COVID-19 experience in the Philippines : response, surveillance and monitoring using the FASSSTER platform / Maria Regina Justina Estuar, Elvira De Lara-Tuprio, editors.
2023
RA644.C67 C68 2023eb
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Title
COVID-19 experience in the Philippines : response, surveillance and monitoring using the FASSSTER platform / Maria Regina Justina Estuar, Elvira De Lara-Tuprio, editors.
ISBN
9789819931538
9819931533
9819931533
Published
Singapore : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (xx, 159 pages).
Item Number
10.1007/978-981-99-3153-8 doi
Call Number
RA644.C67 C68 2023eb
Dewey Decimal Classification
362.1962/4144/0954
Summary
This book provides an overview of the extensive work that has been done on the design and implementation of the COVID-19 Philippines Local Government Unit Monitoring Platform, more commonly known as Feasibility Analysis of Syndromic Surveillance Using Spatio-Temporal Epidemiological Modeler for Early Detection of Diseases (FASSSTER). The project began in 2016 as a pilot study in developing a multidimensional approach in disease modeling requiring the development of an interoperable platform to accommodate input of data from various sources including electronic medical records, various disease surveillance systems, social media, online news, and weather data. In 2020, the FASSSTER platform was reconfigured for use in the COVID-19 pandemic. Using lessons learned from the previous design and implementation of the platform toward its full adoption by the Department of Health of the Philippines, this book narrates the story of FASSSTER in two main parts. Part I provides a historical perspective of the FASSSTER platform as a modeling and disease surveillance system for dengue, measles and typhoid, followed by the origins of the FASSSTER framework and how it was reconfigured for the management of COVID-19 information for the Philippines. Part I also explains the different technologies and system components of FASSSTER that paved the way to the operationalization of the FASSSTER model and allowed for seamless rendering of projections and analytics. Part II describes the FASSSTER analytics and models including the Susceptible-Exposed-Infected-Recovered (SEIR) model, the model for time-varying reproduction number, spatiotemporal models and contact tracing models, which became the basis for the imposition of restrictions in mobility translated into localized lockdowns.
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Description based upon print version of record.
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Disaster risk reduction.
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Table of Contents
Part I. COVID-19 Disease Surveillance System in the Philippines
Origins of FASSSTER
Management of COVID-19 Data for the FASSSTER Platform
FASSSTER Data Pipeline and DevOps
Part II. FASSSTER Analytics and Models
Disease Surveillance Metrics and Statistics
Effective Reproduction Number Rt
The FASSSTER SEIR model
Geospatial and spatio-temporal models.
Origins of FASSSTER
Management of COVID-19 Data for the FASSSTER Platform
FASSSTER Data Pipeline and DevOps
Part II. FASSSTER Analytics and Models
Disease Surveillance Metrics and Statistics
Effective Reproduction Number Rt
The FASSSTER SEIR model
Geospatial and spatio-temporal models.