Marivull/Egypt-Chronic-Diseases-Dashboard

Comprehensive Power BI dashboard analyzing chronic diseases in Egypt with 118M+ population data covering 33 diseases, risk factors, and economic burden. # Egypt-Chronic-Diseases-Dashboard Comprehensive Power BI dashboard analyzing chronic diseases in Egypt with 118M+ population data covering 33 diseases, risk factors, and economic burden --- ## 🎯 Project Overview This interactive Power BI dashboard provides in-depth analysis of chronic non-communicable diseases (NCDs) in Egypt, covering: - **33 Chronic Diseases** across 9 categories - **14 Risk Factors** affecting 118.4M population - **372.6B EGP** annual economic burden (89% of healthcare budget) - **645K Annual Deaths** from NCDs (81% of all deaths) - **20 Governorates** geographic distribution analysis --- ## 📸 Dashboard Pages ### Page 1: Executive Overview ### Page 2: Disease Categories ### Page 3: Disease-Level Insights ### Page 4: Risk Factors & Comorbidities --- ## 📊 Key Findings ### Disease Prevalence - **71% of Egyptians** (84.1M people) affected by at least one chronic disease - **Top 3 Diseases:** 1. Cardiovascular Diseases - 42.6% (50.4M cases) 2. Hypertension - 40.0% (47.4M cases) 3. Obesity - 35.0% (41.4M cases) ### Economic Impact - **Total Annual Cost:** 372.6 Billion EGP - Direct costs: 231.1B EGP - Indirect costs: 150.7B EGP - **Productivity Loss:** 100.9 Billion EGP/year - **DALYs Lost:** 6.48 Million years ### Risk Factors - **Air Pollution:** 95% exposed (112.5M people) - **Low Fruit/Vegetable Intake:** 85% (100.6M) - **Physical Inactivity:** 74% (87.6M) - **Overweight/Obesity:** 66% (78.1M) ### Egypt vs Global Average - **Obesity:** 2.69x global average (35% vs 13%) - **Diabetes Type 2:** 2.04x global average (22.4% vs 11%) - **Hypertension:** 1.82x global average (40% vs 22%) --- ## 🗂️ Dataset Structure The dashboard uses **12 interconnected CSV files**: | File | Records | Description | |------|---------|-------------| | `1_diseases_prevalence.csv` | 33 | Main disease statistics | | `2_age_distribution.csv` | 60 | Prevalence by age group | | `3_gender_distribution.csv` | 22 | Male vs Female distribution | | `4_risk_fac …