TECHNOLOGY GENERATOR

Dr. Mideth B. Abisado
National University Philippines

THE PROBLEM

Emerging and re-emerging infectious diseases such as COVID-19, tuberculosis, and respiratory infections remain a public health threat in the Philippines. Traditional surveillance systems often lag in detecting outbreaks early, especially in regions with limited data infrastructure. Despite the Department of Health’s use of health records and institutional reports, real-time data that captures early symptoms or sentiment indicators from the public is still lacking. Without timely detection, outbreaks can escalate, resulting in severe public health and economic consequences.

THE SOLUTION

This project introduces HealthPH, an intelligent digital surveillance system that leverages social media platforms, specifically Twitter and Facebook, to detect emerging disease trends in real-time. By analyzing public posts in English, Filipino, and Cebuano, the system identifies keywords and symptom-related phrases associated with infectious diseases. The tool employs machine learning and natural language processing (NLP) to classify and monitor disease trends, providing health authorities with spatially visualized data through an interactive dashboard. This innovation allows for earlier interventions and more informed public health decisions.

TECHNOLOGY DEVELOPMENT STATUS

The project is currently in its development phase. A comprehensive symptom dictionary has been created in multiple languages, and NLP models are being trained on thousands of posts collected from 2019 to 2021. An interactive dashboard prototype has been designed to visualize geographic disease trends, keyword frequency, and tweet sentiment over time. The next steps include refining the models, integrating them into the dashboard, and evaluating the system using real-world historical data. The tool will also undergo ISO 25010 software quality testing and is being positioned for copyright protection and future scale-up.

CURRENT NEEDS

To bring HealthPH to full deployment, the team is seeking partnerships with government agencies, local government units, and healthcare institutions for implementation support and data validation. Collaborations with language and public health experts are needed to expand symptom dictionaries and refine model accuracy. Additionally, technical support for scaling the dashboard, mobile app development, and policy advocacy is essential to embed this tool in national disease response systems and ensure long-term sustainability.

CONTACT DETAILS

Dr. Mideth B. Abisado
National University Philippines
551 M.F. Jhocson Street, Sampaloc, Manila