Evidence map›Paper›PMID 41944594›Full record

ArticleInternational journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics2026

Application of geospatial analysis for mapping the distribution of severe maternal morbidities in eastern Ethiopia: The case of the Ethiopian obstetric surveillance system.

Sisay Mulugeta Alemu, Gerd Weitkamp, Marian Knight, Sagni Girma, Mohammed Yuya, Jelle Stekelenburg, Thomas van den Akker, Regien Biesma, Abera Kenay Tura

Abstract read
In one paragraph

Article in International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Sisay Mulugeta AlemuGlobal Health Unit, Department of Health Sciences, University Medical Center Groningen, Groningen, the Netherlands.ORCID https://orcid.org/0000-0002-9270-9281
Gerd WeitkampDepartment of Cultural Geography, Faculty of Spatial Sciences, University of Groningen, Groningen, the Netherlands.ORCID https://orcid.org/0000-0002-7367-8467
Marian KnightNational Perinatal Epidemiology Unit, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-1984-4575
Sagni GirmaSchool of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Haramaya, Ethiopia.ORCID https://orcid.org/0000-0002-3858-190X
Mohammed YuyaDepartment of Obstetrics and Gynecology, Leiden University Medical Center, Leiden, the Netherlands.ORCID https://orcid.org/0000-0002-4143-3297
Jelle StekelenburgGlobal Health Unit, Department of Health Sciences, University Medical Center Groningen, Groningen, the Netherlands.ORCID https://orcid.org/0000-0002-2732-6620
Thomas van den AkkerDepartment of Obstetrics and Gynecology, Leiden University Medical Center, Leiden, the Netherlands.ORCID https://orcid.org/0000-0002-9890-9145
Regien BiesmaGlobal Health Unit, Department of Health Sciences, University Medical Center Groningen, Groningen, the Netherlands.ORCID https://orcid.org/0000-0002-5532-0242
Abera Kenay TuraSchool of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Haramaya, Ethiopia.

Funding

Universitair Medisch Centrum Groningen
6 · The paper itself

Abstract

introductionThe disparity in maternal mortality and severe morbidity between high- and low-income countries is well established. Previously, we highlighted within-country disparities in Ethiopia using demographic and health survey data. This study used enhanced obstetric surveillance data to detect subnational hotspot areas and factors associated with disparities in severe maternal morbidity in eastern Ethiopia.

methodsThis study used data from the Ethiopian Obstetric Surveillance System (EthOSS) study, which collected data for all women who experienced severe maternal morbidity in 13 hospitals in eastern Ethiopia between April 2021 and March 2022. Women whose geographical location was not recorded were excluded. We used optimized hotspot analysis to identify areas with higher rates of severe maternal morbidity while controlling for population density and conducted linear and geographically weighted regression analyses to assess factors associated with the distribution.

resultsOf all 2043 women with severe maternal outcomes, 1775 (87%) women with severe maternal morbidity with complete geographical information were included for analysis. Less than half (47%) lived within the recommended 2-h travel time to the nearest emergency obstetric and newborn care (EmONC) facility, with significant geographic variation. Hotspot analysis identified clusters of high rates near urban centers such as Dire Dawa and Harari even after controlling for the population density, while lower rates were found in eastern Oromia. Geographically weighted regression analysis showed that proximity to health facilities, especially to a basic or comprehensive EmONC facility, was associated with higher maternal complication rates.

conclusionThis study highlights the value of leveraging geocoded surveillance data to conduct geospatial analyses to uncover spatial patterns. We found a higher rate of severe maternal morbidity in the larger cities, indicating that the urban population had better access to care during obstetric complications, while rural and remote areas with limited access might fail to come to hospitals when complications arise or die at home or lower-level facilities.

Indexed as

Maternal Health ServicesPopulation SurveillancePregnancy ComplicationsAdolescentAdultEthiopiaFemaleHumansMaternal MortalityPregnancySpatial AnalysisYoung AdultEthiopiageospatial analysismaternal complicationsobstetric surveillance

Identifiers

PMID41944594
PMCPMC13629590

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