Bees-png/Nigeria-malaria-analysis

Power BI project analyzing malaria in Nigeria (2000–2023) # Nigeria Malaria Dashboard (2000–2023) This project is a complete Power BI dashboard that analyzes malaria incidence in Nigeria between 2000 and 2023 using official data from the World Health Organization (WHO). The purpose is to turn raw data into a visual, story-driven dashboard that supports advocacy, monitoring, and better public health decisions. ## Objective To analyze, visualize, and communicate trends in malaria incidence in Nigeria using real-world data and build a professional Power BI dashboard as part of a public health data portfolio. ## Dashboard Preview ## Region Extraction The original dataset was global. I filtered it to focus only on Nigeria using the column `GEO_NAME_SHORT` with this logic: ``` GEO_NAME_SHORT = "Nigeria" ``` This allowed for a focused national-level analysis without the distraction of multiple country data. ## DAX Calculated Columns (New Columns Created) To make the dashboard deeper and more meaningful, I created the following new columns in Power BI using DAX: **1. Year-over-Year (YoY) % Change** This compares the malaria rate of each year to the previous one. ```powerbi YoY_Change = VAR CurrentYear = [DIM_TIME] VAR CurrentRate = [RATE_PER_1000_N] VAR PreviousRate = CALCULATE( MAX([RATE_PER_1000_N]), FILTER( 'Nigeria_Malaria_Incidence', [DIM_TIME] = CurrentYear - 1 ) ) RETURN IF( ISBLANK(PreviousRate) || PreviousRate = 0, BLANK(), DIVIDE(CurrentRate - PreviousRate, PreviousRate) ) ``` **2. Decade** This groups each year into 2000s, 2010s, and 2020s. ```powerbi Decade = INT([DIM_TIME] / 10) * 10 ``` **3. Estimate Gap** This shows the difference between WHO’s upper and lower estimate for each year. ```powerbi Estimate_Gap = [RATE_PER_1000_NU] - [RATE_PER_1000_NL] ``` ## Visuals in the Dashboard - **KPI Cards** for Highest, Lowest, and Average malaria rates - **Line Chart** to show overall trend of malaria from 2000 to 2023 - **Area Chart** showing WHO’s estimate range (upper vs lower) - **Column Chart** to show Year …