rryesuafuga/uganda-child-health-r-analytics

--- title: Uganda Child Health Analytics R Dashboard emoji: 🏥 colorFrom: blue colorTo: red sdk: docker pinned: false license: mit --- # Uganda Child Health & Nutrition Analytics Dashboard ## Overview This comprehensive R Shiny dashboard supports World Vision's mission to improve child health outcomes in Uganda through advanced statistical analysis and data-driven insights. ## Features ### 🌍 Multi-Focus Areas Addressing World Vision's key focus areas: - **Child Health & Mortality**: Track and predict under-5 and infant mortality rates - **Nutrition**: Monitor stunting, wasting, and underweight prevalence - **WASH**: Analyze water and sanitation access impact on health - **Disease Prevention**: Track malaria, HIV, and tuberculosis indicators - **Maternal Health**: Evaluate antenatal care and skilled birth attendance ### 📊 Advanced Statistical Techniques 1. **Generalized Linear Models (GLM)** - Multiple regression analysis for health determinants - Ridge and LASSO regression for feature selection - Model diagnostics and validation 2. **Causal Inference with Propensity Score Matching** - Evaluate intervention effectiveness - Control for confounding variables - Estimate average treatment effects 3. **Machine Learning with Random Forests** - Predict health outcomes using ensemble methods - Feature importance analysis - Model performance evaluation 4. **Intervention Simulation** - Design multi-sector health programs - Budget optimization - Cost-effectiveness analysis - Lives saved estimation ### 🎯 Key Capabilities - **Interactive Visualizations**: Dynamic Plotly charts for data exploration - **Real-time Analysis**: Instant model updates based on user inputs - **Regional Comparison**: Identify disparities across Uganda's regions - **Temporal Trends**: Track progress over time (2010-2023) - **Predictive Modeling**: Forecast future health outcomes ## Data Sources The dashboard integrates multiple Uganda health indicators: - Child mortality rates (under-5 and infa …