ArticleScientific data2025
A monthly sub-national Harmonized Food Insecurity Dataset for comprehensive analysis and predictive modeling.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Data for famine and extreme emergencies: challenges and opportunities.Journal of public health policy · 2026Article
- Heading toward a famine: modeling seasonality of malnutrition in Yemen, 2018-2023.Journal of public health policy · 2026Article
- Harmonized food consumption dataset by food category and acquisition source for Sub-Saharan African countries.Scientific data · 2026Article
- Plate Food Waste in Early Childhood Education: Contextual and Nutritional Drivers with Implications for Sustainable Food Systems.Foods (Basel, Switzerland) · 2025Article
- A monthly sub-national Harmonized Food Insecurity Dataset for comprehensive analysis and predictive modeling.Scientific data · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Food insecurity is a complex, multidimensional concept challenging to measure comprehensively. Effective anticipation, monitoring, and mitigation of food crises require timely and comprehensive global data. This paper introduces the Harmonized Food Insecurity Dataset (HFID), an open-source resource consolidating four key data sources: the Integrated Food Security Phase Classification (IPC)/Cadre Harmonisé (CH) phases, the Famine Early Warning Systems Network (FEWS NET) IPC-compatible phases, and the World Food Program's (WFP) Food Consumption Score (FCS) and reduced Coping Strategy Index (rCSI). Updated monthly and using a common reference system for administrative units, the HFID provides comprehensive spatial and temporal coverage to the extent permitted by the available data. It serves as a vital tool for food insecurity experts and humanitarian agencies, providing a unified resource for analyzing food insecurity conditions and highlighting global data disparities and gaps. The scientific community can also leverage the HFID to develop data-driven predictive models, enhancing the capacity to forecast and prevent future food crises.
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Registered trials
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