A government-supported initiative that aims to create a hub for different data sources to facilitate understanding of the spread of diseases will undergo enhancements to create a predictive model for Covid-19.
The added module for Feasibility Analysis of Syndromic Surveillance using Spatio-Temporal Epidemiological Modeler (FASSSTER) will allow forecasting of possible cases in a given area at a specified period of time.
Data generated from this model will support the decision-making of the Department of Health, local government units, and healthcare facilities, in terms of resource planning and other measures to mitigate the spread of the virus.
The tool was developed by Dr. Regina Justina E. Estuar of Ateneo de Manila University and her team, with support from the Department of Science and Technology’s Philippine Council for Health Research and Development (DOST-PCHRD).
At the moment, FASSSTER is used for creating predictive models and visualizing possible scenarios of outbreaks of dengue, typhoid fever, and measles, at specified time periods. It uses data from the Department of Health’s Philippine Integrated Disease Surveillance and Response (PIDSR) system, Electronic Medical Records, and SMS-based reports of primary care facilities.
The latest addition to the technology is its TUGON feature, an SMS-based reporting feature which allows staff from rural health units and barangay health stations to report cases of dengue, measles, and typhoid fever through text commands.
To date, FASSSTER had been deployed and tested in the Department of Health Regional Office VI where 17 rural health units (RHUs) have been trained in the use of the SMS-based reporting system for surveillance of dengue, typhoid fever, and measles.