Abstract
In the face of climate change-induced droughts, vulnerable regions encounter severe threats to food security, demanding urgent humanitarian assistance. This paper introduces a causal inference framework for the Horn of Africa, aiming to assess the impact of cash-based interventions on food crises. Our contributions include identifying causal relationships within the malnutrition system, harmonizing a comprehensive database including socio-economic, weather and remote sensing data, and estimating the causal effect of cash-based interventions on malnutrition. On a country level, our results revealed no significant effects, likely due to limited sample size, suboptimal data quality, and an imperfect causal graph resulting from our limited understanding of multidisciplinary systems like malnutrition. Instead, on a district level, results revealed significant effects, further implying the context-specific nature of the system. This underscores the need to enhance data collection and refine causal models with domain experts for more effective future interventions and policies, improving transparency and accountability in humanitarian aid.
| Original language | English |
|---|---|
| Pages | 1546-1552 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2024 |
| Externally published | Yes |
| Event | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 - Athens, Greece Duration: 7 Jul 2024 → 12 Jul 2024 |
Conference/symposium
| Conference/symposium | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 |
|---|---|
| Country/Territory | Greece |
| City | Athens |
| Period | 7/07/24 → 12/07/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
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SDG 13 Climate Action
Keywords
- Causality
- food insecurity
- humanitarian crises
- malnutrition
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