Project Overview:

The Vaccination Demand Prediction System is an AI-driven web application that predicts the future demand for vaccines in a specific region based on past data, demographics, seasonal patterns, and health reports. It helps healthcare authorities, hospitals, and vaccine distributors plan inventory, reduce wastage, and ensure timely availability of vaccines.

This project is ideal for showcasing the use of data science and machine learning in public health management.

Technologies Used:

• Frontend: HTML, CSS, Bootstrap, JavaScript

• Backend: Node.js / PHP / Java

• Machine Learning (Model Training): Python (Pandas, scikit-learn, Prophet)

• Database: MySQL / MongoDB

• Visualization: Chart.js, D3.js, or Google Charts

• API Communication: RESTful APIs

Key Features:

1. Admin Dashboard:

• Upload past vaccination records and demographic data

• Monitor region-wise predictions

• Manage vaccine types and stock levels

2. Data Input Modules:

• Input historical data such as:

  • Vaccination counts by age group, vaccine type, and date

  • Regional population data

  • Weather patterns and outbreak history

  • Public awareness campaign dates

3. Prediction Engine:

• Time-series analysis and regression models

  • ARIMA, Linear Regression, Prophet, or Random Forest

• Predicts vaccine demand per:

  • Region

  • Age group

  • Vaccine type

  • Time period (week/month)

4. Visual Reports:

• Line graphs of actual vs predicted demand

• Region-wise heatmaps of demand

• Pie charts for age or vaccine-wise consumption

5. Smart Alerts & Recommendations:

• Alert if predicted demand exceeds stock

• Recommend restocking dates and quantities

• Notifications to staff on upcoming peak demands

6. Export & Reports:

• Downloadable PDF/Excel of demand predictions

• Shareable reports for government or suppliers

7. User Roles:

• Admin: Full control over data, predictions, and reports

• Health Officer: View predictions and manage local reports

• Public View (optional): Show vaccine availability trends