Evidence map›Paper›PMID 39617760›Full record

ArticleScientific reports2024

Exploring the spatial and spatiotemporal patterns of severe food insecurity across Africa (2015-2021).

Mesfin M Ayalew, Zelalem G Dessie, Aweke A Mitiku, Temesgen Zewotir

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mesfin M AyalewDepartment of Statistics, College of Science, Bahir Dar University, P.O.Box 79, Bahir Dar, Ethiopia. m2mulu@gmail.com.
Zelalem G DessieDepartment of Statistics, College of Science, Bahir Dar University, P.O.Box 79, Bahir Dar, Ethiopia.
Aweke A MitikuDepartment of Statistics, College of Science, Bahir Dar University, P.O.Box 79, Bahir Dar, Ethiopia.
Temesgen ZewotirSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food insecurity is a rapidly increasing global challenge. It has multiple adverse effects on public health and nutrition outcomes. The level and patterns of severe food insecurity vary by region. This study, therefore, aims to investigate the spatial and spatio-temporal patterns of severe food insecurity across the African continent. Data used in this study include the annual prevalence of severe food insecurity from 2015 to 2021, obtained from the FAO. Spatial analytical techniques such as Global Moran's I, Anselin's Local Moran I, and Getis-Ord Gi* statistic were used to determine the extent of spatial clustering of severe food insecurity and detect severe food insecurity hotspot (high-risk) areas over time. Kulldorff's space-time scan statistic was also used to detect temporal and space-time clusters of severe food insecurity. A Poisson model was utilized for this purpose. The results revealed that severe food insecurity varies unevenly across the continent over time and there was a significant clustering of severe food insecurity from 2015 to 2021 at a 5% significance level. Accordingly, Democratic Republic of the Congo and Central African Republic (2015-2021), Uganda (2015 and 2017-2020), Zambia (2019-2020), Angola (2019-2021) and Sierra Leone (2017) were identified as hotspot (high-risk) areas for severe food insecurity at 5% level of significance. The space-time cluster analysis identified six significant clustered areas. The most likely significant space-time cluster was located in Somalia, East Africa (LLR = 6,081,314.44, RR = 2.41, P-value < 0.000), which occurred between 2015 and 2017. The largest secondary significant space-time cluster was located in the continent's central regions between 2015 and 2017 (LLR = 44,393,763, RR = 2.26, P < 0.000). The study concludes that intervention efforts should consider the spatial heterogeneity of severe food insecurity over time to prevent and control this issue.

Indexed as

Food InsecuritySpatio-Temporal AnalysisAfricaFood SupplyHumansPrevalenceAfricaSevere food insecuritySpace–time clusterSpatial patternSpatiotemporal pattern

Identifiers

PMID39617760
PMCPMC11609261

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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.