ADDIS ABABA—A study conducted by the Intergovernmental Authority on Development’s (IGAD) Conflict Early Warning and Response Mechanism (CEWARN) and Virtual Research Associates (VRA) has found a significant correlation between favorable climate conditions and a reduced likelihood of violent conflict in the IGAD region. The report, titled “
CLIMATE-CONFLICT NEXUS IN THE IGAD REGION,” analyzed data from 2018 to 2022 to identify environmental and behavioral predictors of conflict incidents. The study was published in November 2023 with financial support from Irish Aid.
Key Findings
The study used a logit regression statistical analysis on environmental and open-source media report data, revealing that healthier vegetation and increased rainfall are significantly related to a lower probability of physical conflict. The research specifically focused on conflicts involving assault, fighting, and violence.
Key findings from the study include:
- A One-Month Lag: The study established a one-month lag between environmental changes and their impact on conflict outcomes. This means changes in vegetation health or rainfall in a given month can predict the likelihood of conflict in the following month.
- Vegetation’s Impact: A 0.2 increase in the Normalized Difference Vegetation Index (NDVI), a measure of vegetation greenness, was associated with a 12% decrease in the probability of physical conflict in the subsequent month.
- Rainfall’s Impact: An additional inch of rainfall in an Area of Reporting (AOR) was found to result in an 8% reduction in the likelihood of conflict the following month.
- Strong Correlation: The study also revealed a high correlation between rainfall and the vegetation index, suggesting that rainfall data can be used to estimate vegetation quality and, consequently, its likely impact on conflict.
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Methodology and Data
The 2023 study represents an expansion on previous research, using a broader geographical scope across the entire IGAD region and incorporating a new climate variable—
Rainfall Estimate (RFE)—for its analysis. It utilized an open-source media report dataset, which comprised approximately 13,000 discrete AORs, and environmental data on vegetation and rainfall estimates. The study team, consisting of experts from VRA and CEWARN, strategically selected AORs that were crucial agricultural hubs, suburban zones, and conflict hotspots to optimize their analysis.
To overcome challenges with data integration, such as discrepancies in location names and the vast size of administrative regions, the researchers designated “admin2s” as the basic unit for their analysis. The team also had to exclude data from Somalia due to its “sporadic and unreliable nature,” which would have negatively impacted the integrity of the regression outcomes.
An Early Warning Tool
Based on these findings, CEWARN has formulated a predictive model that can be used to forecast the likelihood of conflict in the month ahead. This highlights the feasibility of a one-month early warning system. The model integrates observed rainfall data to estimate vegetation health, which then forecasts the probability of conflict. The report recommends the swift development of an operational tool based on these findings to assist policymakers and conflict analysts.
Looking Ahead
While the 2023 study successfully correlated climate data with conflict using a comprehensive and readily available media dataset, it noted that previous studies using CEWARN’s field data had a higher degree of statistical confidence. The report, therefore, recommends a comprehensive approach that integrates both media and field data for a more nuanced understanding of conflict dynamics. It also calls for follow-up research and the development of Standard Operating Procedures (SOPs) for timely data collection, quality assurance, and regular training to ensure a sustainable early warning system.
