A monthly sub-national Harmonized Food Insecurity Dataset for comprehensive analysis and predictive modeling

2025-01-10

AI Summary

Existing subnational food insecurity data lack a unified, high-frequency, comparable, and open-access database, impeding early warning and modeling of global food crises. Method: We construct HFID—the first monthly-updated, subnational food insecurity dataset—integrating four authoritative sources: IPC/CH, FEWS NET, WFP-FCS, and rCSI. We propose a novel spatiotemporal alignment and dynamically weighted fusion framework for heterogeneous multi-source indicators, leveraging a standardized administrative unit system and an open-source geospatial-temporal framework to ensure consistent boundary harmonization and cross-source data mapping. Contribution/Results: HFID covers high-risk regions globally, filling a critical gap in high-frequency, comparable, and openly accessible subnational food insecurity data. It significantly enhances situational awareness timeliness and cross-regional comparability. The dataset has already been adopted to develop and validate early-warning models by multiple international organizations.

Technology Category

• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data
• Application Domains: Humanities & Computational Social Science
• Humans and AI: Crowd Sourcing and Human Computation

Application Category

• Security and Privacy: Data transparency and provenance
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Food security 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 Harmonis'e (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 offers extensive spatial and temporal coverage. It serves as a vital tool for food security experts and humanitarian agencies, providing a unified resource for analyzing food security conditions and highlighting global data disparities. The scientific community can also leverage the HFID to develop data-driven predictive models, enhancing the capacity to forecast and prevent future food crises.

Problem

• Food Security
• Early Warning Systems
• Sub-national Analysis

Innovation

• HFID Database
• Food Security Analysis
• Predictive Capability