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COVID-19 Vaccination Card Digitization

This project was initiated to address the logistical and durability challenges of standard-sized COVID-19 vaccination certificates by converting government-issued PDFs into portable, double-sided ID cards.

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Overview

Title: COVID-19 Vaccination Card Digitization

Industry: Government / Public Health

Project category: Document Automation and Digital Transformation

Project duration: Approximately 1-2 Weeks

Project Cost: $600

Project started on: Aug, 2020

Role: Creator & Developer

GITHUB URL: https://github.com/hamzaig/CovidVaccinationCertificateToCard

Tags: • COVID-19 • Automation • Document Processing • Python • Government • Healthcare

Description: This project was initiated to address the logistical and durability challenges of standard-sized COVID-19 vaccination certificates. By leveraging Python robust libraries, the development team created an automated system that converts government-issued PDF documents into portable, double-sided ID cards. This made it easier for individuals to carry proof of vaccination and for authorities to verify authenticity.

Problem: Physical vaccination certificates are bulky, prone to wear and tear, and inconvenient for everyday use. Government-issued PDF files often required manual cropping or resizing, making digital or small-format printed versions challenging to produce at scale. This led to inefficiencies and occasional misplacements of critical personal health documents.

Solution: • Python-Based Automation Tool: A custom tool was designed to automatically handle PDF input, auto-crop relevant certificate information, and reshape the content into a standardized ID card template. • Batch Processing: Multiple certificates could be processed at once, simplifying mass issuance and drastically reducing manual intervention. • Digital Output: Output files were generated in a format suited for both printing as double-sided cards and digital storage on smartphones, improving accessibility and portability.

Technologies Used: • Python: Chosen for its extensive ecosystem and readability. • Pillow (PIL Fork): Used for image manipulation tasks such as cropping, resizing, and enhancing image quality. • PyPDF2: Responsible for PDF reading, extraction, and content manipulation.

Impact: • Enhanced Portability: Individuals could conveniently carry a compact double-sided ID card instead of full-page certificates. • Increased Convenience: Frequent verification at airports, workplaces, or public venues became faster and simpler. • Operational Efficiency: Reduced manual labor for government agencies and organizations, speeding up verification processes during public health checks.

Key Highlights

  • Automated conversion of government-issued vaccination PDFs into portable double-sided ID cards
  • Batch processing support for high-volume certificate digitization with minimal manual effort
  • Python + Pillow + PyPDF2 pipeline for reliable parsing, cropping, and formatting
  • Digital and print-friendly outputs for quick verification in public and travel settings
  • Reduced document loss and improved day-to-day accessibility of vaccination records
  • Improved operational efficiency for health verification workflows

Tech Stack

COVID-19AutomationDocument ProcessingPythonGovernmentHealthcare

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