-sectional data from 692 public health facilities in Eastern and Southern Provinces, the approach integrates routine service and maternal mortality data from the national Health Management Information System (HMIS), with facility infrastructure assessments and geospatial analysis. Facilities were screened using binary eligibility criteria based on recorded maternal deaths and then ranked using a weighted scoring model reflecting infrastructure readiness gaps for continuity of maternal care. Findings indicate widespread facility coverage for labor and delivery services, contrasted against inadequate capacity for the recommended 48-hour postnatal observation care. Maternal deaths were concentrated in 28% of facilities in Eastern and 19% in Southern Province. Applying the prioritization framework reduced the potential scope of infrastructure investment from 606 facilities to 27 high-priority sites, lowering projected investment costs from US$41.8 million to approximately US$2 million. The approach demonstrates how targeted infrastructure investments, informed by geospatial and routine health system data, can improve equity, continuity of care, and optimize impact from limited resources. This applied framework offers a practical and scalable model for evidence-informed infrastructure planning in resource-constrained settings.