georgixxx/kenya-poverty-resilience-map

## Technical Report: The Resilience Map **Project: 2025/2026 Strategic Budget Allocation for Arid and Semi-Arid Lands (ASAL)** Analyst and Author: Brightone Onyango --- ## Table of Contents 1. Executive Summary 2. The Data Dictionary 3. Ingestion and Validation Logic 4. Socio-Economic Insight 5. Strategic Recommendations --- ## 1. Executive Summary This report details the automated analysis of projected vulnerability trends in Kenya to guide the 2025/2026 agricultural subsidy budget. By utilizing high-integrity humanitarian data, we identified regions where vulnerability, specifically the population living in informal settlements, remains consistently above the 45% critical intervention threshold. These findings provide the objective evidence required to prioritize resource distribution in high-risk areas. --- ## 2. The Data Dictionary To ensure transparency in our decision-making model, we utilized a standardized Data Dictionary to define our core metrics. This ensures that technical and non-technical stakeholders share a common understanding of the indicators driving the budget. | Field | Description | |---|---| | **Indicator Name** | The socio-economic metric under observation. In this analysis, we focused on the percentage of the urban population living in slum conditions. | | **Value** | The numerical percentage or count associated with the indicator. | | **Reference Year** | The temporal data point for the observation or projection, allowing for longitudinal trend analysis. | | **Poverty Headcount Ratio (P)** | A fundamental metric represented by the formula $P = \frac{q}{n}$, where $q$ is the number of individuals below the poverty line and $n$ is the total population. | --- ## 3. Ingestion and Validation Logic Public datasets often suffer from structural noise that can lead to the misallocation of funds if not handled programmatically. Our ingestion pipeline utilizes an automated validation layer to ensure data integrity. ### Handling HXL Me …