FURfect Pulse: Dynamics of Companion Animals using Discrete Exponential Growth Model

Abstract

Monitoring and prediction of companion animal dynamics are essential for public health management, creating opportunities for developing integrated analytical systems supporting comprehensive decision-making. This research presents the development and evaluation of FURfect Pulse, an analytical dashboard designed to monitor and predict companion animal dynamics in Iloilo Province, Philippines. The dashboard integrates descriptive, predictive, and geospatial analysis capabilities to analyze key variables including animal population, vaccination, human deaths, rabies cases, and sterilization data from the Iloilo Provincial Veterinary Office (IPVO) spanning 2018-2024, as well as municipal geographical data. Key features include performance indicator calculations, time series trend analysis, discrete exponential growth modeling for two-year forecasting, and choropleth mapping to visualize the distribution of key variables across municipalities. A hybrid prototyping methodology was employed, combining iterative design approaches with ISO 25010 evaluation standards. System evaluation demonstrated high reliability scores across quality characteristics, with successful validation of integrated analytics capabilities and positive user acceptance ratings. The dashboard achieved research objectives, providing stakeholders with a unified platform for evidence-based decision-making in animal health management. FURfect Pulse represents a significant advancement in companion animal health monitoring systems, offering a scalable solution bridging complex data analysis and practical public health applications, with adaptation potential across similar regional contexts.