Project Overview:

The Disease Spread Tracking Dashboard is a real-time, web-based system that monitors, visualizes, and analyzes the spread of infectious diseases across various regions. It uses data science and IoT integrations (optional) to track outbreak patterns, predict hotspots, and visualize transmission trends on interactive maps and graphs.

This project is particularly relevant in scenarios like tracking COVID-19, dengue, flu, or other local disease outbreaks and can help healthcare providers and authorities make data-driven decisions.

Technologies Used:

• Frontend: HTML, CSS, Bootstrap, JavaScript

• Backend: Node.js / PHP / Java

• Database: MySQL / MongoDB

• Visualization: Chart.js, D3.js, Google Charts, Leaflet.js (for maps)

• ML/AI (optional): Python (scikit-learn for spread prediction)

• IoT (optional): Sensors to collect temperature or health data

Key Features:

1. Admin Panel:

• Manage reported cases and user inputs

• Add new diseases or outbreak types

• Monitor global, national, or regional spread

2. Case Reporting Module:

• Citizens or health officers can report:

  • Type of disease

  • Date of onset

  • Symptoms

  • Location (auto-detected or manually added)

3. Heatmap and Location Tracking:

• Uses GPS coordinates or region names to plot:

  • Disease clusters

  • High-risk zones

  • Daily new cases and recoveries

4. Analytics Dashboard:

• Graphs and stats for:

  • Active vs recovered vs deceased

  • Region-wise growth

  • Time-series analysis of outbreak

5. Predictive Modeling (Optional):

• Predict future spread using:

  • Exponential or logistic regression

  • Time series forecasting

  • Weather or population density correlation

6. Alerts and Notifications:

• Notify users if entering a red zone

• Weekly reports via email or SMS

• Admin alerts when threshold of cases is crossed in a region

7. Role-Based Access:

• Admin: Full access to data and analytics

• Health Officials: Manage entries for their region

• Public Users: View outbreak maps and safety tips