Real-Time Pandemic Simulation Engine Using Web-Based Technologies

Pandemic modeling and simulation play a critical role in understanding the spread of infectious diseases and evaluating intervention strategies. Traditional epidemiological tools are often complex, resource-intensive, and not easily accessible for educational or exploratory use. This paper presents PATHOGEN, a web-based real-time pandemic simulation engine developed using HTML, CSS, and JavaScript. The system models disease spread using agent-based simulation and visualizes interactions dynamically through an interactive interface. Users can modify key parameters such as transmission rate, recovery time, infection radius, and intervention strategies including social distancing, vaccination, and quarantine.

The application provides real-time statistical insights including susceptible, infected, recovered, and deceased populations, along with epidemic curves and reproduction metrics. The system operates entirely on client-side processing, ensuring fast performance and accessibility without backend dependencies. Experimental results demonstrate the system’s effectiveness in simulating emergent epidemic behavior and enabling intuitive understanding of disease dynamics. The proposed solution serves as an educational and analytical tool for studying epidemic spread and intervention impact.