Scientific Reports (Dec 2024)

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

DOI
https://doi.org/10.1038/s41598-024-78616-8
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 14

Abstract

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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.

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