FASSSTER Disease Surveillance and Modeling Toolkit

What is it about?

Feasibility Analysis of Syndromic Surveillance Using Spatio-Temporal Epidemiological ModeleR (FASSSTER) for early detection of diseases is a scenario-based disease modeling and surveillance tool developed by the Ateneo Center for Computing Competency and Research (ACCCRe) for use by the Epidemiology Bureau of the Department of Health (DOH). The platform accommodates the implementation of scenario-based compartmental disease models developed in R programming language for time series projections. Designed for Covid-19 monitoring and using statistical and machine learning tools, FASSSTER transforms data into health, health capacity, social, economic, and security indicators that serve as decision points for policy and implementation of programs for localized management of the pandemic.

Based on IATF Resolution No. 85, FASSSTER is considered the main operational disease surveillance and modeling tool for the national government. Stakeholders have recognized the need to provide local government units with access to the same dashboard used by the national agency, especially to those who may not have the capacity to develop and maintain in-house surveillance systems.  As disease surveillance systems may be new to most LGUs, this learning activity aims to provide an introduction to the FASSSTER platform, its features, and how information can be used in the management and monitoring of COVID-19 in their respective localities.

What are the objectives?

At the end of this course, participants should be able to: 

  • EXPLAIN main functions of FASSSTER
  • IDENTIFY data source, processing, and visualization components
  • IDENTIFY the different components of FASSSTER in the FASSSTER Framework
  • ENUMERATE the registration process and  the importance of data use agreements and data privacy
  • SELECT which features in FASSSTER are needed to address specific needs in disease monitoring and surveillance
  • INTERPRET results generated by models and analytics
  • ARTICULATE the FASSSTER SEIR Model and analytical computations in FASSSTER
  • EXPLAIN basic mathematical and analytical concepts used in disease surveillance and modeling
  • DEVELOP/PRODUCE reports that provide information needed for decision making

How long will this course take?

Module 1 – 1 hour

Module 2 – 1 hour

Module 3 – 4 hours

Module 4 – 4 hours

Not Enrolled

Course Includes

  • 6 Lessons
  • 9 Topics
  • 4 Quizzes
  • Course Certificate