Evidence map›Paper›PMID 35939400›Full record

SynthesisJournal of global health2022

How applicable is geospatial analysis in maternal and neonatal health in sub-Saharan Africa? A systematic review.

Sisay Mulugeta Alemu, Abera Kenay Tura, Gabriel S Gurgel do Amaral, Catherine Moughalian, Gerd Weitkamp, Jelle Stekelenburg, Regien Biesma

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Application of geospatial analysis for mapping the distribution of severe maternal morbidities in eastern Ethiopia: The case of the Ethiopian obstetric surveillance system.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sisay Mulugeta AlemuGlobal Health Unit, Department of Health Sciences, University Medical Center Groningen, Groningen, the Netherlands.
Abera Kenay TuraSchool of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia.
Gabriel S Gurgel do AmaralDepartment of Health Sciences, Community and Occupational Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Catherine MoughalianGlobal Health Unit, Department of Health Sciences, University Medical Center Groningen, Groningen, the Netherlands.
Gerd WeitkampDepartment of Cultural Geography, Faculty of Spatial Sciences, University of Groningen, Groningen, the Netherlands.
Jelle StekelenburgGlobal Health Unit, Department of Health Sciences, University Medical Center Groningen, Groningen, the Netherlands.
Regien BiesmaGlobal Health Unit, Department of Health Sciences, University Medical Center Groningen, Groningen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sub-Saharan Africa (SSA) has the world's highest maternal and neonatal morbidity and mortality and has shown the slowest progress in reducing them. In addition, there is substantial inequality in terms of maternal and neonatal morbidity and mortality in the region. Geospatial studies can help prioritize scarce resources by pinpointing priority areas for implementation. This systematic review was conducted to explore the application of geospatial analysis to maternal and neonatal morbidity and mortality in SSA. Methods: A systematic search of PubMed, SCOPUS, EMBASE, and Web of Science databases was performed. All observational and qualitative studies that reported on maternal or neonatal health outcomes were included if they used a spatial analysis technique and were conducted in a SSA country. After removing duplicates, two reviewers independently reviewed each study's abstract and full text for inclusion. Furthermore, the quality of the studies was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklists. Finally, due to the heterogeneity of studies, narrative synthesis was used to summarize the main findings, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was strictly followed to report the review results. A total of 56 studies were included in the review. Results: We found that geospatial analysis was used to identify inequalities in maternal and neonatal morbidity, mortality, and health care utilization and to identify gaps in the availability and geographic accessibility of maternal health facilities. In addition, we identified a few studies that used geospatial analysis for modelling intervention areas. We also detected challenges and shortcomings, such as unrealistic assumptions used by geospatial models and a shortage of reliable, up-to-date, small-scale georeferenced data. Conclusions: The use of geospatial analysis for maternal and neonatal health in SSA is still limited, and more detailed spatial data are required to exploit the potential of geospatial technologies fully.

Indexed as

Health FacilitiesInfant HealthAfrica South of the SaharaHumansInfant, NewbornPatient Acceptance of Health CareQualitative Research

Identifiers

PMID35939400
PMCPMC9359463

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.