A Web-Based Real-Time Pandemic Monitoring System

A pandemic monitoring system is a web-based software platform designed to collect, track, analyze, and display real-time data on infectious disease outbreaks. Many public health institutions, especially in regions like Africa, face significant challenges in monitoring pandemic trends due to fragmented reporting systems, lack of predictive analytics, and delayed public communication. This project seeks to design and develop a responsive web application that provides a centralized platform for tracking pandemic cases, predicting future outbreaks, issuing real-time notifications, and disseminating verified news updates to users. The design, development, and implementation of pandemic monitoring systems have become critical in public health infrastructure, particularly in responding to fast-spreading diseases such as COVID-19 and Ebola. Existing systems, such as WHO dashboards and CDC outbreak trackers, provide important functionalities but often lack features like integrated AI prediction, user-specific alerts, and local community-level data display— features which our proposed system addresses. The methodology and tools used for the development and deployment of this system follow the AGILE METHODOLOGY for its iterative and user-centered development process. Tools and technologies include Next.js, Node.js, MySQL, Tailwind CSS, and real-time data APIs. System testing showed the platform successfully tracked and visualized case data, allowed admin management of news and user roles, and delivered real-time alerts and notifications. The system also featured an AI-driven chatbot and prediction model to assist users in decision-making. This system successfully implements and extends the core functionalities of pandemic monitoring platforms while offering greater interactivity, flexibility, and real-time public health engagement.