bellotijani38/MALARIA-SURVEILLANCE-

Built an interactive two-page Power BI dashboard analyzing 4 years of quarterly malaria data across Nigeria's 37 states. Cleaned data in Power Query, developed 7 DAX measures, and uncovered key insights on disease burden, seasonality, ITN coverage, and vulnerable populations. # 🦟 Malaria Surveillance Dashboard — Nigeria (2020–2023) An interactive two-page Power BI dashboard analyzing four years of quarterly malaria surveillance data across all 36 Nigerian states and the Federal Capital Territory. The project covers the full analytics workflow — data cleaning, DAX measure development, dashboard design, and insight extraction — using a synthetic dataset built for capstone/portfolio purposes. --- ## 📊 Dashboard Preview ### Page 1 — National Overview ### Page 2 — Geographic & Data Quality --- ## 🎯 Project Overview This project analyzes 600 rows of quarterly malaria data (37 states × 4 years × 4 quarters, plus a partial 2024 Q1 sample) to answer: - How has malaria burden changed nationally from 2020–2023? - Which states and zones carry the highest burden? - Does ITN (insecticide-treated net) coverage actually correlate with lower incidence? - What role does seasonality/rainfall play? - How much of the burden falls on children under 5 and pregnant women? - Where are the data-quality gaps in reporting? --- ## 🧹 Data Cleaning (Power Query) - Verified completeness (0 missing values) and uniqueness (0 duplicates) across all 14 original columns - Trimmed whitespace and standardized text fields (State, Geopolitical_Zone, Quarter, Quarter_Months) - Corrected data types (Whole Number for counts, Decimal for rates/percentages) - Added a Quarter_Num column so Q1–Q4 sort chronologically, not alphabetically - Merged FCT into North Central via Table.ReplaceValue, matching Nigeria's official 6-zone structure (confirmed: 6 distinct values, 0% errors) - Validated logical integrity (deaths never exceed cases; all percentages fall within 0–100%) - Identified and excluded incomplete 2024 data (8 of 37 states, Q1 only) from all KPI totals and trends - Added a Burden_Tier column (Low / Moderate / High / Very High) based on incidence thresholds --- ## 🧮 DAX Measures Total Cases = SUM(Malaria_Data[Reported_Malaria_Cases]) Total …