Global COVID-19 Data Analysis & Outbreak Monitoring System

A SQL-based outbreak monitoring system built on real-world WHO health surveillance data to detect trends, classify risk levels, and identify high-risk regions across 187 countries.

📸 Dashboard Preview

Page 1 — Global Overview

Page 2 — Deep Dive Analysis

Project Overview

This project implements a SQL-based disease outbreak monitoring system that analyzes real-world COVID-19 surveillance data to support public health decision-making.

Core Capabilities:

• Detection of outbreak patterns and transmission trends
• Country-level alert classification (CRITICAL / HIGH / MEDIUM / LOW)
• High-risk region identification using weekly spike threshold analysis
• End-to-end visualization of the pandemic journey from 2020 to 2026

This system is designed to be extensible — the same framework can be applied to monitor future outbreaks of emerging infectious diseases or regional health crises beyond COVID-19.

Datasets Used

Dataset	Source	Size
WHO Global Daily Data	WHO Official	538,080 rows
Country Wise Latest Snapshot	Kaggle	187 countries

Tools & Technologies

Tool	Purpose
MySQL 8.0	Database design, query execution, views
MySQL Workbench	SQL development environment
Power BI Desktop	Interactive dashboard & visualization
WHO / Kaggle	Real-world open-source datasets

Database Structure

Database: mysqlproject1
│
├── who_daily        
│   └── 538,080 rows — Daily country-level case & death tracking
│       Columns: Date_reported, Country, WHO_region, 
│                New_cases, Cumulative_cases, 
│                New_deaths, Cumulative_deaths
│
└── country_latest   
    └── 187 rows — Latest outbreak snapshot per country
        Columns: Country_Region, Confirmed, Deaths, Recovered,
                 Active, New_cases, One_week_pct_increase, WHO_Region

SQL Queries Covered

Data Quality & Validation

• NULL value detection across both tables
• Duplicate record identification
• Data integrity check — cumulative vs confirmed case mismatch

Trend Analysis

• Month-wise global case trend (2020–2026)
• Daily case progression for India — Wave 1 & Wave 2
• Running total of global cases using window functions
• Top 5 worst weeks by global case volume
• Peak month identification (Omicron — Jan 2022)

Alert System & Risk Classification

• Peak alert level classification by country
• Weekly spike detection (>20% threshold trigger)
• Active outbreak monitoring (high active + rising trend)
• Same-day death ratio signal (CRITICAL / WARNING / NORMAL)

Mortality & Recovery Analysis

• Death rate per 100 cases — country level
• Death distribution across WHO regions
• Best recovery rate countries
• Active case burden vs recovery efficiency

Multi-Table JOIN Analysis

• WHO daily trend joined with latest snapshot (SEAR region)
• Cross-dataset data quality validation

SQL View

• outbreak_summary — Aggregated regional view for health officers

Alert Classification Logic

CASE
    WHEN New_cases > 50000 OR One_week_pct_increase > 30 
         THEN 'CRITICAL'  🔴
    WHEN New_cases > 10000 OR One_week_pct_increase > 20 
         THEN 'HIGH'      🟠
    WHEN New_cases > 1000  OR One_week_pct_increase > 10 
         THEN 'MEDIUM'    🟡
    ELSE 'LOW'            🟢
END AS Alert_Level

This logic powers both the world map visual and the scatter chart risk monitor in the dashboard.

Power BI Dashboard

Page 1 — Global Overview

Visual	Chart Type	Purpose
Global Summary	5 KPI Cards	Confirmed, Deaths, Recovered, Active, Countries
Monthly Trend	Line Chart	Pandemic wave detection 2020–2026
WHO Region Comparison	Clustered Bar	Regional active & new case burden
Alert Level Map	Filled Map	Country-level CRITICAL/HIGH/MEDIUM/LOW
India Case Trend	Area Chart	Wave 1 (Sep 2020) & Wave 2 (May 2021)

Page 2 — Deep Dive Analysis

Visual	Chart Type	Purpose
Death Rate by Region	Donut Chart	Europe 6.40% stands out
Weekly Spike Countries	Bar Chart	>20% alert threshold exceeded
Case Outcome Split	Donut Chart	Recovered vs Active vs Deaths
Cumulative Journey	Line Chart	0 to 779M — full pandemic story
Top 10 Countries	Treemap	USA, Brazil, India dominance
Highest Death Rate	Funnel Chart	Yemen → Canada healthcare inequality
Outbreak Risk Monitor	Scatter Chart	Active cases vs weekly spike %

Key Findings

• COVID-19 affected 187 countries with over 16.4 million confirmed cases in this dataset snapshot
• Omicron (January 2022) represented the global peak — 91.7 million cases in a single month
• India's second wave (May 2021) reached 400,000+ daily cases — the highest single-country surge in Asia
• Europe recorded the highest regional death rate at 6.40% per 100 confirmed cases
• Globally, 57% of cases recovered — however recovery rates vary significantly by region
• Americas carried the highest active case burden at 4 million+ active cases
• From mid-2023, global daily cases fell below 10,000 — marking the transition to endemic phase
• Weekly batch reporting patterns and data inconsistencies highlight the importance of data quality validation in surveillance systems

Future Scope

"The monitoring framework developed here can be directly applied to real-time disease surveillance and early warning systems in public health."

• Real-time data pipeline integration with live WHO feeds
• Automated alert notifications to district health officers
• Framework extension to Dengue, Monkeypox, and Influenza monitoring
• District-level granularity for India-specific health surveillance
• Machine learning integration for predictive outbreak forecasting
• Integration with hospital capacity and healthcare resource data

Author

Name: Subhasri

Email: ktsubhasri2005@gmail.com

GitHub: SubhasriiT

LinkedIn: LinkedIn Profile

📜 License

This project uses open-source data from WHO and Kaggle for educational and research purposes only.