ArticleFrontiers in public health2025
Making sense of shaky data in humanitarian crises.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- The humanitarian AI paradox: Key opportunities, challenges and research needs for the use of AI in humanitarian mental health response.Global mental health (Cambridge, England) · 2026Review
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2 authors.
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Abstract
Humanitarian decision-making occurs in volatile and politically charged environments where information is often incomplete, outdated, or conflicting. Effective humanitarian response often requires interpreting poor-quality data to guide interventions, allocate resources, and assess impact. Despite advances in evidence generation, knowledge gaps persist, and decisions are frequently influenced by political and organizational factors rather than by data. This paper argues that data interpretation is an area of weakness in humanitarian response. Data availability and quality vary across crises, with methodological challenges and political sensitivities further complicating interpretation. The three examples of Darfur (Sudan), Yemen and Ethiopia illustrate how conflicting information and ambiguous interpretation can negatively impact critical decisions with far-reaching consequences on the affected communities. This paper concludes with suggestions for making better interpretation and use of data in humanitarian crises.
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