Misidentified household food insecurity: how relying on a single survey round produces targeting errors in food security programs

Summary

This study addresses a critical implementation gap in humanitarian food security programs: the reliance on single-round surveys to identify beneficiaries, despite substantial weekly and seasonal fluctuations in household food security status. Using year-long weekly financial diary data and Monte Carlo simulations, the authors demonstrate that single-indicator surveys produce misclassification rates of 15–48%, but combining multiple indicators—using tools already available to implementers—reduces this to 6–15%. The findings have direct relevance for improving programme targeting accuracy in low- and middle-income country contexts.

Regional applicability

Whilst the study focuses on low- and middle-income countries, the methodological insight applies broadly to food security programme design. In the United Kingdom, where food insecurity measurement increasingly informs policy and welfare targeting, the findings underscore the importance of capturing temporal variation in household food security status rather than relying on cross-sectional snapshots.

Key measures

Misclassification rates (false positives and false negatives) for three widely used food security indicators; comparison of single-indicator versus multi-indicator approaches

Outcomes reported

The study quantified misclassification rates when using single-round household surveys to identify food-insecure households eligible for humanitarian assistance. It demonstrated that combining multiple food security indicators substantially reduces targeting errors.

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