dlangkip/epidash

Interactive epidemiological dashboard visualizing disease trends across Kenya. Built with PHP, Chart.js, and Leaflet for the CEMA Software Engineering Internship. # EpiDash – Epidemiological Data Dashboard **Live Demo:** cema.benfex.net **A data visualization dashboard built to empower evidence-based public health decisions** ## 📊 Dashboard Preview Interactive visualization of epidemiological data across regions, diseases, and time periods --- ## 🔍 Overview **EpiDash** is an interactive web-based dashboard designed to assist epidemiologists, public health researchers, and health officials in visualizing and analyzing epidemiological data across Kenya. Inspired by CEMA's mission to leverage data-driven approaches for infectious disease control, this tool demonstrates the power of digital solutions in modern public health surveillance. The platform offers intuitive visualization of disease trends across regions, demographics, and time periods, turning complex epidemiological data into actionable insights. --- ## 🎯 Project Objectives - **Democratize Data Access**: Create an intuitive interface that makes epidemiological data accessible to both experts and policy makers - **Enhance Analytical Capabilities**: Provide powerful filtering and visualization tools for identifying patterns and trends in disease outbreaks - **Support Decision Making**: Generate exportable reports and visualizations for evidence-based public health interventions - **Ensure Scalability**: Architect a solution that can grow from prototype to production, handling increasing data volumes and user demands --- ## 💻 Key Features | Feature | Description | |--------|-------------| | 📊 **Multi-dimensional Visualization** | Interactive charts for disease trends, regional distributions, and demographic analysis powered by Chart.js | | 🗺️ **Geographic Mapping** | Choropleth maps for visualizing disease prevalence across Kenya's counties using Leaflet.js | | 🔍 **Advanced Filtering** | Dynamic filters for disease type, region, gender, age group, and custom date ranges | | 📅 **Temporal Analysis** | Data grouping by day, week, month, qu …