With support from the Department of Science and Technology- Philippine Council for Health Research and Development (DOST-PCHRD), the University of the Philippines Mindanao (UPM) developed an app that can generate forecasts and modes of disease outbreaks.

The application named Disease Watch and Analytics (DiWA) App was developed by the team of Dr. May Anne Mata through the Center for Applied Modeling, Data Analytics, and Bioinformatics for Decision Support Systems in Health (AMDABiDSS-Health), a research center on disease surveillance established under the DOST Niche Centers in the Regions for R&D (NICER) Program. It provides policymakers with data that can be used in formulating strategic interventions against the spread of diseases with three (3) key features, namely: 1) Forecasting Epidemic and Describing Impacts, 2) Epidemic Damage Control, and 3) Models for the Surveillance and the Dynamics of COVID-19.

Currently, the DiWA Team has produced policy briefs on the utilization and integration of the app in the local healthcare system. Its integration is expected to complement existing local and national current approaches for disease surveillance, disease data analysis, and disease risk management. The team has also produced publications, delivered presentations, and conducted training on bioinformatics, predictive modeling, and related topics on disease surveillance.

The DiWA App was developed by taking reference from four pillar research projects of the AMDABiDSS-Health.

“The works of the AMDABiDSS-Health is an example of how one research effort can lead to more useful innovations that will benefit Filipinos,” said DOST-PCHRD Executive Director Dr. Jaime C. Montoya. “We hope that the DiWA App will also bring about health innovations that will make our local communities prepared for various health crises,” he added.

One of the projects contributing to the development of DiWA is the Predictive Modeling and Viral Phylodynamic Analysis on the Spatial and Temporal Patterns of Disease Outbreaks with considerations for Control and Logistics applied in Mindanao Region (PPASTOL) which generated a tool that provides precise predictions of the spread of a disease, the number of cases, deaths, recoveries and other crucial health information.

Also geared towards disease surveillance, another AMDABiDSS-Health study that led to DiWA is the Integrated Wastewater-Based Epidemiology and Data Analytics for Community-Level Pathogen Surveillance and Genetic Tracking: Proof-of-Concept (IWAS). It utilizes bioinformatics, specifically for detection of COVID-19 in wastewater systems.

On triaging and prioritization of interventions, the AMDABiDSS-Health also conducts the Risk Management and Enhanced Survival Analysis Integrated through Longitudinal Infectious Disease Data and Statistical Epidemiological Model using Clinical Risk Factors (RESILIEMC) project which provides health risk maps and information on risk factors across communities in Davao.

Lastly, the project entitled, “Vulnerability Assessment Tool: A Decision Support System for Pre-Emptive Preparedness on Emerging Infections Among Animal Reservoirs in Urban Green Spaces (VATAS),” studies risk assessment on infectious disease, with focus on animal reservoirs and urban green spaces.