COVID-19 Experience in the Philippines [electronic resource] : Response, Surveillance and Monitoring Using the FASSSTER Platform / edited by Maria Regina Justina Estuar, Elvira De Lara-Tuprio.

Contributor(s):

Material type: Text

TextLanguage: English Series: Publication details: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.Edition: 1st ed. 2023Description: XX, 159 p. 65 illus., 58 illus. in color. online resourceISBN:

9789819931538

Subject(s):

DDC classification:

551 23
363.34 23

Online resources:

Click Here

Contents:

Chapter 1. Origins of FASSSTER -- Chapter 2. Management of COVID-19 Data for the FASSSTER Platform -- Chapter 3. FASSSTER Data Pipeline and DevOps -- Chapter 4. Disease Surveillance Metrics and Statistics -- Chapter 5. Effective Reproduction Number Rt -- Chapter 6. The FASSSTER SEIR Model -- Chapter 7. Geospatial and Spatio-Temporal Models. .

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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Holdings
Item type	Current library	Call number	Materials specified	Status	Date due	Barcode	Item holds
E-Books	National Library of India Online Resource	551 \| 363.34 (Browse shelf(Opens below))		Available		EBK000044527ENG

Total holds: 0

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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