NyakweaAnn/Kinetic-Routes-Somalia

Domaine:

peace and securitygeospatial

Type de record:

project

Créateur:

Nya

Hôte:

Predictive humanitarian displacement model correlating conflict, market prices, and population movement. # 🌍 Kinetic Routes: Predictive Displacement Monitoring (Somalia) ### **Executive Summary** This project provides a **Command Center** for humanitarian decision-makers. By correlating live conflict lethality with market stress, the dashboard identifies "push" factors before mass displacement occurs at the border. --- ## 🏗️ The Data Architecture This model synchronizes three disparate datasets into a relational engine: 1. **The Push (Conflict):** ACLED data tracking **93K+ fatalities** in Somalia. 2. **The Stress (Economics):** WFP market data identifying all-time price peaks in **Maize and Sorghum**. 3. **The Result (Movement):** UNHCR displacement figures validated by geographic corridors. --- ## 📊 Technical Methodology - **ETL Process:** Used Power Query to clean and normalize district names (`Admin2`) across conflict and market sources. - **Relational Modeling:** Established a **Many-to-Many** bidirectional relationship between conflict events and price spikes to enable cross-filtering. - **Geospatial Intelligence:** Categorized data by **City/County** to isolate specific transit "choke points" like Belet Hawo. --- ## 🧠 Key Findings - **Trigger Correlation:** Displacement in the Gedo region surges exactly **14 days** after local grain prices exceed historical thresholds. - **Hotspot Identification:** Belet Hawo was identified as a primary "Red Flag" due to the intersection of high fatality rates and peak food prices. --- ## 🏆 Project Impact This dashboard transforms raw humanitarian data into **Operational Intelligence**. - **Predictive Power:** Identifies high-risk departure points 14 days before border arrival spikes. - **Strategic Branding:** Developed under the **Ann Nyakwea: Innovating with Data** framework to bridge the gap between complex analytics and frontline action. --- ## 🛠️ How to View - Download the `.pbix` file in this repository. - Open in **Power BI Desktop**. - Interact with the Map to see real-time filtering of the Hunger and Movemen …

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