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Better data for better outcomes: New tools and analysis to break Afghanistan’s food security crisis

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Better data for better outcomes: New tools and analysis to break Afghanistan’s food security crisis Bamiyan, Afghanistan - 05 11 2024: A woman in blue burqa begs for food at a market stall in Bamiyan bazaar. / Photo: Shutterstock

Afghanistan is facing a severe food security crisis. Nearly one-third of the population – 12.6 million people – are experiencing food insecurity, with 2.9 million on the brink of starvation. Economic instability, climate shocks, and disrupted agricultural productivity have left the nation struggling to meet basic needs. As the world aims for zero hunger by 2030, Afghanistan’s challenges paint a different picture. However, tools like machine-learning-enabled food security estimates and real-time price monitoring are helping address critical gaps and provide hope for effective policy interventions.
 

Climate shocks: a critical factor in the crisis

Climatic shocks are a key driver of food insecurity in Afghanistan, significantly impacting the country’s conflict-affected agricultural economy. Floods and droughts disrupt agricultural cycles, making it difficult for farmers to sustain productivity. While these impacts have long been reported, a new study leveraging nearly 15 years of monthly data on climatic anomalies, food security outcomes, and local price information provides fresh quantitative insight into their effects. The data show that flood events increase the probability of food stress (Integrated Phase Classification 2 and above) by 23.4% and food crises (IPC 3 and above) by 5.9%. Food crises, in particular, signal a severe level of food insecurity where livelihoods risk irreversible damage.

The analysis further reveals that droughts tend to worsen food shortages, despite occasional mitigation from market responses and aid. Positive vegetation anomalies, which suggest lush conditions after floods, paradoxically heighten food stress due to their association with excessive rainfall and subsequent challenges. These findings highlight the importance of interpreting climate data within local conditions and underscore the complex interplay of climatic and economic factors shaping Afghanistan’s food crisis.


Figure 1. Marginal effects of various factors on food stress and food crisis.

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Source: Estimates taken from Gbadegesin, T. K., Andree, B. P. J., Braimoh, A. Climate Shocks and Their Effects on Food Security, Prices, and Agricultural Wages in Afghanistan. Policy Research Working Paper; Washington, D.C.: World Bank Group. The chart visualizes the impact of key factors such as floods, droughts, and vegetation health on food insecurity. The blue bars represent factors influencing food stress, while the orange bars show their impact on food crises. Flood anomalies stand out as the most significant contributor to both food stress and crisis risks. Flood anomalies increase food stress probability by 23.4% and food crisis probability by 5.9%. Positive NDVI anomalies raise food stress probability by 18% and food crisis by 1.5%, while negative NDVI anomalies increase food stress by 8.8% and food crisis by 3.7%.

Building the foundation of tomorrow’s food security systems

Modeled approaches such as these not only improve the understanding of food security drivers but also lay the foundation for a more data-driven global food security analysis system. In a field historically dominated by qualitative analysis and institutional narratives, verifiable data and reproducible analysis such as for this new paper provide an important anchor for unbiased food security assessments.

By leveraging modern data processing techniques, including machine learning, we can develop advanced data systems to track food insecurity estimates with greater speed and precision—and form the backbone of next-generation monitoring capabilities that offer increased transparency and lower costs.

 

Figure 2. Historical and estimated food stress

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This figure demonstrates the potential of new modeling approaches to deliver rapid and cost-effective food security assessments. The blue line indicates data from FEWS NET used by the study. The green line shows estimates produced by the study’s model. No assessments were carried out between June 2021 and February 2023. However, modeled estimates continued to be produced, showcasing how these innovations can reduce the costs of traditional assessments and improve the efficiency of responses to emerging crises.

Two examples of improved monitoring tools that have already been brought online are the World Bank’s Real Time Prices (RTP) system and the multi-partner Joint Monitoring Report.
 

The RTP platform leverages machine learning techniques to monitor food price shocks and inflation with unprecedented detail, enabling policymakers to track and respond to emerging challenges in near real-time. The RTP system was also used to support this new study in Afghanistan.

The Real Time Prices platform provides granular insights into food price fluctuations, helping identify inflationary trends that impact vulnerable populations. Such tools enable new analysis such as presented in this blog and enhance the overall precision and timeliness of interventions, offering a new edge in the fight against food insecurity. The dropdown menus can be used to select market locations and commodity types. Note that these data can be accessed on the Microdata Library. Unofficial deflators, such as local-market exchange rates and wages used in this study, can also be viewed here: RTP on the Microdata Library.

The JMR provides a cost-effective platform that leverages these new data innovations to equip countries with high-frequency monitoring solutions powered by advanced machine learning and artificial intelligence. In collaboration with partners, efforts are underway to expand the Joint Monitoring Report into a cutting-edge, cost-effective platform for rapid, data-driven food security assessments in 60 countries by 2030. Currently, the JMR is being pioneered in countries like Somalia and Yemen, where, using just six high-frequency indicators, over 80% of food security emergencies can be detected before they emerge, even in data-scarce environments.
 

You can watch a shorter version of the below video here.


Turning insights into action: leveraging better monitoring for targeted interventions and resilience

With improved monitoring capabilities, policymakers can take more targeted and effective action. Building resilience in Afghanistan’s agriculture is essential to mitigating the devastating impact of climate shocks. Strengthening irrigation systems, adopting drought-resistant crops, and investing in early warning systems can stabilize food prices and wages while reducing dependency on humanitarian aid. These measures must be paired with targeted interventions in provinces with consistently high probabilities of food insecurity to break the cycle of hunger and vulnerability.

Addressing these challenges requires a coordinated approach that integrates economic and environmental solutions. By leveraging better data systems and embracing forward-looking policies, Afghanistan can pave the way for a more secure and sustainable future.


Figure 3. Estimated crisis probabilities in provinces across Afghanistan (2010-2023)

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Source: Estimates taken from Gbadegesin, T. K., Andree, B. P. J., Braimoh, A. Climate Shocks and Their Effects on Food Security, Prices, and Agricultural Wages in Afghanistan. Policy Research Working Paper; Washington, D.C.: World Bank Group. The map visualizes how estimated crisis vary by region, underscoring the need for localized interventions. 

For a deeper dive into the findings and policy recommendations, read the full study: World Bank Policy Research Working Paper and Reproducibility Package.


Tosin Gbadegesin

Economist & Data Scientist, Gender and Economic Inclusion Department, IFC

Bo Andree

Data Scientist, Development Data Group, World Bank

Ademola Braimoh

Senior Natural Resources Management Specialist, Agriculture Global Practice, World Bank

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