Financing & Policy

Evidence brief: Effective Coverage of Maternal and Newborn Health Services in Sub-Saharan Africa: What distinguishes high from medium and low performers?

A sourced PLOS One study, published 2026-04-13. Read the researchers’ findings, methods and context, with links to connected African health evidence.

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Published in PLOS One on 2026-04-13, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.

Original authors: Ayelign Mengesha Kassie, Solomon Woldeyohannes, Anteneh Zewdie, Eskinder Wolka, Yibeltal Assefa

Source: PLOS One • DOI 10.1371/journal.pone.0347151

Read the complete primary study ↗ · Creative Commons Attribution licence

From the researchers

Abstract

Effective coverage (EC) has emerged as a better measure of service coverage, in the past decades, compared to the simple crude coverage measures. It represents the proportion of a population in need of a service that successfully receives it with sufficient quality to achieve the intended health benefits. Nevertheless, EC in maternal and newborn health (MNH) services are significantly variable across and within countries. Therefore, this study aimed to identify the societal and health system factors that can explain why some countries are having higher EC of MNH services than others in Sub-Saharan Africa (SSA).

A mixed-method case study design was employed with inclusion of document review. Effective coverage rates were estimated using countries demographic and health survey (DHS) datasets. Two countries were then selected for each MNH service domain from each performance category, high, medium, and low, for further analysis of explanatory factors. Data sources included DHS and health facility survey summary reports, the Global Health Expenditure Database, and TheGlobalEconomy.com.

We found huge variation in EC of MNH services across countries in SSA. The scores range from 7% in Ethiopia to 64% in Liberia for 4+ ANC visits, 9% in Ethiopia and Nigeria to 81% in Rwanda for institutional delivery, 3% in Ethiopia to 77% in Gambia for PNC mothers, and 1% in Ethiopia to 68% in South Africa for PNC newborns. These discrepancies are highly likely influenced by multilevel health system and societal factors. High-performing countries in EC of MNH services have higher service availability and readiness scores than medium- and low-performing ones. For instance, Ghana and Liberia scored 83% and 84%, respectively, for tracer indicators of ANC service availability, compared to 43% in Ethiopia and 64% in Malawi. Similar pattern is observed between the selected countries EC estimates of MNH services and their health service specific readiness index scores. In addition, they also have favourable societal factors including high proportion of women attending primary and/or more school levels, better mass media and internet access, and relatively lower political instability indexes. Low-performing countries like Ethiopia and Nigeria had complex futures including having low health service availability and readiness scores and unfavourable societal factors including in women’s education, and internet and mass media access. Furthermore, the two countries had weakest average political stability index that hinders the utilization and delivery of MNH services.

The findings revealed that better health service availability and readiness, strong healthcare financing, favourable societal factors and having a relatively stable political index are critical in determining countries performance in EC of MNH services. Therefore, countries, particularly low performers in EC of MNH services need to learn from positive outliers in improving EC of MNH services. Strengthening existing health facilities with better staffing, training, and resources is crucial beyond merely expanding new ones.

Reading this evidence

Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.

This briefing makes the source accessible within the wider financing & policy desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.

© 2026 Ayelign Mengesha Kassie, Solomon Woldeyohannes, Anteneh Zewdie, Eskinder Wolka, Yibeltal Assefa. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.

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Health Signal Editorial Desk

Health Signal’s publication desk curates source-based health analysis and attributed research briefings. Study authors and originating institutions are credited within each article. Preparation used AI assistance; source and licence checks do not constitute independent replication or clinical endorsement.

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